Original article
SmartLab 2.0 in cardiovascular prevention of atherogenic dyslipidemia
SmartLab 2.0 en prevención cardiovascular de dislipemia aterogénica
Raquel Galván Toribioa,
, Teresa Arrobas Velillaa, Cristóbal Morales Porillob, Miguel Ángel Ricoc, Mar Martínez Quesadad, Antonio León Justela
Corresponding author
a Laboratorio de Nutrición y RCV, Unidad de Bioquímica Clínica, Hospital Universitario Virgen Macarena, Sevilla, Spain
b Hospital de día de Diabetes, Unidad de Endocrinología y Nutrición, Hospital Universitario Virgen Macarena, Sevilla, Spain
c Unidad de Hipertensión y RCV, Unidad de Medicina Interna, Hospital Universitario Virgen Macarena, Sevilla, Spain
d Unidad de Rehabilitación Cardiaca, Unidad de Cardiología, Hospital Universitario Virgen Macarena, Sevilla, Spain
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array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Laboratorio de Nutrición y RCV, Unidad de Bioquímica Clínica, Hospital Universitario Virgen Macarena, Sevilla, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Hospital de día de Diabetes, Unidad de Endocrinología y Nutrición, Hospital Universitario Virgen Macarena, Sevilla, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Unidad de Hipertensión y RCV, Unidad de Medicina Interna, Hospital Universitario Virgen Macarena, Sevilla, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Unidad de Rehabilitación Cardiaca, Unidad de Cardiología, Hospital Universitario Virgen Macarena, Sevilla, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "SmartLab 2.0 en prevención cardiovascular de dislipemia aterogénica" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 3516 "Ancho" => 2341 "Tamanyo" => 366020 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0050" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Diagram of the process initiated when diabetic patients with probable severe atherogenic dyslipidaemia are detected by analysis. Activation of the algorithm triggers the implementation of an analytical warning.</p> <p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">PC: primary care; ApoB: apolipoprotein B; HDLc: cholesterol bound to high density lipoproteins; LDLc: cholesterol bound to low density lipoproteins; HbA1c: glycated haemoglobin; TG: triglycerides.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Cardiovascular disease (CVD) is still the most common cause of death worldwide, vastly surpassing the number of deaths due to cancer.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Furthermore, it is calculated that no less than 60 million years of potential life are lost due to CVD in Europe every year, showing the resulting high incidence of premature deaths.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Atherosclerosis is considered to be a direct cause of CVD, and alterations in the normal concentrations of lipids and lipoproteins favour the appearance of atherosclerosis, so that dyslipidaemia is a major cardiovascular risk factor.<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">One type of dyslipidaemia known as atherogenic dyslipidaemia is associated with especially high cardiovascular risk due to the individual and synergic action of its three main components: an increase in total triglycerides (TG), a fall in cholesterol bound to high density lipoproteins (HDLc) and the presence of small dense LDL particles.<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> It is also usually accompanied by a rise in apolipoprotein B (ApoB), which is present in all non-HDL and therefore reflects the total number of lipoproteins associated with cardiovascular disease (LDL, residual particles and Lp[a]).<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Atherogenic dyslipidaemia is normally associated with different conditions and diseases, such as being overweight, obesity, diabetes mellitus and metabolic syndrome.<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> Special mention should be made of diabetes, as it is estimated that up to 41% of diabetic patients in our country have atherogenic dyslipidaemia.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> Therefore, given that diabetes is considered to be a cardiovascular risk factor in itself, the combination of both of these entities multiplies the predisposition of these patients to suffer cardiovascular events. In fact, CVD is the main cause of morbimortality in type 2 diabetes mellitus.<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> This is why early diagnosis and the use of corrective therapeutic measures is fundamental in such cases, to guarantee the health of these patients.</p><p id="par0025" class="elsevierStylePara elsevierViewall">SmartLab 2.0 is an innovative concept for multidisciplinary cooperation between the clinical laboratory and the day diabetes unit. It aims to identify patients at high or very high cardiovascular risk who should receive priority attention, including those who have atherogenic dyslipidaemia. The ultimate aim is to create a cardiovascular prevention strategy in primary care. It is fundamentally based on the implementation of analytical warnings for doctors who have requested an analysis, by applying automatic computerized algorithms within the laboratory’s information system. These algorithms are reviewed and validated by the laboratory analyst, and the system also resolves electronic consultations, which are new valid tools for the consolidation of cardiovascular health strategies in n collaboration with the diabetes day unit.