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Original article
Is there an association between commonly employed biomarkers of liver fibrosis and liver stiffness in the general population?
Francesco Giuseppe Foschia,1, Marco Domenicalib, Pierluigi Giacomonic, Anna Chiara Dall’Aglioa, Fabio Contia, Alberto Borghia, Vittoria Bevilacquaa, Lucia Napolia, Federica Miricia, Alessandro Cucchettib, Giorgio Ercolania, Andrea Casadei Gardinid, Stefano Bellentanie, Amalia Gastaldellif, Mauro Giuffrèg, Claudio Tiribellie, Giorgio Bedognie,1,
Corresponding author
giorgiobedogni@gmail.com

Corresponding author at: Clinical Epidemiology Unit, Liver Research Center, Building Q, AREA Science Park, Strada Statale 14 km 163.5, 34012 Basovizza, Trieste, Italy.
, Bagnacavallo Study Group 2
a Department of Internal Medicine, Ospedale di Faenza, AUSL Romagna, Italy
b Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
c Department of Internal Medicine, Ospedale di Lugo, AUSL Romagna, Italy
d Department of Oncology and Hematology, Division of Oncology, University of Modena and Reggio Emilia, Modena, Italy
e Italian Liver Foundation, Basovizza, Trieste, Italy
f Institute of Clinical Physiology, National Research Council, Pisa, Italy
g Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">1</span><span class="elsevierStyleSectionTitle" id="sect0035">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Many non-invasive serum markers of liver fibrosis have been developed in tertiary care centers using liver biopsy as the reference standard <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46; These biomarkers are increasingly used to estimate the prevalence of liver fibrosis in the general population&#44; which is a very different setting from the one in which they were developed <a class="elsevierStyleCrossRefs" href="#bib0175">&#91;2&#44;3&#93;</a>&#46; Because liver biopsy is invasive and cannot be performed outside tertiary care centers&#44; the true prevalence of liver fibrosis in the general population is currently unknown <a class="elsevierStyleCrossRefs" href="#bib0180">&#91;3&#44;4&#93;</a>&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Liver stiffness &#40;LS&#41;&#44; as measured by transient elastography &#40;TE&#41;&#44; is an accurate surrogate index of liver fibrosis in tertiary care centers <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46; Contrarily to liver biopsy&#44; TE can be easily performed in the general population&#46; While it is plausible that a &#8220;high&#8221; value of LS as detected by TE is associated with a higher probability or degree of liver fibrosis in the general population&#44; this association cannot be evaluated against liver biopsy because of its invasiveness <a class="elsevierStyleCrossRefs" href="#bib0180">&#91;3&#44;5&#93;</a>&#46; On the other hand&#44; TE is expensive&#44; time-consuming&#44; and requires substantial expertise <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">A recent study <a class="elsevierStyleCrossRef" href="#bib0175">&#91;2&#93;</a>&#44; pooling 6925 individuals from four countries <a class="elsevierStyleCrossRefs" href="#bib0195">&#91;6&#8211;11&#93;</a>&#44; suggested that a TE cut-point LS of 9&#46;1<span class="elsevierStyleHsp" style=""></span>kPa can be applied to diagnose significant fibrosis &#40;&#8805;F2&#41; in primary care&#46; Expectedly&#44; however&#44; only a minority &#40;5&#37;&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>352&#41; of the 6925 individuals had undergone liver biopsy <a class="elsevierStyleCrossRef" href="#bib0225">&#91;12&#93;</a>&#46; The Rotterdam study used&#44; instead&#44; a cut-point of 8&#46;0<span class="elsevierStyleHsp" style=""></span>kPa to diagnose liver fibrosis&#44; detecting it in 5&#46;6&#37; of 3041 consecutive participants aged &#8805;45 years who visited their study center <a class="elsevierStyleCrossRef" href="#bib0230">&#91;13&#93;</a>&#46; Because the TE cut-point of 8&#46;0<span class="elsevierStyleHsp" style=""></span>kPa was chosen based on a previous study of patients with non-alcoholic fatty liver disease &#40;NAFLD&#41; performed in tertiary care <a class="elsevierStyleCrossRef" href="#bib0235">&#91;14&#93;</a>&#44; it was pointed out the need to consider the so-called spectrum bias&#44; that is the fact that the performance of a diagnostic test is known to vary substantially with the prevalence of the disease <a class="elsevierStyleCrossRef" href="#bib0225">&#91;12&#93;</a>&#46; In addition&#44; one has to consider the loss of efficiency and the classification problems arising from the dichotomization of intrinsically continuous variables such as LS <a class="elsevierStyleCrossRef" href="#bib0240">&#91;15&#93;</a>&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">In the present analysis of the general