Lobar intracerebral haemorrhage: Analysis of a series and characteristics of patients receiving antiplatelet or anticoagulation treatment

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Romero López, J.L. Maciñeiras Montero, M. Fontanillo Fontanillo, D. Escriche Jaime, M.J. Moreno Carretero, E. Corredera García" "autores" => array:6 [ 0 => array:4 [ "nombre" => "J." "apellidos" => "Romero López" "email" => array:1 [ 0 => "jesus.Romero.Lopez@Sergas.Es" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "¿" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "J.L." "apellidos" => "Maciñeiras Montero" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "M." "apellidos" => "Fontanillo Fontanillo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "D." "apellidos" => "Escriche Jaime" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "M.J." "apellidos" => "Moreno Carretero" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "E." "apellidos" => "Corredera García" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Sección de Neurología, Hospital do Meixoeiro (CHUVI), Vigo, Pontevedra, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Unidad de Apoyo a la Investigación, Hospital do Meixoeiro (CHUVI), Vigo, Pontevedra, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Hemorragia intracerebral lobular: análisis de una serie y características en pacientes antiagregados y anticoagulados" ] ] "textoCompleto" => "IntroductionDue to their specific location, aetiology, and prognosis, lobar intracerebral haemorrhages (LICH) are different from other types of intracerebral haemorrhages (ICH). According to different series, they account for 14%–39% of all ICH.<a class="elsevierStyleCrossRefs" href="#bib0005">1–5</a> LICH occurs in the cortical–subcortical junction of the cerebral lobes and usually extends along a plane parallel to the adjacent cerebral cortex. It may affect any of the cerebral lobes, but it most commonly presents in one or more lobes of the parietal-occipital-temporal association area.<a class="elsevierStyleCrossRefs" href="#bib0010">2–5</a> The various causes of LICH coincide with the aetiologies of other types of ICH; in LICH, however, high blood pressure plays a less important role and cerebral amyloid angiopathy (CAA) appears more frequently. Although high blood pressure causes 80% of basal ganglia haemorrhages, it only occurs in 30%–50% of LICH cases.<a class="elsevierStyleCrossRefs" href="#bib0020">4–8</a> Other aetiological factors, such as arteriovenous malformations, occur in 7%–20% of LICH cases; tumours are present in 7%–9%, and blood or clotting disorders are found with 5%–20% cases of haemorrhages.<a class="elsevierStyleCrossRefs" href="#bib0010">2–5,9</a>The purpose of this study is to evaluate a consecutive series of 162 patients with LICH and analyse LICH patient subgroups with a prior history of antiplatelet or anticoagulation treatment. We recorded demographic, aetiological, and clinical differences, outcome, and the bleeding volume plus its predictive value for mortality.Patients and methodsWe conducted a retrospective study of a series of 162 consecutive LICH patients drawn from a database of stroke patients admitted to the neurology department at Hospital Meixoeiro in Vigo (CHUVI) between January 1991 and December 2009. Stroke subtypes were classified according to the guidelines drawn up by the Spanish Society of Neurology's Cerebrovascular Diseases Study Group.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> All patients in the series were admitted to the neurology department in the first 24 h after symptom onset. They were diagnosed and monitored by one of the department's neurologists according to the Spanish Society of Neurology's stroke care protocols.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> Patients cared for by other departments were not included in the study.Patients were diagnosed with LICH if they had non-traumatic intraparenchymal haemorrhages and met the following criteria: (a) medical history, examination and brain CT compatible with intracerebral haemorrhage; (b) primary location of the haemorrhage in the cortical or cortical–subcortical region, in one or more cerebral lobes (in some cases, it was difficult to distinguish between lobar and deep cerebral haemorrhages. Those located within 1cm of the lateral ventricular wall were considered deep or basal ganglia haemorrhages; when the haemorrhage location was unclear, the CT scan was reviewed by a group of neurologists and radiologists in order to reach a consensus). Some included cases also featured (c) cortical vessel rupture with bleeding into the subarachnoid space or ventricular invasion.<a class="elsevierStyleCrossRef" href="#bib0010">2</a>The following exclusion criteria were applied: traumatic LICH, LICH secondary to an arteriovenous malformation bleed, cavernous haemangioma, primary or metastatic brain tumours, and cerebral infarctions with haemorrhagic conversion. Cases of LICH associated with subarachnoid haemorrhage were included when the latter was found to be secondary to the lobar haemorrhage and not associated with aneurysm or arteriovenous malformation. In all patients, we ruled out the presence of an underlying pathology behind the haemorrhage with the aid of subsequent neuroimaging studies (CT scan or brain MRI).The data collection protocol included the following: age, sex, and intracerebral haemorrhage risk factors according to international criteria.<a class="elsevierStyleCrossRefs" href="#bib0015">3,10,11</a> Diagnosis of any risk factor or factors and their treatment at the time of the haemorrhage had to be recorded in the patient's medical history. We also recorded clinical manifestations upon admission, possible aetiology or aetiologies of LICH indicated by the neurologist on the patient's discharge report, and outcome as either death or survival. LICH cases associated with possible, probable, or definite diagnoses of CAA were classified according to the Boston CAA Group guidelines.<a class="elsevierStyleCrossRef" href="#bib0060">12</a> We specifically recorded prior treatment with oral antiplatelet and anticoagulation agents.All patients had a brain CT scan taken during the first 6 h after admission. Bleed volume was measured using the standard formula for volume (cc)=A·B·C/2 (where A is the largest cross-sectional diameter of the haemorrhage in cm, B is the largest diameter perpendicular to A, and C is the number of 1-cm tomographic slices intersecting the haemorrhage).<a class="elsevierStyleCrossRef" href="#bib0065">13</a> The CT scanners used during these years were ProSpeed, HiSpeed Spiral and Lightspeed VCT models built by General Electric.Certain patients had a brain MRI taken between the first and the sixth month after the haemorrhage so as to rule out LICH secondary to an underlying lesion.Within this series, we analysed two subgroups: LICH patients previously treated with the anticoagulation agent Sintrom® and patients previously treated with antiplatelet agents (aspirin, triflusal, or clopidogrel). We compared patients’ different demographic, clinical and aetiological variables, as well as the bleed volume in the 2 subgroups, to patients with LICH who had not received antiplatelet or anticoagulation agents.Statistical analysis was performed with the Statistical Package for Social Sciences programme version 15.0 (SPSS, Chicago, United States).We performed a descriptive analysis of the variables included in the study. For qualitative variables, we used frequencies and percentages, and for quantitative variables, we used standard deviation, range, median, and interquartile range.We used the t test to compare ages between the 2 patient subgroups receiving anticoagulation and antiplatelet agents. In the overall series, the t test was also used to compare patients with no anticoagulation and antiplatelet agents with those receiving either anticoagulation or antiplatelet agents. We used the median test to measure the haemorrhage volume shown by the CT scan in each of the different patient subgroups.We compared risk factors, clinical data, and aetiology among different patient subgroups using univariate analysis (χ2 test or Fisher's exact test). The Kolmogorov–Smirnov test was used to study normality. P<.05 was considered statistically significant.The variables best predicting risk of death were determined by means of a backward stepwise logistic regression model based on the maximum likelihood method. Death was considered the dependent variable (coded as 1=yes, 0=no). Covariates were those shown to be clinically relevant or significant in the univariate analysis. The odds ratio (OR) and 95% confidence interval were estimated based on the coefficients and standard deviations. Sensitivity and specificity of the bleed volume with respect to death were determined by using receiver operating characteristic (ROC) curves to determine the best cut-off point.ResultsA total of 5248 stroke patients were treated by the Hospital Meixoeiro neurology department between January 1991 and December 2009. Of these patients, 994 (18.9%) were diagnosed with ICH. The ICH group included 162 patients with LICH. That subgroup comprised 16.4% of the patients with ICH and 3% of the total stroke patients treated in this department.Results of the retrospective analysis of the general series of 162 LICH patients are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. Of the LICH patient total, 54% were women and the mean age of both sexes was 73.7 years, with a range of 35–95 years. Women had a mean age of 76.3 with a range of 35–93 years, while men had a mean age of 70.8 with a range of 40–95 years. Vascular risk factors, aetiology, symptoms, outcome (death/survival), and haemorrhage volume measured by CT are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. Since LICH may have multiple causes, we determined the number of patients with both high blood pressure and CAA, and the combination of HBP, CAA, and antiplatelet or anticoagulation therapy.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>The results of the subgroups of patients who received antiplatelet agents (n=32) or anticoagulation agents (n=16) prior to LICH are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. The table also displays age and sex distribution, vascular risk factors, aetiology, clinical characteristics, outcome, and bleeding volume.<elsevierMultimedia ident="tbl0010"></elsevierMultimedia>Patients treated with Sintrom® upon arrival at the emergency department had an anticoagulation level of 3.26 (measured by the International Normalised Ratio, INR) with a range of 1.35–11.28 and a typical deviation of 2.4.Comparison of both subgroups revealed significant age-related differences between women receiving antiplatelet agents and those treated with anticoagulation agents. As we might expect, heart disease is significantly more common among patients receiving anticoagulation agents. The presence of high blood pressure, diabetes mellitus type 2 (DM 2), and death was also significant. Deaths were more frequent in the group of patients receiving anticoagulation agents. Haemorrhage volume was larger in the patients receiving anticoagulation agents, but the difference was not significant.The comparative analysis between the general LICH series (excluding patients treated with antiplatelet or anticoagulation agents) and the group of patients receiving anticoagulation agents (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>) revealed significant differences related to age, but not to sex. Heart disease was also significantly more frequent in the group of patients receiving anticoagulation agents, as was to be expected.