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FRAX® thresholds to identify people with high or low risk of osteoporotic fracture in Spanish female population
Umbrales de FRAX® para identificar personas con alto o bajo riesgo de fractura osteoporótica en población femenina española
Rafael Azagraa,b,c,
Corresponding author
rafael.azagra@uab.cat

Corresponding author.
, Genís Rocaa,d, Juan Carlos Martín-Sáncheze, Enrique Casadof, Gloria Encabog, Marta Zwarta,h, Amada Aguyéi, Adolf Díez-Péreza,j,k, representing the research group GROIMAP
a Departamento de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
b Medicina de Familia, CAP Badía del Vallés, Institut Català de la Salut (ICS), USR MN-IDIAP Jordi Gol, Barcelona, Spain
c Departamento de Medicina, Universitat Internacional de Catalunya, Sant Cugat del Vallés, Barcelona, Spain
d Medicina de Familia, CAP Sant Llàtzer, Corporació Sanitària de Terrassa, Terrassa, Barcelona, Spain
e Bioestadística, Departamento de Ciencias Básicas, Universitat Internacional de Catalunya, Campus Sant Cugat, Sant Cugat del Vallés, Barcelona, Spain
f Reumatología, Hospital de Sabadell, Corporació Sanitària Parc Taulí, Sabadell, Barcelona, Spain
g Medicina Nuclear, Hospital Universitari Vall d’Hebron, Institut Català de la Salut (ICS), Barcelona, Spain
h Medicina de Familia, CAP Girona-2, Institut Català de la Salut (ICS)-USR Girona, IDIAP Jordi Gol, Girona, Spain
i Medicina de Familia, CAP Granollers Centre, Institut Català de la Salut (ICS), Granollers, Barcelona, Spain
j Departamento de Medicina Interna, URFOA, IMIM, Parc de Salut Mar, Barcelona, Spain
k Red Temática de Investigación Cooperativa en Envejecimiento y Fragilidad (RETICEF), Instituto de Salud Carlos III-FEDER, Madrid, Spain
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Decision-making diagram according to the most cost-effective option in the FRIDEX cohort of Spanish women who did not receive treatment during the 10 years of follow-up DXA&#58; dual energy X-ray absorptiometry&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Osteoporosis is a public health problem of great magnitude that leads to increased risk of fragility fractures in any location&#44; particularly of the vertebrae&#44; proximal femur&#44; shoulder and wrist&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">1</span></a> In general&#44; fragility fractures entail a risk of complications&#44; disabilities and&#44; sometimes&#44; also higher mortality&#46;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">2</span></a> In 1994&#44;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">3</span></a> a committee of experts from the World Health Organization &#40;WHO&#41; published certain criteria based on the measurement of bone mineral density &#40;BMD&#41; by dual-energy X-ray absorptiometry &#40;DXA&#41; to define osteoporosis&#46; Since their publication&#44; clinicians have incorporated these criteria into the daily management of osteoporosis and prevention of fragility fractures&#46;<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">4&#44;5</span></a> Apart from BMD&#44; diverse clinical risk factors have been identified as promoters of fragility fractures&#46;<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">5</span></a> Among them&#44; old age and previous fractures stand out&#44; but there are also other factors whose correlation with fragility fractures has been demonstrated in large studies and&#47;or meta-analyses&#44; which have used different scales&#46;<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">5&#8211;8</span></a> For instance&#44; the WHO have published the <span class="elsevierStyleItalic">Fracture Risk Assessment Tool</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">&#174;</span></span> &#40;FRAX<span class="elsevierStyleSup">&#174;</span>&#41;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">9</span></a> based on research by a team of experts at the University of Sheffield&#46; It is an algorithm that uses an online application to estimate 10-year absolute risk of osteoporotic fractures for male and female populations&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">9</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The tool includes 10 particular clinical risk factors&#44; with the optional incorporation of the femoral neck T-score measured by DXA&#46; This risk measure is expressed in absolute values &#40;percentage&#41; for major or frequent fracture &#40;major osteoporotic fracture&#41;&#44; which includes proximal femur&#44; clinical vertebrae&#44; proximal humerus and distal forearm or wrist fractures&#46; It also individually expresses the absolute risk of proximal femur fracture &#40;hip fracture&#41;&#46; This tool is available in its version 3&#46;8 for 47 countries in 20 languages&#46; On the web&#44; it has been recommended that each country should determine which high-risk levels of fracture will be treated surgically&#44; based on a perspective of cost-effectiveness&#44; the population and its resources &#40;<a href="http://www.shef.ac.uk/FRAX/index.aspx?lang=sp">http&#58;&#47;&#47;www&#46;shef&#46;ac&#46;uk&#47;FRAX&#47;index&#46;aspx&#63;lang&#61;sp</a>&#41;&#46; The FRAX<span class="elsevierStyleSup">&#174;</span> tool has been evaluated in many countries&#44; and in some it has also been calibrated with adjustments&#46;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">10&#8211;12</span></a> The National Osteoporosis Guideline Group &#40;NOGG&#41; published the first cost-effectiveness study of the FRAX<span class="elsevierStyleSup">&#174;</span> tool for the population of the United Kingdom based on clinical risk factors&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">This publication defined the FRAX<span class="elsevierStyleSup">&#174;</span> values that were considered an intermediate risk of major fracture &#40;for which DXA was recommended&#41; and high risk factors &#40;for which pharmacological treatment was recommended&#41;&#44; with certain cost-effective criteria in the primary prevention of fragility fractures&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> More recently&#44; other countries have published FRAX<span class="elsevierStyleSup">&#174;</span> thresholds that adjust to their risk characteristics&#44; particularly hip fracture&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">14&#44;15</span></a> The realities of these countries&#44; both in terms of fragility fracture incidence and health care resource distribution&#44; differentiate them from southern European countries&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">16</span></a> For the Spanish population&#44; various studies have been published that analyse the discriminative and predictive capacity of the FRAX<span class="elsevierStyleSup">&#174;</span> tool in 3 cohorts of Spanish women&#46;<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">17&#8211;19</span></a> These studies agree that the FRAX<span class="elsevierStyleSup">&#174;</span> tool has a moderate discriminative capacity to identify Spanish women at high risk of major fracture&#46; Although the analyses are global&#44; these studies agree that the evaluations of predictive capacity need to be adjusted or calibrated to better predict the individual risk at 10 years&#46;<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">17&#8211;19</span></a> It has been demonstrated that&#44; both in the Spanish and in other populations&#44; FRAX<span class="elsevierStyleSup">&#174;</span> is very well prepared to detect women that will experience densitometry osteoporosis&#46;<a class="elsevierStyleCrossRefs" href="#bib0245"><span class="elsevierStyleSup">20&#44;21</span></a> Thus&#44; the establishment of FRAX<span class="elsevierStyleSup">&#174;</span> values to identify the Spanish population at low or high risk of fracture in the next 10 years is still pending&#46;<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">22&#44;23</span></a> Common practice