</p><p id="par0030" class="elsevierStylePara elsevierViewall">The objective of this study was to implement an automated biochemical algorithm within the laboratory information system (LIS) for the identification within routine analyses of diabetic patients who fulfil the criteria for atherogenic dyslipidaemia, and the priority referral of the corresponding cases to the diabetes day unit, together with the creation of a specific electronic facility for this with primary care.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Material and methods</span><p id="par0035" class="elsevierStylePara elsevierViewall">An automated biochemical algorithm was implemented in the LIS, defined as glycated haemoglobin (HbA1c)<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>TG<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>150<span class="elsevierStyleHsp" style=""></span>mg/dl<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>HDLc<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>LDLc/ApoB<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>1.3 (a ratio below 1.3 is compatible with the presence of potentially atherogenic small dense LDL particles).<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> The following legend is automatically inserted into any routine analysis that fulfils the four criteria, depending on the HbA1c value and highlighting the therapeutic targets according to patient risk.</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">If HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7</span><p id="par0040" class="elsevierStylePara elsevierViewall">Warning: “The patient has a lipid triad that indicates atherogenic dyslipidaemia: a high concentration of TG, low HDLc and the presence of small dense potentially atherogenic particles”.</p><p id="par0045" class="elsevierStylePara elsevierViewall">According to 2019 European Society of Cardiology guidelines, the therapeutic targets in diabetic patients are:<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">•</span><p id="par0050" class="elsevierStylePara elsevierViewall">Very high-risk patients: SCORE<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>10%. Reduction of LDLc<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>50% respecting the basal value, and LDLc<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>55<span class="elsevierStyleHsp" style=""></span>mg/dl.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">•</span><p id="par0055" class="elsevierStylePara elsevierViewall">High risk patients: SCORE<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>5% y <<span class="elsevierStyleHsp" style=""></span>10%. Reduction of LDLc<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>50% respecting the basal value, and LDLc<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>70<span class="elsevierStyleHsp" style=""></span>mg/dl.</p></li></ul></p><p id="par0060" class="elsevierStylePara elsevierViewall">In this way all patients with possible atherogenic dyslipidaemia are characterized and marked in the LIS with their corresponding diagnostic remarks in the report on analysis, for the attention of the doctor who requested the analysis.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">If HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>9.3</span><p id="par0065" class="elsevierStylePara elsevierViewall">Given that HbA1c above certain levels has been found to multiply cardiovascular risk,<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10,11</span></a> agreement was reached with the diabetes day unit that, in the integrated care process for diabetes mellitus of the Board of Health of the Regional Government of Andalucía, a level above 9.3 was set for priority referral to the said unit.</p><p id="par0070" class="elsevierStylePara elsevierViewall">In the validation procedure, the laboratory analyst reviews the analyses that fulfil the criteria for atherogenic dyslipidaemia and which have a result for HbA1c higher than 9.3. If these patients have not achieved the LDLc targets and come from primary care, as well as the warning about patients con HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7, they are recommended for priority referral to the diabetes day hospital or the possibility of e-consultation for atherogenic dyslipidaemia in the lipid laboratory. Both routes are committed to replying or making an appointment within 48<span class="elsevierStyleHsp" style=""></span>h. <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a> shows the flow of working.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Data analysis</span><p id="par0075" class="elsevierStylePara elsevierViewall">A descriptive retrospective analysis was performed of the analytical data of the patients with HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7 to evaluate the performance of the said algorithm, which was activated from January to December 2021. The following analytical parameters were analysed to describe the biochemical characteristics of the population in question:<ul class="elsevierStyleList" id="lis0010"><li class="elsevierStyleListItem" id="lsti0015"><span class="elsevierStyleLabel">•</span><p id="par0080" class="elsevierStylePara elsevierViewall">Lipid profile: triglycerides, total cholesterol, LDL cholesterol, HDL cholesterol, apolipoprotein B and the LDLc/ApoB coefficient.