<elsevierMultimedia ident="tbl0015"></elsevierMultimedia>There were no significant differences for the other vascular risk factors except for DM 2. There were also no significant differences between the 2 subgroups with regard to aetiology and symptoms. Deaths were more frequent in the group of patients treated with anticoagulation agents. However, this result was not significant compared to the group of LICH patients without antiplatelet or anticoagulation treatment. Nevertheless, the median haemorrhage volume was 3 times higher in the patient subgroup treated with anticoagulation agents, and the difference was clearly significant (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>).In our series, the median haemorrhage volume was 30.2cc. In our patients, the volume of the CT scan had a high predictive value for death (area under the ROC curve, 0.88; P<.001). The cut-off point was 37.8cc (sensitivity 78% and specificity 72%).In the group of patients receiving antiplatelet agents, the median volume was 41.5cc. In LICH patients who did not receive antiplatelet or anticoagulation agents, median volume was 27.8cc. This difference was significant (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). In this subgroup, the cut-off point for death was a bleeding volume of 58cc, with a sensitivity of 100% and a specificity of 76% (area under the ROC curve, 1; P<.001).There was no relationship between INR (mean, 3.2) upon arrival at the hospital and haemorrhage volume in the anticoagulation group. One patient had an INR of 11.28 and a haemorrhage volume of 84cc, and another patient had an INR of 2.7 and a haemorrhage volume of 283cc. Haemorrhage volume also had a low predictive value for death in this subgroup since the area under the ROC curve was only 0.68.According to the multivariate logistic regression analysis of the general series, there was a significant association between death and the variables sex and haemorrhage volume quantified by CT. OR for haemorrhage volume was 1.032, and OR for female sex was 5.37 (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>). In the anticoagulation group, there was no significant link between bleeding volume and death due to the dispersion of the data and the low number of patients.<elsevierMultimedia ident="tbl0020"></elsevierMultimedia>DiscussionBetween 1991 and 2009, LICH accounted for 3% of the total stroke patients treated in the neurology department at Hospital Meixoeiro, Vigo, Spain; this figure was similar to that reported in another study.<a class="elsevierStyleCrossRef" href="#bib0020">4</a> LICH also accounted for 16.4% of the total ICH patients attended, a lower percentage than that reported by other published studies.<a class="elsevierStyleCrossRefs" href="#bib0010">2,14</a> In our study, females are slightly predominant and mean age is similar to that in other studies.<a class="elsevierStyleCrossRefs" href="#bib0020">4,15</a>Vascular risk factors recorded in our series are similar to those in the literature,<a class="elsevierStyleCrossRefs" href="#bib0010">2–4</a> with the exception of one series with an increased incidence of high blood pressure.<a class="elsevierStyleCrossRef" href="#bib0040">8</a> There were no significant differences between the patient subgroup treated with antiplatelet agents and the subgroup on anticoagulation agents except that heart disease was more frequent in the second group, which was to be expected.In our general series, the frequency of clinical manifestations (hemiparesis, aphasia, and changes in alertness) was similar to those listed in other series of LICH patients.<a class="elsevierStyleCrossRefs" href="#bib0010">2,4,8,9</a> Headache frequency, however, was lower among our patients.<a class="elsevierStyleCrossRefs" href="#bib0010">2–4</a> Our study found no significant differences in clinical presentation between the general series and the LICH patient subgroups treated with antiplatelet and anticoagulation agents, or between the last two subgroups.We found a high mortality rate for LICH (25% in our series) which was very similar to rates given in other studies.<a class="elsevierStyleCrossRefs" href="#bib0015">3–5,7</a> This study found no significant differences for percentage of deaths between the general series without antiplatelet and anticoagulation agents (114 patients) and the patient subgroup treated with antiplatelet agents (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). Comparing the general series with the patient group on anticoagulation agents shows that the mortality rate is almost twice as high in the anticoagulation group. This rate approaches statistical significance but does not reach it, probably due to the low number of patients in the anticoagulation group (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). There are more deaths in the anticoagulation group than in the antiplatelet group (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>), but the difference is not significant.The literature does not report the incidence of death in LICH patients previously treated with antiplatelet or anticoagulation agents, which is why our study provides a novel contribution. However, we found one study of a series of ICH patients previously treated with antiplatelet agents in which the in-hospital mortality rate was nearly identical to the one in our antiplatelet subgroup (about 25% in both studies).<a class="elsevierStyleCrossRef" href="#bib0080">16</a> There are also series of ICH cases associated with anticoagulation in which in-hospital mortality rates are quite similar to the one in our anticoagulation subgroup (between 35% and 45%).<a class="elsevierStyleCrossRefs" href="#bib0085">17–19</a> The aetiologies (or combinations of aetiologies) underlying LICH were similar to those in other published series: high blood pressure, diabetes, heart disease, prior stroke, and dyslipidaemia.<a class="elsevierStyleCrossRefs" href="#bib0010">2–5</a> According to the Boston CAA Group guidelines, the presence of possible or probable CAA (close to 75%) was similar to that reported by a study including an anatomical pathology assessment.<a class="elsevierStyleCrossRef" href="#bib0060">12</a> This highlights the important role that disease plays in lobar haemorrhages. Incidence of CAA was similar to the above study in the antiplatelet patient group, but lower in the anticoagulation group.In our series, the median bleeding volume was 30.2cc, slightly lower than the volume in an earlier series published by our group,<a class="elsevierStyleCrossRef" href="#bib0025">5</a> and also lower than the volumes reported in other studies.<a class="elsevierStyleCrossRefs" href="#bib0015">3,15,20</a> As we stated in another previous study, the haemorrhage volume quantified by CT upon admission showed a high predictive value for death in the overall series.<a class="elsevierStyleCrossRef" href="#bib0025">5</a>We also found that haemorrhage volume had a high predictive value for death, with a cut-off point of 58cc, in the patient group treated with antiplatelet agents. This is a new finding which is relevant for managing LICH and for potential approaches to treatment. However, the same result could not be demonstrated in the anticoagulation group since this patient subgroup was quite small and bleeding volumes varied greatly.The considerable difference between mean haemorrhage volume in the patient subgroup without antiplatelet or anticoagulation agents and the antiplatelet patient subgroup (27.8cc versus 41.5cc) may be explained by the action of the antiplatelet agents, and also in part by the significant age difference between groups. It was recently determined that LICH volume is related to age. The older the patient is, the larger the bleed volume.<a class="elsevierStyleCrossRef" href="#bib0075">15</a>CAA is the most frequent cause of LICH<a class="elsevierStyleCrossRefs" href="#bib0025">5,12</a> and it is associated with ApoE alleles ¿2 and ¿4.<a class="elsevierStyleCrossRef" href="#bib0070">14</a> It is often present in patients with Alzheimer disease.<a class="elsevierStyleCrossRef" href="#bib0105">21</a> Brain microbleeds, especially those located in the cortex, can be detected by using gradient echo MR imaging. They are indicative of CAA.<a class="elsevierStyleCrossRefs" href="#bib0110">22,23</a> It is also known that these microbleeds are predictors of a greater tendency towards LICH in patients treated with anticoagulation agents. Elderly patients should therefore be checked for microbleeds prior to anticoagulation treatment, and presence of microbleeds must be factored into the risk-benefit ratio for anticoagulation.<a class="elsevierStyleCrossRefs" href="#bib0085">17,24</a> It was recently shown that antiplatelet treatment with aspirin in LICH patients may increase the risk of bleed recurrence.<a class="elsevierStyleCrossRef" href="#bib0125">25</a>Our study has a number of limitations since it is a retrospective series spanning 19 years. Patients were not monitored after discharge, which is why we have no information regarding long-term outcomes, bleed recurrences, or other potentially interesting variables. The small size of the LICH patient subgroup treated with anticoagulation agents does not permit us to gather significant data. However, death rates in this group are much higher than in the rest of the series.Our study reveals interesting information on LICH aetiology, clinical manifestations, and the differences in death rate associated with prior use of antiplatelet or anticoagulation agents. We also feel that it would be interesting to define cut-off points for haemorrhage volume that would enable us to predict patient mortality in the different subgroups under study.Conflicts of interestThe authors have no conflicts of interest to declare." "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:2 [ "identificador" => "xres169974" "titulo" => array:5 [ 0 => "Abstract" 1 => "Introduction" 2 => "Patients and methods" 3 => "Results" 4 => "Conclusions" ] ] 1 => array:2 [ "identificador" => "xpalclavsec158047" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xres169973" "titulo" => array:5 [ 0 => "Resumen" 1 => "Introducción" 2 => "Pacientes y métodos" 3 => "Resultados" 4 => "Conclusiones" ] ] 3 => array:2 [ "identificador" => "xpalclavsec158048" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "Patients and methods" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Conflicts of interest" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2011-05-18" "fechaAceptado" => "2011-07-30" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec158047" "palabras" => array:4 [ 0 => "Anticoagulation" 1 => "Antiplatelet" 2 => "Lobar intracerebral haemorrhage" 3 => "Prognostic variables" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec158048" "palabras" => array:4 [ 0 => "Anticoagulación" 1 => "Antiagregación" 2 => "Hemorragia intracerebral lobular" 3 => "Variables pronósticas" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "IntroductionLobar intracerebral haemorrhage (LICH) is a rare cause of stroke which accounts for about 20% of primary intracerebral haemorrhages. The most common causes are cerebral amyloid angiopathy (CAA), high blood pressure and others, such as using antiplatelet or anticoagulation agents.We analysed a series of patients with LICH and compared it with subgroups of patients with LICH who were previously receiving antiplatelet or anticoagulation agents. We determined the volume of the bleeding and its predictive value for mortality. Patients and methodsWe consecutively and retrospectively included 162 patients diagnosed with LICH and cared for in the Neurology Department of Hospital Meixoeiro in Vigo between 1991 and 2009. We collected demographic characteristics, risk factors, aetiologies and symptoms, and conducted a comparative analysis between the general series and the subgroups of patients receiving anticoagulation and antiplatelet agents. ResultsIn the general series, the most common cause was possible or probable CAA followed by hypertension. In the subgroup of patients receiving antiplatelet or anticoagulation agents there were no differences in the variables studied, except for the frequency of heart disease. Nonetheless, there were differences with respect to age, heart disease and bleeding volume between the general series (patients not treated with antiplatelet or anticoagulation agents) when compared with the subgroups of patients receiving antiplatelet and anticoagulation agents. ConclusionsWe provide new information regarding the clinical behaviour of LICH and its differences in patients receiving antiplatelet or anticoagulation agents. Mortality is higher in cases of LICH on anticoagulants. Female sex and the volume of bleeding are predictors of mortality." ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "IntroducciónLa hemorragia intracerebral lobular (HIL) es una causa poco frecuente de ictus y representan cerca del 20% de las hemorragias intracerebrales primarias. La causa más frecuente son la angiopatía amiloidea cerebral (AAC), la hipertensión arterial (HTA) y otras como el tratamiento antiagregante o anticoagulante.Analizar una serie de pacientes con HIL y compararla con subgrupos de pacientes con HIL antiagregados o anticoagulados previamente. Determinar el volumen de la hemorragia y su valor predictivo de mortalidad. Pacientes y métodosSe incluyó de forma consecutiva y retrospectiva a 162 pacientes diagnosticados de HIL y atendidos en el servicio de neurología del Hospital Meixoeiro de Vigo entre los años 1991 y 2009. Se recogieron características demográficas, factores de riesgo, etiologías y clínica, y se realizó un análisis comparativo entre la serie general y los subgrupos de paciente antiagregados y anticoagulados. ResultadosEn la serie general la causa más frecuente fue la AAC posible o probable seguida de la HTA. En los subgrupos de pacientes antiagregados o anticoagulados no había diferencias en las variables estudiadas excepto en la frecuencia de cardiopatía. Sí existían diferencias en cuanto a la edad, la cardiopatía y la volumen de la hemorragia entre la serie general (sin los pacientes antiagregados o anticoagulados) cuando se compararon con los subgrupos de antiagregados y anticoagulados. ConclusionesAportamos algunas novedades respecto al comportamiento clínico de la HIL y sus diferencias en los pacientes antiagregados o anticoagulados. La mortalidad es superior en las HIL anticoaguladas. Son variables predictivas de defunción el sexo femenino y el volumen de la hemorragia." ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Romero López J, et al. Hemorragia intracerebral lobular: análisis de una serie y características en pacientes antiagregados y anticoagulados. Neurología. 2012;27:387–93." ] ] "multimedia" => array:4 [ 0 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "CAA: cerebral amyloid angiopathy; SD: standard deviation; DM 2: type 2 diabetes mellitus; HBP: high blood pressure; IQR: interquartile range; CT scan: computed tomography (brain)." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">N=162 \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Demographic factors</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Females, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87 (53.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD; range, years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73.7±11.3; (35–95) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD; range, years (female) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.3±10.4; (35–93) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD; range, years (male) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70.8±11.6; (40–95) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cardiovascular risk factors,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73 (45.1) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Prior stroke \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37 (22.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Antiplatelet drugs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 (19.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Heart disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 (17.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DM 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (12.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alcohol \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (7.4) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Dyslipidaemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (8.0) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Anticoagulation agents \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (9.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Smoking \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (4.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Blood clotting disorders \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (2.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DM \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (1.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aetiologies,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73 (45.1) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CAA</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Possible \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">106 (65.4) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Probable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (9.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Anticoagulation agents \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 (9.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Antiplatelet therapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 (19.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alcohol abuse \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (6.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP+CAA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">53 (32.7) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP+CAA+anticoagulation agents \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (1.2) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP+CAA+antiplatelet agents \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (6.8) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Clinical characteristics,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemiparesis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">89 (54.9) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aphasia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54 (33.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Coma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31 (19.0) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Headache \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 (25.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemianopia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (16.0) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Drowsiness \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (8.0) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stupor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 (10.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Disorientation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (6.2) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Death, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 (25.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median volume by CT (IQR), cc \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30.2 (13.9–68.2) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab264934.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Descriptive results from the general series." ] ] 1 => array:7 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "SD: standard deviation; IQR: interquartile range." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Antiplatelet agents (n=32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Anticoagulation agents (n=16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">P \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Demographic factors</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Females, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (46.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (50.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.838 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD; range, years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78.9±7.4; (62–91) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.6±5.3; (68–85) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.252 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD; range, years; female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82.3±6.0; (73–91) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.0±4.7; (68–82) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.018 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age (SD); range, years; male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.1±7.4; (62–91) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77.1±6.2; (69–85) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.728 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Vascular risk factors,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (43.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.221 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Prior stroke \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (28.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (37.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.509 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Heart disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (75.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DM 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (31.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.267 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alcohol \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Dyslipidaemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (9.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.712 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Smoking \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.475 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aetiology,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (40.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.153 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CAA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.002<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Possible \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 (75.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Probable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alcohol abuse \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Unknown \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Clinical characteristics,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemiparesis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (59.