in Spain&#44; which we will call the traditional model&#8217;&#44; is based on patient selection and DXA testing according to clinical criteria and isolated risk factors&#44; especially in primary prevention&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">24</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">The main objective of this study is to identify FRAX<span class="elsevierStyleSup">&#174;</span> cut-off points &#40;FRAX<span class="elsevierStyleSup">&#174;</span> calibrated model&#41; in order to identify groups of women at low and high risk of fragility fractures in the following 10 years&#44; while providing a cost-effective assessment and comparison of this model with current standard clinical practice&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and methods</span><p id="par0025" class="elsevierStylePara elsevierViewall">The following is a prospective cohort study performed in the Fracture RIsk factors and bone DEnsitometry type central dual X-ray &#40;FRIDEX&#41; with a cohort of Spanish women&#46;</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study population</span><p id="par0030" class="elsevierStylePara elsevierViewall">The characteristics of the FRIDEX cohort have been recently described&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">25</span></a> In short&#44; it is a dynamic cohort of Spanish women aged &#8805;40 and &#8804;90 years old&#44; whose physician had ordered DXA testing and who provided their consent to participate&#44; pursuant to the rules accepted by the governing Clinical Investigation Ethics Committee&#46; This study excluded cases derived from errors in the contact record&#44; failure to answer 3 call attempts&#44; refusal to participate&#44; deceased persons and those with cancer or receiving osteoporotic medications at baseline&#44; except supplements &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; The criteria were satisfied by 1308 women&#46; Of these&#44; 492 women were excluded as they had received osteoporotic treatment for at least 6 months during the 10 years of the study&#44; not including calcium and&#47;or vitamin D supplements&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">Using an initial and final structured questionnaire&#44; the following baseline clinical variables were obtained&#58; age&#44; body mass index &#40;BMI&#41;&#59; dichotomous variables &#40;yes&#47;no&#41;&#58; previous fracture&#44; hip fracture in the parents&#44; active smoking&#44; glucocorticoids&#44; excessive alcohol intake&#44; rheumatoid arthritis and presence of secondary osteoporosis&#44; as per the FRAX<span class="elsevierStyleSup">&#174;</span> criteria&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Determination of bone mass</span><p id="par0040" class="elsevierStylePara elsevierViewall">Bone mass was determined by central DXA in a single densitometer model &#40;GE Lunar Prodigy Advance&#8482;&#41; with software version 11&#46;4 and daily calibrations&#46; According to the recommendations of the International Society for Clinical Densitometry &#40;<a href="http://www.iscd.org/official-positions/">http&#58;&#47;&#47;www&#46;iscd&#46;org&#47;official-positions&#47;</a>&#41;&#44; the analysed regions were the entire L1&#8211;L4 lumbar spine and the total proximal femur and femoral neck values&#46; The results were categorised as osteoporosis&#44; osteopenia or normal&#44; as per the WHO criteria from 1994&#46;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">3</span></a></p><p id="par0045" class="elsevierStylePara elsevierViewall">The analyses included only the incident fractures that were able to be confirmedby patient medical files or hospital records&#46; For the FRAX<span class="elsevierStyleSup">&#174;</span> assessment analyses&#44; only fractures considered major osteoporotic fractures according to the FRAX<span class="elsevierStyleSup">&#174;</span> tool &#40;hip&#44; clinical vertebrae&#44; proximal humerus and distal forearm&#41; were included&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">The risk estimation for major fracture with FRAX<span class="elsevierStyleSup">&#174;</span> of the participants was performed through the official web page for the Spanish population using data from the baseline interview&#46; To calculate FRAX<span class="elsevierStyleSup">&#174;</span> with BMD&#44; the femoral neck T-score value from the baseline DXA was used&#46; The calculations were made separately and in parallel by 2 researchers and subsequently reviewed by another 2&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Diagnostic reliability tests</span><p id="par0055" class="elsevierStylePara elsevierViewall">The discriminative capacity of the FRAX<span class="elsevierStyleSup">&#174;</span> tool for 10-year major fracture risk &#40;with and without BMD&#41; was determined through the area under the curve &#40;AUC&#41; receiver operating characteristic &#40;ROC&#41; analysis&#46; The predictive capacity of the FRAX<span class="elsevierStyleSup">&#174;</span> tool was analysed through the ratio of observed fractures &#40;ObsFx&#41; during the 10-year follow-up of the FRIDEX cohort and the expected fractures &#40;ExpFx&#41; by the FRAX<span class="elsevierStyleSup">&#174;</span> tool with the formula&#58; &#91;ObsFx&#47;sum of the individual probability for fracture assigned by FRAX<span class="elsevierStyleSup">&#174;</span> to women in the cohort&#47;100&#93;&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Detection of the best FRAX<span class="elsevierStyleSup">&#174;</span> threshold values for calibration</span><p id="par0060" class="elsevierStylePara elsevierViewall">The process to determine the best cut-off points was developed in various phases&#46; In the first phase&#44; the accumulated incidence of fragility fractures was analysed in the cohort with 816 women who did not receive pharmacological treatment during the 10-year period&#46; The cases of major osteoporotic fractures were observed&#44; and the descriptive analysis of the different risk factors included in the FRAX<span class="elsevierStyleSup">&#174;</span> tool was done&#44; with the additional factor of falls in the previous year and the differences between women with fractures and those without fractures&#46; Subsequently&#44; the discriminative capacity of FRAX<span class="elsevierStyleSup">&#174;</span> was analysed through the AUC-ROC&#46; To end this phase&#44; the predictive capacity of FRAX<span class="elsevierStyleSup">&#174;</span> was evaluated with the ratio of the number of women with fractures &#40;ObsFx&#41; in the cohort and the number of women who could have fractures &#40;ExpFx&#41;&#44; estimated by FRAX<span class="elsevierStyleSup">&#174;</span>&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">In the second phase&#44; these 816 women were stratified into 3 risk groups &#40;low&#44; moderate and high&#41;&#44; following the criterion used in the Canadian cohort CaMos&#44;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">26</span></a> which considers absolute 10-year fracture risk lower than 10&#37; as low risk&#44; values over 20&#37; as high risk and values between 10 and 20&#37; as moderate risk&#46; In the third phase&#44; the values equivalent to the 2 cut-points among the 3 groups were observed&#46; That is to say&#44; the threshold below which there were women with less than 10&#37; of 10-year fragility fractures&#44; and the threshold that determined the group of women with a fracture in more than 20&#37; of cases&#46; The intermediate risk group was defined between both groups&#46; Finally&#44; with the FRAX<span class="elsevierStyleSup">&#174;</span> detected cut-off points&#44; the fracture frequencies for each risk group were calculated&#44; with a 95&#37; confidence interval &#40;CI 95&#37;&#41;&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Cost-effectiveness calculation</span><p id="par0070" class="elsevierStylePara elsevierViewall">For the cost-effectiveness and