</p></li><li class="elsevierStyleListItem" id="lsti0020"><span class="elsevierStyleLabel">•</span><p id="par0085" class="elsevierStylePara elsevierViewall">Evaluation of diabetes: glycated haemoglobin.</p></li><li class="elsevierStyleListItem" id="lsti0025"><span class="elsevierStyleLabel">•</span><p id="par0090" class="elsevierStylePara elsevierViewall">Evaluation of kidney function: glomerular filtration (estimated based on the CKD-EPI equation) and the albumin/creatinine coefficient.</p></li></ul></p><p id="par0095" class="elsevierStylePara elsevierViewall">The number of analytical warnings issued is described, together with whether the patients met their lipid targets or not. The statistical software used for this study was R Commander (version 2.8–0). The Shapiro–Wilk test was used to study the normalcy of the variables.</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Results</span><p id="par0100" class="elsevierStylePara elsevierViewall">During 2021 the diagnostic algorithm for atherogenic dyslipidaemia was activated in 899 patients with HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7. 730 of these patients came from primary care, 132 from specialized departments and 37 from hospitalization. The population identified was composed of 619 men and 280 women, with an average age of 61 years old.</p><p id="par0105" class="elsevierStylePara elsevierViewall">The main biochemical characteristics, and the ones that were found to be the most useful in characterizing the general population obtained, are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. Due to the non-normalcy of the variables, data are shown in terms of the median and interquartile range.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">The following results were obtained in this population regarding the achievement of lipid targets (defined specifically for diabetic patients who were at least at high risk due to the presence of dyslipidaemia)<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> and the recommendations for normal values of total cholesterol:<ul class="elsevierStyleList" id="lis0015"><li class="elsevierStyleListItem" id="lsti0030"><span class="elsevierStyleLabel">•</span><p id="par0115" class="elsevierStylePara elsevierViewall">LDL cholesterol <70<span class="elsevierStyleHsp" style=""></span>mg/dl: 196 patients achieved the target (21.8% of the population).</p></li><li class="elsevierStyleListItem" id="lsti0035"><span class="elsevierStyleLabel">•</span><p id="par0120" class="elsevierStylePara elsevierViewall">Apolipoprotein B <80<span class="elsevierStyleHsp" style=""></span>mg/dl: 52 patients achieved the target (5.8% of the population).</p></li><li class="elsevierStyleListItem" id="lsti0040"><span class="elsevierStyleLabel">•</span><p id="par0125" class="elsevierStylePara elsevierViewall">Total cholesterol <200<span class="elsevierStyleHsp" style=""></span>mg/dl: 463 patients achieved the target (51.5% of the population).</p></li></ul></p><p id="par0130" class="elsevierStylePara elsevierViewall">Different degrees of severity were defined for triglyceride analysis. A TG concentration higher than 500<span class="elsevierStyleHsp" style=""></span>mg/dl is considered to be severe hypertriglyceridemia. A total of 237 patients had a result of TG >500<span class="elsevierStyleHsp" style=""></span>mg/dl (26.4% of the population).</p><p id="par0135" class="elsevierStylePara elsevierViewall">Respecting kidney function, a glomerular filtration rate below 60<span class="elsevierStyleHsp" style=""></span>ml/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span> (indicating a poor filtration rate and kidney damage) was detected in 184 patients (20.5% of the population).</p><p id="par0140" class="elsevierStylePara elsevierViewall">Of the 899 patients with HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7 and diagnosed atherogenic dyslipidaemia, 307 had a result of HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>9.3 (34.1% of the population). Of these, 253 came from primary care, 36 came from specialized departments and 18 from hospitalization. After review by a doctor of these figures it was found that only 65 patients were within the targets set for LDLc (LDLc<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>70<span class="elsevierStyleHsp" style=""></span>mg/dl). Of the remaining 242 patients who did not meet the targets, 203 came from primary care and were referred to the diabetes day hospital for cardiovascular prevention due to their high risk.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Discussion</span><p id="par0145" class="elsevierStylePara elsevierViewall">Dyslipidaemia is common in patients with diabetes, and it adds to the increased risk of cardiovascular events and death. Genetic factors, lifestyle, hypertension, kidney disease, obesity, inflammation, a prothrombotic state, the duration of diabetic disease and control of glycaemia are also important cardiovascular risk factors within this context.