population of the Bagnacavallo study <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#44; to avoid the problems of spectrum bias and dichotomization <a class="elsevierStyleCrossRefs" href="#bib0225">&#91;12&#44;15&#93;</a>&#44; we evaluated the association between LS and seven commonly employed biomarkers of liver fibrosis &#40;AST&#47;ALT&#44; APRI&#44; Forns Index&#44; FIB-4&#44; GGT&#44; BARD and BAAT&#41; using LS and all the biomarkers where this was feasible &#40;AST&#47;ALT&#44; APRI&#44; Forns Index&#44; FIB-4&#44; GGT&#41; as continuous and the other biomarkers &#40;BARD and BAAT&#41; as discrete&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2</span><span class="elsevierStyleSectionTitle" id="sect0040">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;1</span><span class="elsevierStyleSectionTitle" id="sect0045">Study design</span><p id="par0025" class="elsevierStylePara elsevierViewall">The protocol and the primary outcome of the Bagnacavallo study are reported in detail elsewhere <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; The study was approved by the Ethical Committee of Area Vasta Romagna &#8211; IRST &#40;reference number 112&#41;&#44; and all subjects gave their written informed consent&#46; Briefly&#44; 3933 citizens of Bagnacavallo &#40;Ravenna&#44; Italy&#41; aged 30&#8211;60 years&#44; were studied between October 2005 and March 2009&#46; Altered liver enzymes &#40;ALE&#41; were defined as alanine transaminase &#40;ALT&#41;<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>40<span class="elsevierStyleHsp" style=""></span>U&#47;l and&#47;or aspartate transaminase &#40;AST&#41;<span class="elsevierStyleHsp" style=""></span>&#62;37<span class="elsevierStyleHsp" style=""></span>U&#47;l&#44; <span class="elsevierStyleItalic">i&#46;e&#46;</span> the upper limit of normal &#40;ULN&#41; of the laboratory&#46; After the exclusion of subjects with HBV infection&#44; HCV infection&#44; and lack of ultrasonography&#44; the main Bagnacavallo analysis was performed on 349 ALE&#43; and 1810 ALE&#8722; citizens <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; The same 2159 &#40;349<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>1810&#41; citizens were analyzed here&#46; 636 &#40;29&#37;&#41; of them had consecutively undergone TE between November 2008 and March 2009 <a class="elsevierStyleCrossRef" href="#bib0250">&#91;17&#93;</a>&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">&#40;A previous analysis of TE in the Bagnacavallo cross-section was performed only in a subsample of 331 &#8220;healthy&#8221; subjects selected among 780 citizens who had undergone TE between October 2008 and May 2009 <a class="elsevierStyleCrossRef" href="#bib0250">&#91;17&#93;</a>&#46; Our starting sample of citizens with TE availability &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>636&#41; is lower than that employed in the previous report &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>780&#41; <a class="elsevierStyleCrossRef" href="#bib0250">&#91;17&#93;</a> because of different selection criteria <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; The present analysis was performed by strictly applying the designed criteria of the Bagnacavallo Study <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;2</span><span class="elsevierStyleSectionTitle" id="sect0050">Clinical and laboratory assessment</span><p id="par0035" class="elsevierStylePara elsevierViewall">All participants underwent a detailed clinical history and physical examination&#44; as described in detail elsewhere <a class="elsevierStyleCrossRef" href="#bib0255">&#91;18&#93;</a>&#46; Alcohol intake was assessed by interview <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; Weight and height were measured following international guidelines <a class="elsevierStyleCrossRef" href="#bib0260">&#91;19&#93;</a>&#44; and waist circumference was measured at the midpoint between the last rib and the iliac crest <a class="elsevierStyleCrossRef" href="#bib0255">&#91;18&#93;</a>&#46; Body mass index &#40;BMI&#41; was calculated as weight &#40;m&#41;&#47;height &#40;m&#41;<span class="elsevierStyleSup">2</span> and classified according to the National Institutes of Health &#40;NIH&#41; guidelines <a class="elsevierStyleCrossRef" href="#bib0265">&#91;20&#93;</a>&#46; The performed blood tests included&#58; &#40;1&#41; glucose&#59; &#40;2&#41; triglycerides&#59; &#40;3&#41; total cholesterol&#59; &#40;4&#41; high-density lipoprotein &#40;HDL&#41; cholesterol&#59; &#40;5&#41; low-density lipoprotein &#40;LDL&#41; cholesterol&#59; &#40;6&#41; ALT&#59; &#40;7&#41; AST&#59; &#40;8&#41; GGT&#59; &#40;9&#41; platelets&#46; The metabolic syndrome &#40;MS&#41; was diagnosed using the harmonized international definition <a