diagnostic precision analyses&#44; the European Guidelines for the Treatment of Osteoporosis were followed&#46;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">9</span></a> These guidelines recommend prescribing a healthy lifestyle when there is low risk&#44; ordering DXA to reevaluate low or high risk with FRAX<span class="elsevierStyleSup">&#174;</span>&#44; BMD when there is moderate risk and&#44; finally&#44; pharmacological treatment in cases of high risk&#46; However&#44; in this study&#44; the alternative of ordering a DXA in high fracture risk cases and reevaluating the risk was also included&#44; as the results from the DXA of all the cases were available&#46; Thus&#44; in the case of low fracture risk&#44; the cost of the actual fractures experienced in the group during follow-up was input&#46; In the case of moderate risk groups&#44; DXA was ordered&#46; Cases with osteoporosis in the DXA and&#47;or that exceeded the FRAX<span class="elsevierStyleSup">&#174;</span> threshold with high-risk BMD were considered high-risk cases&#46; For this group&#44; we input DXA cost&#44; cost of the pharmacological treatments and cost of the actual fractures experienced&#44; while subtracting those that would be potentially prevented with pharmacological treatments &#40;a mean 50&#37; reduction of the cases with fractures in the following 10 years was assumed&#41;&#46; In the case of high fracture risk groups&#44; 2 options were analysed&#58; the administration of treatment to all the cases without a DXA and the use of DXA and reevaluation&#44; as in the moderate risk cases&#46; In the first option&#44; the cost of the pharmacological treatments and the cost of the actual fractures experienced were input&#44; while subtracting those that would be potentially prevented by pharmacological treatments &#40;50&#37;&#41;&#59; in the second option&#44; the cost of the DXA was added&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">The amounts for the direct and indirect costs were taken from costs published in Spain<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">27</span></a> &#40;per unit&#41;&#58; DXA 59&#8364;&#44; hip fracture &#8364;15&#44;536&#44; vertebral fracture &#8364;8876&#44; forearm fracture &#8364;2064 and humerus fracture &#8364;3034&#46; For humerus fractures&#44; data were extrapolated from another official publication &#40;DOG 6079&#44; available at&#58; <a href="http://www.municat.gencat.cat/upload/normativa/acord_gov_14_2012.pdf">http&#58;&#47;&#47;www&#46;municat&#46;gencat&#46;cat&#47;upload&#47;normativa&#47;acord&#95;gov&#95;14&#95;2012&#46;pdf</a>&#41;&#46; To calculate the mean cost of one year of treatment&#44; data were taken from the same ISCIII-MS<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">27</span></a> publication on the most commonly used drugs for the treatment of osteoporosis in Spain in 2010&#44; without considering calcium and&#47;or vitamin D supplements&#46; Based on the medication consumption profile for osteoporosis in Spain&#44; the mean cost is &#8364;427&#47;year in 2010&#46; For both models&#44; the cost of 10 years of treatment was input &#40;&#8364;4272&#41;&#46; The cost-effective and diagnostic precision analyses for standard practice in our area were also carried out &#40;traditional model&#41;&#46; The traditional model is based on the request of a DXA for suspected low BMD or risk factors &#40;in this cohort&#44; DXA was performed for all cases&#41; and the indication for pharmacological treatment for cases with a T-score &#8804;<span class="elsevierStyleHsp" style=""></span>&#8722;2&#46;5 standard deviation&#44;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">20</span></a> following the WHO criteria&#46;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">3</span></a> In the costs calculation&#44; for these cases we input the cost of the DXA&#44; the cost of pharmacological treatments that would be indicated in case of osteoporosis shown by DXA and the cost of the actual fractures occurred&#44; minus the ones that would be potentially prevented by the treatment &#40;50&#37;&#41;&#46; For the diagnostic precision analysis&#44; we also calculated the sensitivity&#44; specificity&#44; positive predictive value &#40;PPV&#41; and negative predictive value &#40;NPV&#41; of the 2 models&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0080" class="elsevierStylePara elsevierViewall">The population characteristics population are described with univariate descriptive statistics&#46; The statistical comparison of the variables analysed among cases with or without fractures was done with the Chi-square test for the qualitative variables and the Student <span class="elsevierStyleItalic">t</span> test for the quantitative variables&#46; In cases of significant differences &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#44; the 95&#37; CI was calculated&#46; All the statistical tests were performed with a 95&#37; CI and with the use of the SPSS<span class="elsevierStyleSup">&#174;</span> statistical package&#44; version 17 &#40;Statistical Package for the Social Sciences 2008&#44; SPSS Inc&#46;&#44; Chicago&#44; IL&#44; USA&#41;&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">This study followed the STROBE initiative guidelines for epidemiological studies &#40;<a href="http://www.strobe-statement.org/index.php?id=strobe-publications">http&#58;&#47;&#47;www&#46;strobe-statement&#46;org&#47;index&#46;php&#63;id&#61;strobe-publications</a>&#41;&#46;</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><p id="par0090" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the profile of the cohort of 816 women&#44; with a mean age of 56&#46;8<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>8&#46;2 years old&#44; and 15&#46;6&#37; had osteoporosis at any of the 3 points defined in the DXA&#46; During the 10-year follow-up&#44; 76 women &#40;9&#46;3&#37;&#41; experienced an osteoporotic fracture and 49 &#40;6&#37;&#41; a major fracture &#40;15 hip&#44; 4 vertebrae&#44; 13 proximal humerus and 17 forearm fractures&#41;&#46; In 8 cases &#40;16&#37;&#41;&#44; the women experienced more than one fracture&#44; but these were not contemplated by the different analyses&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">Among the risk factors &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#44; age&#44; previous fractures&#44; falls in the previous year and a diagnosis of osteoporosis in the baseline DXA were significant&#46; The discriminative capacity of FRAX<span class="elsevierStyleSup">&#174;</span> analysed by the ROC curve for the association between risk measurement and fractures showed that the AUC was 0&#46;736 &#40;95&#37; CI 0&#46;657&#8211;0&#46;815&#41; for FRAX<span class="elsevierStyleSup">&#174;</span> without BMD and 0&#46;733 &#40;95&#37; CI 0&#46;652&#8211;0&#46;814&#41; for FRAX<span class="elsevierStyleSup">&#174;</span> with BMD of the femoral neck&#46; The AUC of the DXA with osteoporosis values was 0&#46;697 &#40;95&#37; CI 0&#46;614&#8211;0&#46;780&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">The predictive capacity analysed through the ratio of ObsFx and ExpFx by the FRAX<span class="elsevierStyleSup">&#174;</span> tool for major fracture &#40;ObsFx&#47;ExpFx&#41; was 1&#46;72 &#40;95&#37; CI 1&#46;27&#8211;2&#46;27&#41; for FRAX<span class="elsevierStyleSup">&#174;</span> without BMD and 1&#46;61 &#40;95&#37; CI 1&#46;19&#8211;2&#46;12&#41; for FRAX<span class="elsevierStyleSup">&#174;</span> with the BMD of the femoral neck&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">The values that defined the risk groups were the following&#58; &#60;5&#37; for low risk&#44; &#8805;7&#46;5&#37; for high risk and the values between them defined moderate risk &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">The predictive precision results of the cohort with FRAX<span class="elsevierStyleSup">&#174;</span> cut-off points to identify the risk groups showed&#58; sensitivity 