<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a></p><p id="par0150" class="elsevierStylePara elsevierViewall">Clinical laboratories should play a fundamental role in the detection of dyslipidaemia, given that the diagnosis is always based on analytic proof of lipid alteration. Thus, by combining serum biomarkers and the implementation of biochemical algorithms in information systems it is possible to identify patients at an early stage and reclassify them correctly. To this end, in our nutrition and cardiovascular risk laboratory we implemented an automated algorithm for the detection of the most common form of dyslipidaemia in diabetic patients: atherogenic dyslipidaemia.</p><p id="par0155" class="elsevierStylePara elsevierViewall">An initial evaluation of the project found that we had diagnosed almost 900 patients with atherogenic dyslipidaemia, adding an explanation commentary in the analytical report and enhancing the post-analytical phase. We also activated more than 300 diagnostic analytical warnings of severe atherogenic dyslipidaemia, and more than 200 primary care patients with poor lipid and diabetic control were prioritized for referral to the diabetes day hospital for cardiovascular prevention in 2021. Taking into consideration the substantial pressure during the said year due to the COVID-19 pandemic, and the fact that fewer analyses were received by our laboratory, this figure cannot be ignored. In fact, once these cases have been detected it is primordial to refer them for specialized care, when necessary, given that these patients are at very high cardiovascular risk. To achieve this, it is fundamental for the laboratory to cooperate with clinical units, and this is achieved with this model SmartLab 2.0, interconnecting the laboratory with the clinical and with the patient.</p><p id="par0160" class="elsevierStylePara elsevierViewall">When the average values of the population studied (899 patients) are examined, our results can be said to be comparable with those reported by the Atherogenic Dyslipidaemia Work Group of the Spanish Society of Atherosclerosis in its PREDISAT study. They concluded that diabetic patients with atherogenic dyslipidaemia had an average triglyceridaemia level close to 500<span class="elsevierStyleHsp" style=""></span>mg/dl, and HDLc at 33<span class="elsevierStyleHsp" style=""></span>mg/dl. Our population had an average triglyceridaemia of 437<span class="elsevierStyleHsp" style=""></span>mg/dl and HDLc at 32<span class="elsevierStyleHsp" style=""></span>mg/dl.</p><p id="par0165" class="elsevierStylePara elsevierViewall">The 2021 European Society of Cardiology Guide on the prevention of cardiovascular disease in clinical practice states that cardiovascular risk factors are generally poorly treated even in patients who are considered to be at high risk, including patients with diabetes mellitus and atherogenic dyslipidaemia.<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">14,15</span></a> This statement agrees with the results obtained in our study, as when the lipid parameters of the selected patients were described, it was found that the majority had not achieved their targets.</p><p id="par0170" class="elsevierStylePara elsevierViewall">78.2% of the sample population did not meet their target for LDLc, and 94.2% did not achieve the expected ApoB target figures for diabetic patients. Moreover, many patients had very high total cholesterol and severe hypertriglyceridaemia.</p><p id="par0175" class="elsevierStylePara elsevierViewall">These results underline the need to reinforce all levels of cardiovascular prevention. Implementing biochemical algorithms and enhancing analytic reports with diagnostic remarks and explanations is a simple way of contributing to cardiovascular prevention, and this was the ultimate aim of this project. It is of primordial importance to detect these patients early to prevent progression to complicated or fatal cardiovascular disease, and it is fundamental for different clinical units to work together to thereby guarantee patient safety.</p><p id="par0180" class="elsevierStylePara elsevierViewall">As limitations of this study, we can assume that it is not possible to calculate the actual prevalence of atherogenic dyslipidaemia in our area during 2021 based on these data, given that if the algorithm is to activate, analysis must find a complex lipid profile (which includes ApoB), and this is not requested in the majority of basic analyses.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Conclusions</span><p id="par0185" class="elsevierStylePara elsevierViewall">The implementation of a SmartLab 2.0 which promotes multidisciplinary collaboration between the clinical laboratory and the diabetes day unit can be an effective means of identifying patients with atherogenic dyslipidaemia.</p><p id="par0190" class="elsevierStylePara elsevierViewall">The automated algorithms in the LIS make it possible to identify a high number of patients with poor control of glycaemia and atherogenic dyslipidaemia who do not fulfil desirable targets according to their degree of risk, so that those with the most severe cardiovascular risk can receive priority referral to the diabetes day unit.