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.835 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aphasia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (40.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (31.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.527 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Coma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (21.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.808 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Headache \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (28.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (37.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.509 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemianopia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.772 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Drowsiness \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.610 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stupor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (18.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.563 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Death \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (43.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.186 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median volume in CT scan (IQR), cc \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41.5 (27.8–99.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 (38.8–122.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.0666 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab264935.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "Expected frequency lower than 5." ] ] ] "descripcion" => array:1 [ "en" => "Results of the comparative univariate analysis of patient subgroups treated with antiplatelet and anticoagulation agents." ] ] 2 => array:7 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "SD: standard deviation; IQR=interquartile range." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Series (n=114) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Anticoagulation agents (n=16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">P \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Antiplatelet agents (n=32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">P \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Demographic factors</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Females, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64 (56.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (50.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.644 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (46.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.353 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD, years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72±12.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76.6±5.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.010 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79±7.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD, years, female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">75±11.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76±4.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.785 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82±6.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.017 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean age±SD, years, male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68±12.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77±6.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.046 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76±7.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.013 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Vascular risk factors,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49 (43.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.142 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (43.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.938 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Prior stroke \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (19.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (37.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.097 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (28.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.281 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Heart disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (7.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (75.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.004<a class="elsevierStyleCrossRef" href="#tblfn0010">a</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DM 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (31.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.021 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.259 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alcohol \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (10.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.171 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.054 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Dyslipidaemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (7.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.817 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (9.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.788 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Smoking \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (6.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.308 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.508 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Blood clotting disorders \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (3.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.447 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.283 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DM \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (2.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.511 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.354 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aetiology,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HBP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 (43.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.161 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (40.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.744 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CAA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.000<a class="elsevierStyleCrossRef" href="#tblfn0010">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.734 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Possible \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79 (69.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (18.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 (75.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Probable \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 (10.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alcohol abuse \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (9.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.194 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.068 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Unknown \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (11.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.154 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.160 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Clinical characteristics,n(%)</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemiparesis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60 (52.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (62.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.458 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (59.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.499 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Aphasia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 (31.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (31.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.979 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (40.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.338 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Coma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20 (17.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.472 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (21.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.577 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Headache \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (22.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 (37.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.201 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 (28.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.534 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemianopia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (16.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.672 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 (15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.888 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Drowsiness \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (9.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.660 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.235 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stupor \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (18.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.213 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.527 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Disorientation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.218 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.083 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hemianaesthesia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 (0.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.707 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.595 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Death \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (22.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (43.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.071 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (25.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.795 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median volume in CT scan (IQR), cc \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27.8 (12–48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 (39–123) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41.5 (28–95) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.033 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab264936.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "a" "nota" => "Two boxes have an expected frequency of less than 5." ] ] ] "descripcion" => array:1 [ "en" => "Results of the comparative univariate analysis of the general series (excluding patients treated with antiplatelet or anticoagulation agents) and the patient subgroups treated with antiplatelet or anticoagulation agents." ] ] 3 => array:7 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "SE: standard error; OR: odds ratio; CI: confidence interval." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Variables \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">B \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SE \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">P \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">OR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">95% CI for OR</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Inferior \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" style="border-bottom: 2px solid black">Superior \t\t\t\t\t\t\n \t\t\t\t</td></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sex (female) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.681 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.589 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.370 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.692 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.043 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CTvol \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.031 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.005 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.032 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.021 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.043 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab264937.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Risk of death associated with the predictive variables." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:25 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:1 [ "host" => array:1 [ 0 => array:1 [ "LibroEditado" => array:2 [ "titulo" => "Guía para el diagnóstico y tratamiento del ictus. 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Hemorragia intracerebral lobular: análisis de una serie y características en pacientes antiagregados y anticoagulados

J. Romero Lópeza,

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jesus.Romero.Lopez@Sergas.Es

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, J.L. Maciñeiras Monteroa, M. Fontanillo Fontanillob, D. Escriche Jaimea, M.J. Moreno Carreteroa, E. Corredera Garcíaa

a Sección de Neurología, Hospital do Meixoeiro (CHUVI), Vigo, Pontevedra, Spain

b Unidad de Apoyo a la Investigación, Hospital do Meixoeiro (CHUVI), Vigo, Pontevedra, Spain

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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Due to their specific location&#44; aetiology&#44; and prognosis&#44; lobar intracerebral haemorrhages &#40;LICH&#41; are different from other types of intracerebral haemorrhages &#40;ICH&#41;&#46; According to different series&#44; they account for 14&#37;&#8211;39&#37; of all ICH&#46;<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#8211;5</span></a> LICH occurs in the cortical&#8211;subcortical junction of the cerebral lobes and usually extends along a plane parallel to the adjacent cerebral cortex&#46; It may affect any of the cerebral lobes&#44; but it most commonly presents in one or more lobes of the parietal-occipital-temporal association area&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#8211;5</span></a> The various causes of LICH coincide with the aetiologies of other types of ICH&#59; in LICH&#44; however&#44; high blood pressure plays a less important role and cerebral amyloid angiopathy &#40;CAA&#41; appears more frequently&#46; Although high blood pressure causes 80&#37; of basal ganglia haemorrhages&#44; it only occurs in 30&#37;&#8211;50&#37; of LICH cases&#46;<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4&#8211;8</span></a> Other aetiological factors&#44; such as arteriovenous malformations&#44; occur in 7&#37;&#8211;20&#37; of LICH cases&#59; tumours are present in 7&#37;&#8211;9&#37;&#44; and blood or clotting disorders are found with 5&#37;&#8211;20&#37; cases of haemorrhages&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#8211;5&#44;9</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The purpose of this study is to evaluate a consecutive series of 162 patients with LICH and analyse LICH patient subgroups with a prior history of antiplatelet or anticoagulation treatment&#46; We recorded demographic&#44; aetiological&#44; and clinical differences&#44; outcome&#44; and the bleeding volume plus its predictive value for mortality&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Patients and methods</span><p id="par0015" class="elsevierStylePara elsevierViewall">We conducted a retrospective study of a series of 162 consecutive LICH patients drawn from a database of stroke patients admitted to the neurology department at Hospital Meixoeiro in Vigo &#40;CHUVI&#41; between January 1991 and December 2009&#46; Stroke subtypes were classified according to the guidelines drawn up by the Spanish Society of Neurology&#39;s Cerebrovascular Diseases Study Group&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> All patients in the series were admitted to the neurology department in the first 24 h after symptom onset&#46; They were diagnosed and monitored by one of the department&#39;s neurologists according to the Spanish Society of Neurology&#39;s stroke care protocols&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Patients cared for by other departments were not included in the study&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Patients were diagnosed with LICH if they had non-traumatic intraparenchymal haemorrhages and met the following criteria&#58; &#40;a&#41; medical history&#44; examination and brain CT compatible with intracerebral haemorrhage&#59; &#40;b&#41; primary location of the haemorrhage in the cortical or cortical&#8211;subcortical region&#44; in one or more cerebral lobes &#40;in some cases&#44; it was difficult to distinguish between lobar and deep cerebral haemorrhages&#46; Those located within 1<span class="elsevierStyleHsp" style=""></span>cm of the lateral ventricular wall were considered deep or basal ganglia haemorrhages&#59; when the haemorrhage location was unclear&#44; the CT scan was reviewed by a group of neurologists and radiologists in order to reach a consensus&#41;&#46; Some included cases also featured &#40;c&#41; cortical vessel rupture with bleeding into the subarachnoid space or ventricular invasion&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">The following exclusion criteria were applied&#58; traumatic LICH&#44; LICH secondary to an arteriovenous malformation bleed&#44; cavernous haemangioma&#44; primary or metastatic brain tumours&#44; and cerebral infarctions with haemorrhagic conversion&#46; Cases of LICH associated with subarachnoid haemorrhage were included when the latter was found to be secondary to the lobar haemorrhage and not associated with aneurysm or arteriovenous malformation&#46; In all patients&#44; we ruled out the presence of an underlying pathology behind the haemorrhage with the aid of subsequent neuroimaging studies &#40;CT scan or brain MRI&#41;&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">The data collection protocol included the following&#58; age&#44; sex&#44; and intracerebral haemorrhage risk factors according to international criteria&#46;<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3&#44;10&#44;11</span></a> Diagnosis of any risk factor or factors and their treatment at the time of the haemorrhage had to be recorded in the patient&#39;s medical history&#46; We also recorded clinical manifestations upon admission&#44; possible aetiology or aetiologies of LICH indicated by the neurologist on the patient&#39;s discharge report&#44; and outcome as either death or survival&#46; LICH cases associated with possible&#44; probable&#44; or definite diagnoses of CAA were classified according to the Boston CAA Group guidelines&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> We specifically recorded prior treatment with oral antiplatelet and anticoagulation agents&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">All patients had a brain CT scan taken during the first 6 h after admission&#46; Bleed volume was measured using the standard formula for volume &#40;cc&#41;<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">A</span>&#183;<span class="elsevierStyleItalic">B</span>&#183;<span class="elsevierStyleItalic">C</span>&#47;2 &#40;where <span class="elsevierStyleItalic">A</span> is the largest cross-sectional diameter of the haemorrhage in cm&#44; <span class="elsevierStyleItalic">B</span> is the largest diameter perpendicular to <span class="elsevierStyleItalic">A</span>&#44; and <span class="elsevierStyleItalic">C</span> is the number of 1-cm tomographic slices intersecting the haemorrhage&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> The CT scanners used during these years were ProSpeed&#44; HiSpeed Spiral and Lightspeed VCT models built by General Electric&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Certain patients had a brain MRI taken between the first and the sixth month after the haemorrhage so as to rule out LICH secondary to an underlying lesion&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">Within this series&#44; we analysed two subgroups&#58; LICH patients previously treated with the anticoagulation agent Sintrom<span class="elsevierStyleSup">&#174;</span> and patients previously treated with antiplatelet agents &#40;aspirin&#44; triflusal&#44; or clopidogrel&#41;&#46; We compared patients&#8217; different demographic&#44; clinical and aetiological variables&#44; as well as the bleed volume in the 2 subgroups&#44; to patients with LICH who had not received antiplatelet or anticoagulation agents&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">Statistical analysis was performed with the Statistical Package for Social Sciences programme version 15&#46;0 &#40;SPSS&#44; Chicago&#44; United States&#41;&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">We performed a descriptive analysis of the variables included in the study&#46; For qualitative variables&#44; we used frequencies and percentages&#44; and for quantitative variables&#44; we used standard deviation&#44; range&#44; median&#44; and interquartile range&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">We used the <span class="elsevierStyleItalic">t</span> test to compare ages between the 2 patient subgroups receiving anticoagulation and antiplatelet agents&#46; In the overall series&#44; the <span class="elsevierStyleItalic">t</span> test was also used to compare patients with no anticoagulation and antiplatelet agents with those receiving either anticoagulation or antiplatelet agents&#46; We used the median test to measure the haemorrhage volume shown by the CT scan in each of the different patient subgroups&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">We compared risk factors&#44; clinical data&#44; and aetiology among different patient subgroups using univariate analysis &#40;<span class="elsevierStyleItalic">&#967;</span><span class="elsevierStyleSup">2</span> test or Fisher&#39;s exact test&#41;&#46; The Kolmogorov&#8211;Smirnov test was used to study normality&#46; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;05 was considered statistically significant&#46;</p><p id="par0070" class="elsevierStylePara elsevierViewall">The variables best predicting risk of death were determined by means of a backward stepwise logistic regression model based on the maximum likelihood method&#46; Death was considered the dependent variable &#40;coded as 1<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>yes&#44; 0<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>no&#41;&#46; Covariates were those shown to be clinically