40&#46;8&#37;&#44; specificity 92&#46;3&#37;&#44; PPV 25&#46;3&#37; and NPV 96&#37;&#46; The values of the traditional model were&#58; 40&#46;8&#44; 86&#44; 15&#46;7 and 95&#46;8&#37;&#44; respectively&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a> shows the cost-effective analysis of the proposed FRAX<span class="elsevierStyleSup">&#174;</span> calibration for identifying risk thresholds compared to the traditional method&#46; With FRAX<span class="elsevierStyleSup">&#174;</span> cut-off points&#44; 143 DXA would be required and 82 pharmacological treatments would be indicated for 20 women with fractures&#46; In turn&#44; the treatment of 29 women would be discontinued&#46; With the traditional model&#44; 816 DXA would be required and 127 pharmacological treatments would be indicated for 20 women with fractures&#46; In turn&#44; the treatment of 29 women would be discontinued&#46; The economic cost of using FRAX<span class="elsevierStyleSup">&#174;</span> with the cut-off points would be &#8364;601&#44;852&#44; including DXA&#44; pharmacological treatments and the cost of unprevented fractures&#46; When the traditional model was applied&#44; the cost would be &#8364;843&#44;081&#46; Using the cut-off points&#44; the moderate and risk cases &#40;143&#47;816&#59; 17&#46;5&#37;&#41; of the cohort &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41; were selected for DXA&#46; After having re-evaluated the moderate- and high-risk cases with DXA&#44; 82&#47;816 &#40;10&#37;&#41; of the cohort population were selected for treatment&#44; representing 82&#47;143 &#40;57&#46;3&#37;&#41; of the women who were required to have the DXA performed due to FRAX<span class="elsevierStyleSup">&#174;</span> detected threshold values&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Discussion</span><p id="par0120" class="elsevierStylePara elsevierViewall">In this study&#44; we have seen that not all the risk factors included in FRAX<span class="elsevierStyleSup">&#174;</span> have been significant&#46; Age&#44; previous fracture and presence of osteoporosis at baseline DXA were seen to be significant&#46; Excessive alcohol consumption&#44; glucocorticoids&#44; rheumatoid arthritis&#44; low BMI and hip fracture in the parents showed no significant differences&#46; The first 3 are considered weak risk factors in FRAX<span class="elsevierStyleSup">&#174;</span>&#44; and low BMI is considered a strong risk factor<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a>&#59; its non-significance could be justified by its scarce representation in the cohort&#46; History of fractures in any of the parents was not significant&#44; in spite of the fact that it is well represented in the cohort and that it constitutes a strong risk factor in FRAX<span class="elsevierStyleSup">&#174;</span>&#46; Having suffered more than one fall in the previous year is also shown to be significant&#46; Falls&#44; however&#44; are not included in the FRAX<span class="elsevierStyleSup">&#174;</span>&#44; tool but they are included in other risk scales&#46;<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">7&#44;8</span></a></p><p id="par0125" class="elsevierStylePara elsevierViewall">FRAX<span class="elsevierStyleSup">&#174;</span> demonstrated better discriminative capacity than the traditional DXA-based model&#44; although both models exhibit moderate capacity&#46; This improvement has been previously observed in the Spanish population<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">18&#44;19</span></a> and in other populations&#46;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">10&#44;28</span></a> The low predictive capacity of FRAX<span class="elsevierStyleSup">&#174;</span> measured globally by the ObsFx&#47;ExpFx ratio is consistent with previous studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">17&#8211;19</span></a> Meanwhile&#44; in other cohorts&#44; such as the Canadian&#44; FRAX<span class="elsevierStyleSup">&#174;</span> risk prediction approaches the rate of observed fractures &#40;ratio of 1&#46;12 and 1&#46;09 for major fracture without and with DXA&#44; respectively&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">10</span></a> This could be due to representation problems in the Spanish cohorts introduced in the FRAX<span class="elsevierStyleSup">&#174;</span> tool&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">19</span></a></p><p id="par0130" class="elsevierStylePara elsevierViewall">To determine the threshold values&#44; FRAX<span class="elsevierStyleSup">&#174;</span> baseline values were adjusted with the 10-year fracture results&#44; stratified as proposed by the CAROC System&#46;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">10&#44;26</span></a> Thus&#44; the equivalent results are between the real fracture results obtained in the FRIDEX cohort and the FRAX<span class="elsevierStyleSup">&#174;</span> baseline values in these women&#46; With these threshold values&#44; 82&#46;5&#37; of the women were at low risk&#44; 8&#46;9&#37; at moderate risk and 8&#46;6&#37; at high risk&#46; This means that&#44; with these thresholds&#44; 17&#46;5&#37; of the women in the cohort were identified at moderate to high risk&#44; although it must be considered that these women were referred for BMD determination because they presented some signs of risk&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">The economic assessment was based on European guidelines<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">9&#44;13</span></a> that recommend following a healthy lifestyle in low-risk cases&#44; DXA to reevaluate risk with FRAX<span class="elsevierStyleSup">&#174;</span> in moderate-risk cases&#44; and treatment in high-risk cases&#46;<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">9&#44;13</span></a> In this study&#44; it has been observed that the performance of DXA also in the cases at high risk of fracture is the most cost-effective option&#46; Thus&#44; 15 of the 70 cases identified as high risk with the FRAX<span class="elsevierStyleSup">&#174;</span> tool did not have osteoporosis in the DXA and were left outside the range of high risk of fracture&#46; The first cost-effective proposal calibrated by FRAX<span class="elsevierStyleSup">&#174;</span> was carried out by the NOGG with a population from the United Kingdom<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> for primary prevention&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> Other countries have followed the same example and made making proposals in cost-effective terms&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">14&#44;15</span></a></p><p id="par0140" class="elsevierStylePara elsevierViewall">The diagnostic precision analysis showed a sensitivity of 40&#46;8&#37; in both methods&#44; but the use of FRAX<span class="elsevierStyleSup">&#174;</span> calibration thresholds improved specificity by more than 6 points and PPV by almost 10 points compared to the traditional diagnosis model based on the T-score &#8804;&#8722;2&#46;5 of the DXA&#46; The low sensitivity of the DXA<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> was already known&#44; and FRAX<span class="elsevierStyleSup">&#174;</span> calibrated thresholds do not improve sensitivity&#59; however&#44; the remaining predictive parameters do&#46; It should be noted that neither of the two systems is recommended for population screening&#44; but they should instead be used for the opportunistic identification of cases with potential risk factors&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">In the cost-benefit analysis&#44; direct and indirect costs of fractures have been included&#44; as well as the costs corresponding to the DXA and the pharmacological treatments that both models would assign according to the fractures and real treatment profile costs in Spain<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">27</span></a> &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46; In