</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Financing</span><p id="par0195" class="elsevierStylePara elsevierViewall">This paper was partially financed by the <span class="elsevierStyleGrantSponsor" id="gs0005">SEA grant</span> awarded in 2021 with the title <span class="elsevierStyleItalic">“Aplicación de la telemedicina de laboratorio en atención primaria para la prevención de la enfermedad cardiovascular”</span>.</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conflict of interests</span><p id="par0200" class="elsevierStylePara elsevierViewall">The authors have no conflict of interests to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1915110" "titulo" => "Abstract" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Objective" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Material and methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1653407" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1915109" "titulo" => "Resumen" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Objetivo" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Material y métodos" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0050" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1653408" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "If HbA1c > 7" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "If HbA1c > 9.3" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Data analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0030" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0035" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0040" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "sec0045" "titulo" => "Financing" ] 10 => array:2 [ "identificador" => "sec0050" "titulo" => "Conflict of interests" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2022-06-23" "fechaAceptado" => "2022-09-22" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1653407" "palabras" => array:4 [ 0 => "Atherogenic dyslipidemia" 1 => "Diabetes" 2 => "Early warning" 3 => "Cardiovascular prevention" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1653408" "palabras" => array:4 [ 0 => "Dislipemia aterogénica" 1 => "Diabetes" 2 => "Alerta temprana" 3 => "Prevención cardiovascular" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">SmartLab 2.0 is an innovative concept of multidisciplinary collaboration between the clinical laboratory and the diabetes day unit that was born with the aim of identifying patients at high cardiovascular risk who require priority attention, such as patients with atherogenic dyslipidemia, in order to create a cardiovascular prevention strategy.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Objective</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Implementation in the Laboratory Information System (LIS) of an automated biochemical algorithm for the identification of patients with atherogenic dyslipidemia in routine analyses and priority referral to the diabetes day unit.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Material and methods</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">The algorithm designed in the SIL was: HBA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>9.3<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>TG<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>150<span class="elsevierStyleHsp" style=""></span>mg/dl<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>HDLc<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>mg/dl<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>LDL/ApoB<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>1.3. A comment was inserted alerting the requesting physician of the diagnosis of atherogenic dyslipidemia and priority referral was made from the laboratory to the diabetes day unit in the necessary cases.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">In the 1-year period, a total of 899 patients with HBA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7 and atherogenic dyslipidemia criteria were identified. Of these, 203 patients from primary care with HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>9.3 were referred to the diabetes day hospital.</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusions</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Reinforcement of cardiovascular prevention is necessary at all levels. The clinical laboratory should play a fundamental role in the diagnosis of dyslipidemias. Early detection of patients at high cardiovascular risk is essential and collaboration between the different clinical units is fundamental to guarantee patient safety.</p></span>" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Objective" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Material and methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Introducción</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">El SmartLab 2.0 es un concepto innovador de colaboración multidisciplinar entre el laboratorio clínico y la unidad de día de diabetes que nace con el objetivo de identificar a pacientes de alto riesgo cardiovascular que requieran una atención prioritaria, como son los pacientes que presentan dislipemia aterogénica, con el fin de crear una estrategia de prevención cardiovascular.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Objetivo</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Implementación en el sistema informático de laboratorio (SIL) de un algoritmo bioquímico automatizado para la identificación en analíticas de rutina de pacientes con dislipemia aterogénica y derivación prioritaria a la unidad de día de diabetes.