relevant or significant in the univariate analysis&#46; The odds ratio &#40;OR&#41; and 95&#37; confidence interval were estimated based on the coefficients and standard deviations&#46; Sensitivity and specificity of the bleed volume with respect to death were determined by using receiver operating characteristic &#40;ROC&#41; curves to determine the best cut-off point&#46;</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Results</span><p id="par0075" class="elsevierStylePara elsevierViewall">A total of 5248 stroke patients were treated by the Hospital Meixoeiro neurology department between January 1991 and December 2009&#46; Of these patients&#44; 994 &#40;18&#46;9&#37;&#41; were diagnosed with ICH&#46; The ICH group included 162 patients with LICH&#46; That subgroup comprised 16&#46;4&#37; of the patients with ICH and 3&#37; of the total stroke patients treated in this department&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">Results of the retrospective analysis of the general series of 162 LICH patients are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; Of the LICH patient total&#44; 54&#37; were women and the mean age of both sexes was 73&#46;7 years&#44; with a range of 35&#8211;95 years&#46; Women had a mean age of 76&#46;3 with a range of 35&#8211;93 years&#44; while men had a mean age of 70&#46;8 with a range of 40&#8211;95 years&#46; Vascular risk factors&#44; aetiology&#44; symptoms&#44; outcome &#40;death&#47;survival&#41;&#44; and haemorrhage volume measured by CT are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; Since LICH may have multiple causes&#44; we determined the number of patients with both high blood pressure and CAA&#44; and the combination of HBP&#44; CAA&#44; and antiplatelet or anticoagulation therapy&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">The results of the subgroups of patients who received antiplatelet agents &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>32&#41; or anticoagulation agents &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>16&#41; prior to LICH are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46; The table also displays age and sex distribution&#44; vascular risk factors&#44; aetiology&#44; clinical characteristics&#44; outcome&#44; and bleeding volume&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0090" class="elsevierStylePara elsevierViewall">Patients treated with Sintrom<span class="elsevierStyleSup">&#174;</span> upon arrival at the emergency department had an anticoagulation level of 3&#46;26 &#40;measured by the International Normalised Ratio&#44; INR&#41; with a range of 1&#46;35&#8211;11&#46;28 and a typical deviation of 2&#46;4&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">Comparison of both subgroups revealed significant age-related differences between women receiving antiplatelet agents and those treated with anticoagulation agents&#46; As we might expect&#44; heart disease is significantly more common among patients receiving anticoagulation agents&#46; The presence of high blood pressure&#44; diabetes mellitus type 2 &#40;DM 2&#41;&#44; and death was also significant&#46; Deaths were more frequent in the group of patients receiving anticoagulation agents&#46; Haemorrhage volume was larger in the patients receiving anticoagulation agents&#44; but the difference was not significant&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">The comparative analysis between the general LICH series &#40;excluding patients treated with antiplatelet or anticoagulation agents&#41; and the group of patients receiving anticoagulation agents &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41; revealed significant differences related to age&#44; but not to sex&#46; Heart disease was also significantly more frequent in the group of patients receiving anticoagulation agents&#44; as was to be expected&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">There were no significant differences for the other vascular risk factors except for DM 2&#46; There were also no significant differences between the 2 subgroups with regard to aetiology and symptoms&#46; Deaths were more frequent in the group of patients treated with anticoagulation agents&#46; However&#44; this result was not significant compared to the group of LICH patients without antiplatelet or anticoagulation treatment&#46; Nevertheless&#44; the median haemorrhage volume was 3 times higher in the patient subgroup treated with anticoagulation agents&#44; and the difference was clearly significant &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">In our series&#44; the median haemorrhage volume was 30&#46;2<span class="elsevierStyleHsp" style=""></span>cc&#46; In our patients&#44; the volume of the CT scan had a high predictive value for death &#40;area under the ROC curve&#44; 0&#46;88&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&#41;&#46; The cut-off point was 37&#46;8<span class="elsevierStyleHsp" style=""></span>cc &#40;sensitivity 78&#37; and specificity 72&#37;&#41;&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">In the group of patients receiving antiplatelet agents&#44; the median volume was 41&#46;5<span class="elsevierStyleHsp" style=""></span>cc&#46; In LICH patients who did not receive antiplatelet or anticoagulation agents&#44; median volume was 27&#46;8<span class="elsevierStyleHsp" style=""></span>cc&#46; This difference was significant &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; In this subgroup&#44; the cut-off point for death was a bleeding volume of 58<span class="elsevierStyleHsp" style=""></span>cc&#44; with a sensitivity of 100&#37; and a specificity of 76&#37; &#40;area under the ROC curve&#44; 1&#59; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&#41;&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">There was no relationship between INR &#40;mean&#44; 3&#46;2&#41; upon arrival at the hospital and haemorrhage volume in the anticoagulation group&#46; One patient had an INR of 11&#46;28 and a haemorrhage volume of 84<span class="elsevierStyleHsp" style=""></span>cc&#44; and another patient had an INR of 2&#46;7 and a haemorrhage volume of 283<span class="elsevierStyleHsp" style=""></span>cc&#46; Haemorrhage volume also had a low predictive value for death in this subgroup since the area under the ROC curve was only 0&#46;68&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">According to the multivariate logistic regression analysis of the general series&#44; there was a significant association between death and the variables sex and haemorrhage volume quantified by CT&#46; OR for haemorrhage volume was 1&#46;032&#44; and OR for female sex was 5&#46;37 &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46; In the anticoagulation group&#44; there was no significant link between bleeding volume and death due to the dispersion of the data and the low number of patients&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Discussion</span><p id="par0130" class="elsevierStylePara elsevierViewall">Between 1991 and 2009&#44; LICH accounted for 3&#37; of the total stroke patients treated in the neurology department at Hospital Meixoeiro&#44; Vigo&#44; Spain&#59; this figure was similar to that reported in another study&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> LICH also accounted for 16&#46;4&#37; of the total ICH patients attended&#44; a lower percentage than that reported by other published studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#44;14</span></a> In our study&#44; females are slightly predominant and mean age is similar to that in other studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4&#44;15</span></a></p><p id="par0135" class="elsevierStylePara elsevierViewall">Vascular risk factors recorded in our series are similar to those in the literature&#44;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#8211;4</span></a> with the exception of one series with an increased incidence of high blood pressure&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> There were no significant differences between the patient subgroup treated with antiplatelet agents and the subgroup on anticoagulation agents except that heart disease was more frequent in the second group&#44; which was to be expected&#46;</p><p id="par0140" class="elsevierStylePara elsevierViewall">In our general series&#44; the frequency of clinical manifestations &#40;hemiparesis&#44; aphasia&#44; and changes in alertness&#41; was similar to those listed in other series of LICH patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#44;4&#44;8&#44;9</span></a> Headache frequency&#44; however&#44; was lower among our patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#8211;4</span></a> Our study found no significant differences in clinical presentation between the general series and the LICH patient subgroups treated with antiplatelet and anticoagulation agents&#44; or between the last two subgroups&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">We found a high mortality rate for LICH &#40;25&#37; in our series&#41; which was very similar to rates given in other studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3&#8211;5&#44;7</span></a> This study found no significant differences for percentage of deaths between the general series without antiplatelet and anticoagulation agents &#40;114 patients&#41; and the patient subgroup treated with antiplatelet agents &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; Comparing the general series with the patient group on anticoagulation agents shows that the mortality rate is almost twice as high in the anticoagulation group&#46; This rate approaches statistical significance but does not reach it&#44; probably due to the low number of patients in the anticoagulation group &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; There are more deaths in the anticoagulation group than in the antiplatelet group &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#44; but the difference is not significant&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">The literature does not report the incidence of death in LICH patients previously treated with antiplatelet or anticoagulation agents&#44; which is why our study provides a novel contribution&#46; However&#44; we found one study of a series of ICH patients previously treated with antiplatelet agents in which the in-hospital mortality rate was nearly identical to the one in our antiplatelet subgroup &#40;about 25&#37; in both studies&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> There are also series of ICH cases associated with anticoagulation in which in-hospital mortality rates are quite similar to the one in our anticoagulation subgroup &#40;between 35&#37; and 45&#37;&#41;&#46;<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">17&#8211;19</span></a> The aetiologies &#40;or combinations of aetiologies&#41; underlying LICH were similar to those in other published series&#58; high blood pressure&#44; diabetes&#44; heart disease&#44; prior stroke&#44; and dyslipidaemia&#46;<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2&#8211;5</span></a> According to the Boston CAA Group guidelines&#44; the presence of possible or probable CAA &#40;close to 75&#37;&#41; was similar to that reported by a study including an anatomical pathology assessment&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> This highlights the important role that disease plays in lobar haemorrhages&#46; Incidence of CAA was similar to the above study