the treatment cases&#44; a 50&#37; fracture reduction risk was assumed&#44; as medical literature shows different percentages of relative risk reduction and also variable percentages for the different types of fractures&#44; ranging from 19 to 44&#37; for alendronate&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> In summary&#44; the use of FRAX<span class="elsevierStyleSup">&#174;</span> calibrated thresholds would allow us to avoid more than 82&#37; of DXA and more than 35&#37; of treatments to treat the same number of women with fractures&#44; but at an almost 30&#37; cheaper global cost when compared to standard practice or the traditional model based on DXA&#46; Although in the traditional model all DXA have been counted and this model may seem disadvantaged in the comparison&#44; the real cost of DXA only accounts for 3&#46;2&#37; of the difference between the models&#46; If the DXAs were not included&#44; the difference would change from 28&#46;7 to 25&#46;5&#37; in favour of the use of FRAX<span class="elsevierStyleSup">&#174;</span> calibrated thresholds&#46; The treatments were estimated for 10 years&#44; and if the estimation were for 5 years&#44; the difference would be reduced by 3&#37;&#46; It has been proven that the most cost-effective option is also DXA in the cases of high fracture risk&#44; basically because there are cases with high-risk FRAX<span class="elsevierStyleSup">&#174;</span> values&#44; but with BMD without osteoporosis&#46; Although numerous societies recommend the administration of pharmacological treatment in cases of fractures in postmenopausal women without the need for DXA&#44;<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">13&#8211;15</span></a> some experts specify that this option should be specifically used in cases of hip or vertebrae fracture&#46;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">10&#44;26</span></a></p><p id="par0150" class="elsevierStylePara elsevierViewall">Among the limitations of the study&#44; it is worth mentioning that the FRIDEX cohort includes women who were referred by their physician for DXA&#44; which could affect the results as it is a potentially higher risk population&#46; However&#44; this analysis excluded women who had initiated anti-osteoporotic treatment during follow-up&#44; so mean age and fracture cases of the cohort were reduced&#46; However&#44; this particularity would not affect the comparative analyses of diagnostic precision and cost-effectiveness between the models&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">Another potential limitation may be the non-inclusion in the analysis of the women who died during follow-up&#44; and for whom the study could not be completed&#46; The mortality rate of the 10-year study was 5&#46;8&#37;&#46; There were few cases of previous fractures but&#44; given the low percentage and the difficulty to confirm the fractures with clinical records&#44; they were excluded from the study&#46; This aspect might affect the predictive capacity analysis&#44; but not the comparative cost-effective study&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">Although it is the most commonly used system&#44; retrospective case registration of incident fractures is considered less reliable than prospective studies due to the memory effect and possible patient confusion&#46;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">13</span></a> To minimize this effect&#44; all the fracture cases were verified in the clinical records&#46; Thus&#44; 16&#37; of the women initially detected with fractures were excluded from the study&#44; mostly due to lack of records&#46; Only 2 cases of humerus fracture were excluded due to a difference in interpretation between the questionnaire and the records&#44; along with one hip fracture due to a traffic accident&#46; Without this exclusion&#44; the ObsFx&#47;ExpFx ratio would be still higher&#46; Unlike most of the epidemiological studies on osteoporotic fractures that centre on hip fractures<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">29</span></a> and perform extrapolations for the remainder&#44;<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">11&#8211;13</span></a> in this study all the fractures localizations have been identified&#44; even though for the FRAX<span class="elsevierStyleSup">&#174;</span> prediction analysis the major fractures determined by the FRAX<span class="elsevierStyleSup">&#174;</span> tool have been analysed&#46; This type of analyses assume underestimations of non-clinical vertebral fractures&#44; and it is known that up to two-thirds of these fractures are unknown by the patient and the physician&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">14</span></a> Despite these potential limitations&#44; the data on the discriminative and predictive capacity of FRAX<span class="elsevierStyleSup">&#174;</span> in this study are consistent with previous studies in this and other Spanish cohorts&#46;<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">17&#8211;19</span></a> However&#44; clinical judgement shall always prevail in the decision making process&#44; as the results of this study offer excellent specificity but deficient sensitivity&#46; It is likely that an improvement in risk estimation by FRAX<span class="elsevierStyleSup">&#174;</span> &#40;for example&#44; including falls&#41; could increase its PPV&#46;</p><p id="par0165" class="elsevierStylePara elsevierViewall">In conclusion&#44; osteoporotic fractures have a multifactorial pathogenesis&#44; so it is difficult to predict them using only one risk factor&#44; although strongly associated&#44; as happens with osteoporosis values in DXA&#46; Clinical judgement should prevail&#44; and to adjust the risk of fragility fracture&#44; it is more efficient to consider the greater number of fracture risk factors possible among those that demonstrated evidence&#46; The FRIDEX model to calibrate the Spanish FRAX<span class="elsevierStyleSup">&#174;</span> improves the predictive parameters of fracture risk and is more cost-effective than standard clinical practice based on DXA&#46; However&#44; new studies are necessary for the external validation of these FRAX<span class="elsevierStyleSup">&#174;</span> thresholds or cut-off points in other cohorts and in the general population&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Funding</span><p id="par0170" class="elsevierStylePara elsevierViewall">This project was financed by grants of the <span class="elsevierStyleGrantSponsor" id="gs1">Instituto de Salud Carlos III&#44; Ministry of Science</span> &#91;<span class="elsevierStyleGrantNumber" refid="gs1">PI09&#47;90507</span>&#93;&#44; and the <span class="elsevierStyleGrantSponsor" id="gs2">Instituto Universitario de Investigaci&#243;n en Atenci&#243;n Primaria IDIAP Jordi Gol&#44; Institut Catal&#224; de la Salut&#44; Barcelona&#44; Spain</span>&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conflict of interest</span><p id="par0175" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