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Material y métodos</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Se diseñó en el SIL el algoritmo: HBA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>9,3<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>TG<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>150<span class="elsevierStyleHsp" style=""></span>mg/dl<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>cHDL<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>40 mg/dl<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>LDL/ApoB es<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>1,3. Se inserta un comentario alertando al médico peticionario del diagnóstico de dislipemia aterogénica y se procede a la derivación prioritaria desde el laboratorio a la unidad de día de diabetes en los casos necesarios.</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Resultados</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">En el periodo de un año se han identificado a un total de 899 pacientes con HBA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7 y criterio de dislipemia aterogénica. De ellos, 203 pacientes procedentes de atención primaria con HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>9,3 se derivaron al hospital de día de diabetes.</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Conclusiones</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">El refuerzo de la prevención cardiovascular es necesario a todos los niveles. El laboratorio clínico debe jugar un papel fundamental en el diagnóstico de las dislipemias. La detección temprana de los pacientes con alto riesgo cardiovascular es primordial y la colaboración entre las distintas unidades clínicas es fundamental para garantizar la seguridad del paciente.</p></span>" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Objetivo" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Material y métodos" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0050" "titulo" => "Conclusiones" ] ] ] ] "multimedia" => array:2 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 3516 "Ancho" => 2341 "Tamanyo" => 366020 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0050" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Diagram of the process initiated when diabetic patients with probable severe atherogenic dyslipidaemia are detected by analysis. Activation of the algorithm triggers the implementation of an analytical warning.</p> <p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">PC: primary care; ApoB: apolipoprotein B; HDLc: cholesterol bound to high density lipoproteins; LDLc: cholesterol bound to low density lipoproteins; HbA1c: glycated haemoglobin; TG: triglycerides.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0055" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">ApoB: apolipoprotein B; HDLc: cholesterol bound to high density lipoproteins; LDLc: cholesterol bound to low density lipoproteins; TC: total cholesterol; GF: glomerular filtration rate; HbA1c: glycated haemoglobin; TG: triglycerides.</p>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "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"><th 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" scope="col" style="border-bottom: 2px solid black">Parameter \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th 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" scope="col" style="border-bottom: 2px solid black">Median (interquartile range) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TG (mg/dl) \t\t\t\t\t\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">402 (337–509) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">TC (mg/dl) \t\t\t\t\t\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">197 (167–233) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDLc (mg/dl) \t\t\t\t\t\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">101 (75–126) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDLc (mg/dl) \t\t\t\t\t\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">33 (29–37) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ApoB (mg/dl) \t\t\t\t\t\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">119 (101–140) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL/ApoB \t\t\t\t\t\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">0.85 (0.72–0.96) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HbA1c (%) \t\t\t\t\t\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">8.5 (7.6–10) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">GF (ml/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>) \t\t\t\t\t\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">90 (65–102) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">General biochemical characteristics of the diabetic population identified (HbA1c<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>7) expressed as the median and interquartile range.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:15 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "European Society of Cardiology: cardiovascular disease statistics 2021" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. 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