in the antiplatelet patient group&#44; but lower in the anticoagulation group&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">In our series&#44; the median bleeding volume was 30&#46;2<span class="elsevierStyleHsp" style=""></span>cc&#44; slightly lower than the volume in an earlier series published by our group&#44;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> and also lower than the volumes reported in other studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3&#44;15&#44;20</span></a> As we stated in another previous study&#44; the haemorrhage volume quantified by CT upon admission showed a high predictive value for death in the overall series&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a></p><p id="par0160" class="elsevierStylePara elsevierViewall">We also found that haemorrhage volume had a high predictive value for death&#44; with a cut-off point of 58<span class="elsevierStyleHsp" style=""></span>cc&#44; in the patient group treated with antiplatelet agents&#46; This is a new finding which is relevant for managing LICH and for potential approaches to treatment&#46; However&#44; the same result could not be demonstrated in the anticoagulation group since this patient subgroup was quite small and bleeding volumes varied greatly&#46;</p><p id="par0165" class="elsevierStylePara elsevierViewall">The considerable difference between mean haemorrhage volume in the patient subgroup without antiplatelet or anticoagulation agents and the antiplatelet patient subgroup &#40;27&#46;8<span class="elsevierStyleHsp" style=""></span>cc versus 41&#46;5<span class="elsevierStyleHsp" style=""></span>cc&#41; may be explained by the action of the antiplatelet agents&#44; and also in part by the significant age difference between groups&#46; It was recently determined that LICH volume is related to age&#46; The older the patient is&#44; the larger the bleed volume&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a></p><p id="par0170" class="elsevierStylePara elsevierViewall">CAA is the most frequent cause of LICH<a class="elsevierStyleCrossRefs" href="#bib0025"><span class="elsevierStyleSup">5&#44;12</span></a> and it is associated with ApoE alleles ¿2 and ¿4&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> It is often present in patients with Alzheimer disease&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> Brain microbleeds&#44; especially those located in the cortex&#44; can be detected by using gradient echo MR imaging&#46; They are indicative of CAA&#46;<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">22&#44;23</span></a> It is also known that these microbleeds are predictors of a greater tendency towards LICH in patients treated with anticoagulation agents&#46; Elderly patients should therefore be checked for microbleeds prior to anticoagulation treatment&#44; and presence of microbleeds must be factored into the risk-benefit ratio for anticoagulation&#46;<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">17&#44;24</span></a> It was recently shown that antiplatelet treatment with aspirin in LICH patients may increase the risk of bleed recurrence&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a></p><p id="par0175" class="elsevierStylePara elsevierViewall">Our study has a number of limitations since it is a retrospective series spanning 19 years&#46; Patients were not monitored after discharge&#44; which is why we have no information regarding long-term outcomes&#44; bleed recurrences&#44; or other potentially interesting variables&#46; The small size of the LICH patient subgroup treated with anticoagulation agents does not permit us to gather significant data&#46; However&#44; death rates in this group are much higher than in the rest of the series&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">Our study reveals interesting information on LICH aetiology&#44; clinical manifestations&#44; and the differences in death rate associated with prior use of antiplatelet or anticoagulation agents&#46; We also feel that it would be interesting to define cut-off points for haemorrhage volume that would enable us to predict patient mortality in the different subgroups under study&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle">Conflicts of interest</span><p id="par0185" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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          "titulo" => "Patients and methods"
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            0 => "Anticoagulation"
            1 => "Antiplatelet"
            2 => "Lobar intracerebral haemorrhage"
            3 => "Prognostic variables"
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            0 => "Anticoagulaci&#243;n"
            1 => "Antiagregaci&#243;n"
            2 => "Hemorragia intracerebral lobular"
            3 => "Variables pron&#243;sticas"
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        "titulo" => "Abstract"
        "resumen" => "<span class="elsevierStyleSectionTitle">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Lobar intracerebral haemorrhage &#40;LICH&#41; is a rare cause of stroke which accounts for about 20&#37; of primary intracerebral haemorrhages&#46; The most common causes are cerebral amyloid angiopathy &#40;CAA&#41;&#44; high blood pressure and others&#44; such as using antiplatelet or anticoagulation agents&#46;</p><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">We analysed a series of patients with LICH and compared it with subgroups of patients with LICH who were previously receiving antiplatelet or anticoagulation agents&#46; We determined the volume of the bleeding and its predictive value for mortality&#46;</p> <span class="elsevierStyleSectionTitle">Patients and methods</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">We consecutively and retrospectively included 162 patients diagnosed with LICH and cared for in the Neurology Department of Hospital Meixoeiro in Vigo between 1991 and 2009&#46; We collected demographic characteristics&#44; risk factors&#44; aetiologies and symptoms&#44; and conducted a comparative analysis between the general series and the subgroups of patients receiving anticoagulation and antiplatelet agents&#46;</p> <span class="elsevierStyleSectionTitle">Results</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">In the general series&#44; the most common cause was possible or probable CAA followed by hypertension&#46; In the subgroup of patients receiving antiplatelet or anticoagulation agents there were no differences in the variables studied&#44; except for the frequency of heart disease&#46; Nonetheless&#44; there were differences with respect to age&#44; heart disease and bleeding volume between the general series &#40;patients not treated with antiplatelet or anticoagulation agents&#41; when compared with the subgroups of patients receiving antiplatelet and anticoagulation agents&#46;</p> <span class="elsevierStyleSectionTitle">Conclusions</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">We provide new information regarding the clinical behaviour of LICH and its differences in patients receiving antiplatelet or anticoagulation agents&#46; Mortality is higher in cases of LICH on anticoagulants&#46; Female sex and the volume of bleeding are predictors of mortality&#46;</p>"
      ]
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        "resumen" => "<span class="elsevierStyleSectionTitle">Introducci&#243;n</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">La hemorragia intracerebral lobular &#40;HIL&#41; es una causa poco frecuente de ictus y representan cerca del 20&#37; de las hemorragias intracerebrales primarias&#46; La causa m&#225;s frecuente son la angiopat&#237;a amiloidea cerebral &#40;AAC&#41;&#44; la hipertensi&#243;n arterial &#40;HTA&#41; y otras como el tratamiento antiagregante o anticoagulante&#46;</p><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Analizar una serie de pacientes con HIL y compararla con subgrupos de pacientes con HIL antiagregados o anticoagulados previamente&#46; Determinar el volumen de la hemorragia y su valor predictivo de mortalidad&#46;</p> <span class="elsevierStyleSectionTitle">Pacientes y m&#233;todos</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Se incluy&#243; de forma consecutiva y retrospectiva a 162 pacientes diagnosticados de HIL y atendidos en el servicio de neurolog&#237;a del Hospital Meixoeiro de Vigo entre los a&#241;os 1991 y 2009&#46; Se recogieron caracter&#237;sticas demogr&#225;ficas&#44; factores de riesgo&#44; etiolog&#237;as y cl&#237;nica&#44; y se realiz&#243; un an&#225;lisis comparativo entre la serie general y los subgrupos de paciente antiagregados y anticoagulados&#46;</p> <span class="elsevierStyleSectionTitle">Resultados</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">En la serie general la causa m&#225;s frecuente fue la AAC posible o probable seguida de la HTA&#46; En los subgrupos de pacientes antiagregados o anticoagulados no hab&#237;a diferencias en las variables estudiadas excepto en la frecuencia de cardiopat&#237;a&#46; S&#237; exist&#237;an diferencias en cuanto a la edad&#44; la cardiopat&#237;a y la volumen de la hemorragia entre la serie general &#40;sin los pacientes antiagregados o anticoagulados&#41; cuando se compararon con los subgrupos de antiagregados y anticoagulados&#46;</p> <span class="elsevierStyleSectionTitle">Conclusiones</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Aportamos algunas novedades respecto al comportamiento cl&#237;nico de la HIL y sus diferencias en los pacientes antiagregados o anticoagulados&#46; La mortalidad es superior en las HIL anticoaguladas&#46; Son variables predictivas de defunci&#243;n el sexo femenino y el volumen de la hemorragia&#46;</p>"
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        "nota" => "<p class="elsevierStyleNotepara">Please cite this article as&#58; Romero L&#243;pez J&#44; et al&#46; Hemorragia intracerebral lobular&#58; an&#225;lisis de una serie y caracter&#237;sticas en pacientes antiagregados y anticoagulados&#46; Neurolog&#237;a&#46; 2012&#59;27&#58;387&#8211;93&#46;</p>"
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          "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">CAA&#58; cerebral amyloid angiopathy&#59; SD&#58; standard deviation&#59; DM 2&#58; type 2 diabetes mellitus&#59; HBP&#58; high blood pressure&#59; IQR&#58; interquartile range&#59; CT scan&#58; computed tomography &#40;brain&#41;&#46;</p>"