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              "titulo" => "Detection of the best FRAX threshold values for calibration"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To detect FRAX<span class="elsevierStyleSup">&#174;</span> threshold levels that identify groups of the population that are at high&#47;low risk of osteoporotic fracture in the Spanish female population using a cost-effective assessment&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This is a cohort study&#46; Eight hundred and sixteen women 40&#8211;90 years old selected from the FRIDEX cohort with densitometry and risk factors for fracture at baseline who received no treatment for osteoporosis during the 10 year follow-up period and were stratified into 3 groups&#47;levels of fracture risk &#40;low &#60;10&#37;&#44; 10&#8211;20&#37; intermediate and high &#62;20&#37;&#41; according to the real fracture incidence&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The thresholds of FRAX<span class="elsevierStyleSup">&#174;</span> baseline for major osteoporotic fracture were&#58; low risk &#60;5&#59; intermediate &#8805;5 to &#60;7&#46;5 and high &#8805;7&#46;5&#46; The incidence of fracture with these values was&#58; low risk &#40;3&#46;6&#37;&#59; 95&#37; CI 2&#46;2&#8211;5&#46;9&#41;&#44; intermediate risk &#40;13&#46;7&#37;&#59; 95&#37; CI 7&#46;1&#8211;24&#46;2&#41; and high risk &#40;21&#46;4&#37;&#59; 95&#37; CI 12&#46;9&#8211;33&#46;2&#41;&#46; The most cost-effective option was to refer to <span class="elsevierStyleItalic">dual energy X-ray absorptiometry</span> &#40;DXA-scan&#41; for FRAX<span class="elsevierStyleSup">&#174;</span><span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>5 &#40;Intermediate and high risk&#41; to reclassify by FRAX<span class="elsevierStyleSup">&#174;</span> with DXA-scan at high&#47;low risk&#46; These thresholds select 17&#46;5&#37; of women for DXA-scan and 10&#37; for treatment&#46; With these thresholds of FRAX<span class="elsevierStyleSup">&#174;</span>&#44; compared with the strategy of opportunistic case finding isolated risk factors&#44; would improve the predictive parameters and reduce 82&#46;5&#37; the DXA-scan&#44; 35&#46;4&#37; osteoporosis prescriptions and 28&#46;7&#37; cost to detect the same number of women who suffer fractures&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The use of FRAX<span class="elsevierStyleSup">&#174;</span> thresholds identified as high&#47;low risk of osteoporotic fracture in this calibration &#40;FRIDEX model&#41; improve predictive parameters in Spanish women and in a more cost-effective than the traditional model based on the T-score<span class="elsevierStyleHsp" style=""></span>&#8804;<span class="elsevierStyleHsp" style=""></span>&#8722;2&#46;5 of DXA scan&#46;</p></span>"
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            "titulo" => "Background and objective"
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          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Patients and methods"
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          2 => array:2 [
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Fundamento y objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Detectar los umbrales de la herramienta FRAX<span class="elsevierStyleSup">&#174;</span> que determinen los grupos de riesgo alto&#47;bajo de fractura osteopor&#243;tica en la poblaci&#243;n femenina espa&#241;ola y su valoraci&#243;n coste-efectiva&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes y m&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudio de cohortes&#46; Ochocientas diecis&#233;is mujeres de 40-90 a&#241;os de la cohorte FRIDEX con densitometr&#237;a basal&#44; factores de riesgo de fractura y sin tratamiento para la osteoporosis en los 10 a&#241;os de seguimiento&#46; Se estratificaron en 3 grupos&#47;niveles de riesgo de fractura principal &#40;bajo<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>10&#37;&#44; intermedio 10-20&#37; y alto<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>20&#37;&#41; seg&#250;n la incidencia real de fractura&#44; y se buscaron los puntos de corte equivalentes de FRAX<span class="elsevierStyleSup">&#174;</span> basal&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Los umbrales de FRAX<span class="elsevierStyleSup">&#174;</span> basal para fractura principal fueron&#58; riesgo bajo<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>5&#59; intermedio<span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>5 y &#60;<span class="elsevierStyleHsp" style=""></span>7&#44;5 y alto<span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>7&#44;5&#46; La incidencia real de fractura con estos valores fue&#58; riesgo bajo &#40;3&#44;6&#37;&#59; IC 95&#37; 2&#44;2-5&#44;9&#41;&#59; intermedio &#40;13&#44;7&#37;&#59; IC 95&#37;7&#44;1-24&#44;2&#41;&#44; y alto &#40;21&#44;4&#37;&#59; IC 95&#37; 12&#44;9-33&#44;2&#41;&#46; La opci&#243;n m&#225;s coste-efectiva fue realizar una <span class="elsevierStyleItalic">dual energy X-ray absorptiometry</span> &#40;DXA&#44; &#171;absorciometr&#237;a dual de rayos X&#187;&#41; para FRAX<span class="elsevierStyleSup">&#174;</span><span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>5 &#40;riesgo intermedio y alto&#41; para reclasificar los casos mediante FRAX<span class="elsevierStyleSup"><span class="elsevierStyleItalic">&#174;</span></span> con DXA en riesgo alto&#47;bajo&#46; As&#237; se seleccionar&#237;an 17&#44;5&#37; de las mujeres para DXA y 10&#37; para tratamiento&#46; Con estos umbrales calibrados de FRAX<span class="elsevierStyleSup">&#174;</span>&#44; comparados con la estrategia tradicional basada en la DXA&#44; se mejoran los par&#225;metros predictivos y se reducen las DXA &#40;82&#44;5&#37;&#41;&#44; los tratamientos &#40;35&#44;4&#37;&#41; y el coste global &#40;28&#44;7&#37;&#41; para detectar al mismo n&#250;mero de mujeres que tuvieron fracturas&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La utilizaci&#243;n de los umbrales de FRAX<span class="elsevierStyleSup">&#174;</span> identificados como alto&#47;bajo riesgo de fractura osteopor&#243;tica en la presente calibraci&#243;n &#40;modelo FRIDEX&#41; mejorar&#237;an los par&#225;metros predictivos en mujeres espa&#241;olas y de una forma m&#225;s coste-efectiva que el modelo tradicional basado en el T-score &#8804; -2&#44;5 de la DXA&#46;</p></span>"
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            "titulo" => "Fundamento y objetivo"
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            "identificador" => "abst0030"
            "titulo" => "Pacientes y m&#233;todos"
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        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0025">Please cite this article as&#58; Azagra R&#44; Roca G&#44; Mart&#237;n-S&#225;nchez JC&#44; Casado E&#44; Encabo G&#44; Zwart M&#44; et al&#46; Umbrales de FRAX<span class="elsevierStyleSup">&#174;</span> para identificar personas con alto o bajo riesgo de fractura osteopor&#243;tica en poblaci&#243;n femenina espa&#241;ola&#46; Med Clin &#40;Barc&#41;&#46; 2015&#59;144&#58;1&#8211;8&#46;</p>"
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        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr1.jpeg"
            "Alto" => 1457
            "Ancho" => 2337
            "Tamanyo" => 179514
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Flowchart for the selection of the cohort of Spanish women who did not receive treatment during the 10 years of follow-up anti-OP&#58; treatment with osteoporotic medications not supplemented with calcium&#47;vitamin D&#59; OPFx&#58; osteoporotic fracture&#59; Major Fx&#58; major fracture &#40;major osteoporotic in FRAX<span class="elsevierStyleSup">&#174;</span>&#41;&#46;</p>"
        ]
      ]
      1 => array:7 [
        "identificador" => "fig0010"
        "etiqueta" => "Fig&#46; 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr2.jpeg"
            "Alto" => 1583
            "Ancho" => 1578
            "Tamanyo" => 134269
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        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Decision-making diagram according to the most cost-effective option in the FRIDEX cohort of Spanish women who did not receive treatment during the 10 years of follow-up DXA&#58; dual energy X-ray absorptiometry&#46;</p>"
        ]
      ]
      2 => array:7 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "tabla" => array:2 [
          "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">FN&#58; femoral neck&#59; SD&#58; standard deviation&#59; DXA&#58; <span class="elsevierStyleItalic">dual energy X-ray absorptiometry</span>&#59; FRIDEX&#58; Fracture RIsk factors and bone DEnsitometry type central dual X-ray&#59; BMI&#58; body mass index&#59; TF&#58; total femur&#59; L1&#8211;L4&#58; total lumbar spine&#46;</p>"
          "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"><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Women of the FRIDEX cohort without treatment for osteoporosis</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Women&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">816 &#40;100&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Age in years&#44; mean &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">56&#46;8 &#40;8&#46;24&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">&#62;65 years old&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">147 &#40;18&#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="table-entry  " align="left" valign="top">Weight in kg &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">68&#46;4 &#40;11&#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="table-entry  " align="left" valign="top">Height in cm&#44; mean &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">155&#46;4 &#40;5&#46;95&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">BMI in kg&#47;cm<span class="elsevierStyleSup">2</span>&#44; mean &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28&#46;4 &#40;4&#46;80&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Active smoker&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">102 &#40;12&#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="table-entry  " align="left" valign="top">Hazardous alcohol consumption&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6 &#40;0&#46;74&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Previous fractures&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">166 &#40;20&#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="table-entry  " align="left" valign="top">Hip fracture in parents&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">114 &#40;14&#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="table-entry  " align="left" valign="top">Glucocorticoids&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">38 &#40;4&#46;66&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Rheumatoid arthritis&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">11 &#40;1&#46;35&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Falls in the previous year&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">199 &#40;24&#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="table-entry  " align="left" valign="top">Osteoporosis in the DXA &#40;CF&#44; TF or L1&#8211;L4&#41;&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">127 &#40;15&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Prescriptions&#58; calcium and&#47;or vitamin D&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">303 &#40;37&#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="table-entry  " align="left" valign="top">Prescription of medications with bone activity&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab886658.png"
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          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Profile of the FRIDEX cohort with 816 women with 10-year follow-up&#46;</p>"
        ]
      ]
      3 => array:7 [
        "identificador" => "tbl0010"
        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "tabla" => array:2 [
          "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">BMD&#58; bone mineral density&#59; FRIDEX&#58; Fracture RIsk factors and bone DEnsitometry type central dual X-ray&#59; CI 95&#37;&#58; confidence interval 95&#37;&#59; BMI&#58; body mass index&#59; ns&#58; not significant&#59; u&#58; units&#46;</p>"
          "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"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Women with fracture &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>49&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Women without fracture &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>767&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37; CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Age in years&#44; mean &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">62&#46;6 &#40;9&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">56&#46;5 &#40;8&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;3&#8211;9&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">BMI in kg&#47;cm<span class="elsevierStyleSup">2</span>&#44; mean &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">27&#46;9 &#40;4&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28&#46;4 &#40;4&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;437&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">BMI &#60;20<span class="elsevierStyleHsp" style=""></span>kg&#47;cm<span class="elsevierStyleSup">2</span>&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;04&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;682&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Previous fracture&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">15&#46;7&#8211;45&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Hip fracture in parents&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;360&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Active smoker&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;956&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Alcohol &#8805;3<span class="elsevierStyleHsp" style=""></span>&#956;l&#47;day&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;311&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Glucocorticoids&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;722&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Rheumatoid arthritis&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;137&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">ns&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Falls in the previous year&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">38&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">23&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;016&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1&#46;4&#8211;30&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">BMD with osteoporosis&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">60&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">14&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">30&#46;1&#8211;59&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Normal BMD&#44; &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">32&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">14&#46;7&#8211;32&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab886656.png"
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        "descripcion" => array:1 [
          "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Risk factors in the groups of women with fracture and without fracture in the FRIDEX cohort without treatment during the 10 years&#46;</p>"
        ]
      ]
      4 => array:7 [
        "identificador" => "tbl0015"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "tabla" => array:2 [
          "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">BMD&#58; bone mineral density determined by central DXA&#59; DXA&#58; <span class="elsevierStyleItalic">dual energy X-ray absorptiometry</span>&#59; FRAX<span class="elsevierStyleSup">&#174;</span>&#58; <span class="elsevierStyleItalic">Fracture Risk Assessment</span><span class="elsevierStyleSup">&#174;</span>&#44; <span class="elsevierStyleItalic">WHO Technical Report</span>&#59; FRIDEX&#58; Fracture RIsk factors and bone DEnsitometry type central dual X-ray&#59; Fx&#58; fractures&#59; OP&#58; osteoporosis&#46;</p><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Source</span>&#58; Leslie et al&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">26</span></a></p>"