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                  \t\t\t\t"><span class="elsevierStyleBold">Demographic factors</span></td></tr><tr title="table-row"><td class="td" title="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Females&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">87 &#40;53&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Mean age</span><span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">SD&#59; range&#44; years</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">73&#46;7<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;3&#59; &#40;35&#8211;95&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Mean age</span><span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">SD&#59; range&#44; years &#40;female&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">76&#46;3<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>10&#46;4&#59; &#40;35&#8211;93&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Mean age</span><span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">SD&#59; range&#44; years &#40;male&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">70&#46;8<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>11&#46;6&#59; &#40;40&#8211;95&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Cardiovascular risk factors&#44;</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">n</span></span><span class="elsevierStyleBold">&#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HBP</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">73 &#40;45&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Prior stroke</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">37 &#40;22&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Antiplatelet drugs</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">32 &#40;19&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Heart disease</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">28 &#40;17&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">DM 2</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">20 &#40;12&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Alcohol</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12 &#40;7&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Dyslipidaemia</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13 &#40;8&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Anticoagulation agents</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16 &#40;9&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Smoking</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8 &#40;4&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Blood clotting disorders</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4 &#40;2&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">DM</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;1&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Aetiologies&#44;</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">n</span></span><span class="elsevierStyleBold">&#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HBP</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">73 &#40;45&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CAA</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Possible&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">106 &#40;65&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Probable&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">15 &#40;9&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Anticoagulation agents</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16 &#40;9&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Antiplatelet therapy</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">32 &#40;19&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Alcohol abuse</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11 &#40;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HBP</span><span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CAA</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">53 &#40;32&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HBP</span><span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CAA</span><span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">anticoagulation agents</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;1&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HBP</span><span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CAA</span><span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">antiplatelet agents</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11 &#40;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Clinical characteristics&#44;</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">n</span></span><span class="elsevierStyleBold">&#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Hemiparesis</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">89 &#40;54&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Aphasia</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">54 &#40;33&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Coma</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">31 &#40;19&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Median volume by CT &#40;IQR&#41;&#44; cc&nbsp;\t\t\t\t\t\t\n
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                  """
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">5 &#40;15&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">5 &#40;31&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0 &#40;0&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">0 &#40;0&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;9&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">1 &#40;6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">1 &#40;3&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0 &#40;0&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;475&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Aetiology&#44;</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">n</span></span><span class="elsevierStyleBold">&#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">HBP</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">13 &#40;40&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">10 &#40;62&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">CAA</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#46;002<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Possible&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">24 &#40;75&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">4 &#40;25&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Probable&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">2 &#40;6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">1 &#40;6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0 &#40;0&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0 &#40;0&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Unknown</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">1 &#40;3&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0 &#40;0&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Clinical characteristics&#44;</span><span class="elsevierStyleItalic"><span class="elsevierStyleBold">n</span></span><span class="elsevierStyleBold">&#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Hemiparesis</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19 &#40;59&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">10 &#40;62&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;835&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Aphasia</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13 &#40;40&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;31&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;527&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Coma</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7 &#40;21&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4 &#40;25&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;808&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Headache</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9 &#40;28&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6 &#40;37&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;509&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Hemianopia</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5 &#40;15&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;12&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;772&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Drowsiness</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;3&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;610&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Stupor</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4 &#40;12&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;18&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;563&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Death</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8 &#40;25&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7 &#40;43&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;186&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Median volume in CT scan &#40;IQR&#41;&#44; cc</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">78 &#40;38&#46;8&#8211;122&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
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                  """
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Article information

ISSN: 21735808
Original language: English

DOI:10.1016/j.nrleng.2011.07.004

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Year/Month	Html	Pdf	Total

2024 November	5	1	6
2024 October	33	5	38
2024 September	26	0	26
2024 August	32	14	46
2024 July	25	4	29
2024 June	22	1	23
2024 May	30	3	33
2024 April	24	2	26
2024 March	54	4	58
2024 February	31	8	39
2024 January	13	4	17
2023 December	17	8	25
2023 November	18	3	21
2023 October	16	5	21
2023 September	14	3	17
2023 August	16	4	20
2023 July	11	5	16
2023 June	21	2	23
2023 May	34	4	38
2023 April	34	0	34
2023 March	11	5	16
2023 February	17	4	21
2023 January	18	6	24
2022 December	22	1	23
2022 November	15	5	20
2022 October	24	14	38
2022 September	28	8	36
2022 August	21	12	33
2022 July	13	4	17
2022 June	12	6	18
2022 May	17	5	22
2022 April	12	11	23
2022 March	29	7	36
2022 February	20	5	25
2022 January	46	6	52
2021 December	15	7	22
2021 November	15	10	25
2021 October	21	14	35
2021 September	29	13	42
2021 August	11	7	18
2021 July	14	8	22
2021 June	14	11	25
2021 May	18	13	31
2021 April	25	7	32
2021 March	12	7	19
2021 February	13	7	20
2021 January	17	13	30
2020 December	12	9	21
2020 November	15	4	19
2020 October	12	5	17
2020 September	15	11	26
2020 August	11	8	19
2020 July	6	11	17
2020 June	6	5	11
2020 May	14	7	21
2020 April	11	4	15
2020 March	15	8	23
2020 February	9	7	16
2020 January	13	14	27
2019 December	23	9	32
2019 November	9	7	16
2019 October	17	4	21
2019 September	19	7	26
2019 August	11	4	15
2019 July	16	9	25
2019 June	32	22	54
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2019 April	19	29	48
2019 March	9	16	25
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2018 November	17	5	22
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2018 August	12	7	19
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2018 April	3	2	5
2018 March	20	0	20
2018 February	5	1	6
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2017 December	10	3	13
2017 November	6	2	8
2017 October	16	5	21
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2017 August	10	4	14
2017 July	10	4	14
2017 June	13	3	16
2017 May	3	2	5
2017 April	5	7	12
2017 March	12	8	20
2017 February	11	3	14
2017 January	8	2	10
2016 December	10	6	16
2016 November	18	6	24
2016 October	19	8	27
2016 September	16	2	18
2016 August	7	1	8
2016 July	10	0	10
2016 June	13	7	20
2016 May	15	7	22
2016 April	9	16	25
2016 March	17	19	36
2016 February	21	15	36
2016 January	7	12	19
2015 December	7	11	18
2015 November	18	7	25
2015 October	12	16	28
2015 September	21	8	29
2015 August	16	5	21
2015 July	9	3	12
2015 June	4	2	6
2015 May	9	4	13
2015 April	21	9	30
2015 March	17	3	20
2015 February	11	3	14
2015 January	19	3	22
2014 December	33	10	43
2014 November	18	4	22
2014 October	16	2	18
2014 September	12	2	14
2014 August	41	6	47
2014 July	30	7	37
2014 June	17	1	18
2014 May	18	3	21
2014 April	20	4	24
2014 March	23	4	27
2014 February	20	4	24
2014 January	12	5	17
2013 December	23	5	28
2013 November	23	4	27
2013 October	111	12	123
2013 September	46	3	49
2013 August	27	5	32
2013 July	26	2	28

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