          "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"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Fracture risk groups as per the CAROC System<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">26</span></a> criteria&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Best cut-off points of baseline FRAX<span class="elsevierStyleSup">&#174;</span> identified in the FRIDEX cohort&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Real results of Fx in the FRIDEX cohort after 10-year follow-upMean &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Situation when performing the DXA and calculating FRAX<span class="elsevierStyleSup">&#174;</span> with BMD in case of moderate or high risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Cases without major Fx&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Cases with major Fx&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Low&#47;high final risk after reevaluation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Final result&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Low &#40;&#60;10&#37;&#41;&#58; 673&#160;cases&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">&#60;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;6&#37; &#40;2&#46;2&#8211;5&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Low risk FRAX<span class="elsevierStyleSup">&#174;</span> without BMD &#60;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">649 &#40;96&#46;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">24 &#40;3&#46;6&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Low&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">673&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Moderate &#40;&#8805;10 and &#60;20&#37;&#41;&#58; 73 cases&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">&#8805;5 and &#60;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13&#46;7&#37; &#40;7&#46;1&#8211;24&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#60;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">42 &#40;91&#46;3&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4 &#40;8&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Low&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">46&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#60;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12 &#40;85&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2 &#40;14&#46;3&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">High&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#8805;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3 &#40;100&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0 &#40;0&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">High&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#8805;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6 &#40;60&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4 &#40;40&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">High&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">10&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">High &#40;&#8805;20&#37;&#41;&#58; 70 cases&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">&#8805;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21&#46;4&#37; &#40;12&#46;9&#8211;33&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#60;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">14 &#40;93&#46;3&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1 &#40;6&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Low&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">No OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#8805;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13 &#40;72&#46;2&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5 &#40;27&#46;8&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">High&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">OP in DXA and FRAX<span class="elsevierStyleSup">&#174;</span> with BMD &#8805;7&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">28 &#40;75&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9 &#40;24&#46;3&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">High&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">37&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">All cases&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">767 &#40;94&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49 &#40;6&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">816&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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        "descripcion" => array:1 [
          "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Risk groups&#44; FRAX<span class="elsevierStyleSup">&#174;</span> threshold values that define them&#44; situation during reevaluation with FRAX<span class="elsevierStyleSup">&#174;</span> with bone mineral density&#44; and final result in low&#47;high risk after reevaluation&#46;</p>"
        ]
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        "identificador" => "tbl0020"
        "etiqueta" => "Table 4"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
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          "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">DXA&#58; <span class="elsevierStyleItalic">dual energy X-ray absorptiometry</span>&#59; FRAX<span class="elsevierStyleSup">&#174;</span>&#58; <span class="elsevierStyleItalic">Fracture Risk Assessment</span><span class="elsevierStyleSup">&#174;</span>&#59; FRIDEX&#58; Fracture RIsk factors and bone DEnsitometry type central dual X-ray&#59; Fx&#58; fractures&#46;</p>"
          "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"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Model based on FRAX<span class="elsevierStyleSup">&#174;</span></th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Traditional model</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">FRIDEX calibration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&#8364;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Clinical judgement and DXA&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">&#8364;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Pharmacological treatments&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">82&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">350&#44;337&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">127&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">542&#44;595&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">DXA in intermediate<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>high risk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">143&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8523&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">816&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">48&#44;634&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Cases with real Fx that ARE treated&#47;cost in &#8364;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">100&#44;082&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">90&#44;501&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Cases with real Fx that are NOT treated&#47;cost in &#8364;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">29<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">142&#44;910&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">29<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">162&#44;072&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Value in &#8364;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">601&#44;852&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">843&#44;082&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Difference in &#8364; in favour of FRIDEX calibration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">&#8722;241&#44;950&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">Savings percentage in favour of FRIDEX calibration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">28&#46;7&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
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ISSN: 23870206
Original language: English
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