class="elsevierStyleCrossRef" href="#bib0270">&#91;21&#93;</a>&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;3</span><span class="elsevierStyleSectionTitle" id="sect0055">Liver ultrasonography</span><p id="par0040" class="elsevierStylePara elsevierViewall">Liver ultrasonography was performed by five experienced physicians&#44; as described in detail elsewhere <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; After the exclusion of HBV and HCV infection&#44; NAFLD was defined as fatty liver &#40;FL&#41; associated with ethanol intake &#8804;20<span class="elsevierStyleHsp" style=""></span>g&#47;day in women and &#8804;30<span class="elsevierStyleHsp" style=""></span>g&#47;day in men <a class="elsevierStyleCrossRef" href="#bib0275">&#91;22&#93;</a>&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;4</span><span class="elsevierStyleSectionTitle" id="sect0060">Transient elastography</span><p id="par0045" class="elsevierStylePara elsevierViewall">LS &#40;kPa&#41; was measured with FibroScan &#40;Echosens&#44; Paris&#44; France&#41; by two experienced operators&#46; All measurements were performed with the M probe because the XL probe&#44; which was developed specifically for obese individuals <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#44; was not available when the study was performed&#46; LS was measured on the right hepatic lobe through intercostal spaces with the patient lying in dorsal decubitus position and with the right arm maximally abducted <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46; Following current recommendations&#44; a measurement was considered valid if it was repeated at least 10 times&#44; and the &#91;&#40;75<span class="elsevierStyleSup">th</span><span class="elsevierStyleHsp" style=""></span>&#8722;<span class="elsevierStyleHsp" style=""></span>25<span class="elsevierStyleSup">th</span> percentile&#41;&#47;median ratio&#93; was &#8804;0&#46;30 <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;5</span><span class="elsevierStyleSectionTitle" id="sect0065">Biomarkers</span><p id="par0050" class="elsevierStylePara elsevierViewall">We calculated all the biomarkers of liver fibrosis that could be obtained from the Bagnacavallo study database&#58; &#40;1&#41; AST&#47;ALT ratio&#59; &#40;2&#41; APRI&#59; &#40;3&#41; Forns index&#59; &#40;4&#41; FIB-4&#59; &#40;5&#41; GGT&#59; &#40;6&#41; BARD&#59; &#40;7&#41; BAAT <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;6</span><span class="elsevierStyleSectionTitle" id="sect0070">Statistical analysis</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;6&#46;1</span><span class="elsevierStyleSectionTitle" id="sect0075">Descriptive statistics</span><p id="par0055" class="elsevierStylePara elsevierViewall">Most continuous variables were not Gaussian-distributed and all are reported as median &#40;50<span class="elsevierStyleSup">th</span> percentile&#41; and interquartile range &#40;IQR&#59; 25<span class="elsevierStyleSup">th</span> and 75<span class="elsevierStyleSup">th</span> percentiles&#41;&#46; Discrete variables are reported as the number and proportion of subjects with the characteristic of interest&#46; Between-group comparisons of discrete variables were performed using Pearson&#39;s Chi-square test and those of continuous variables using median regression with heteroskedasticity-robust standard errors <a class="elsevierStyleCrossRefs" href="#bib0255">&#91;18&#44;23&#93;</a>&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;6&#46;2</span><span class="elsevierStyleSectionTitle" id="sect0080">Regression modeling</span><p id="par0060" class="elsevierStylePara elsevierViewall">The relationship between LS and each of the seven biomarkers was quantified using a multivariable linear regression model &#40;LRM&#41; with robust confidence intervals <a class="elsevierStyleCrossRef" href="#bib0285">&#91;24&#93;</a>&#46; The LRM used LS &#40;continuous&#44; kPa&#41; as response variable and ALE &#40;discrete&#44; 0<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>no&#59; 1<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>yes&#41; and the biomarker of interest as predictors&#46; All the biomarkers were modeled as continuous&#44; with the exception of BARD and BAAT&#44; which are intrinsically discrete <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#46; ALE was used as predictor because of the design of the Bagnacavallo study&#44; which enrolled separately ALE&#43; and ALE&#8722; citizens <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; Because LS was available only for 636 &#40;29&#37;&#41; of the 2159 citizens and had a univariate missingness pattern <a class="elsevierStyleCrossRef" href="#bib0290">&#91;25&#93;</a>&#44; we fitted the LRM using multiple imputation &#40;MI&#41; estimates of LS <a class="elsevierStyleCrossRef" href="#bib0295">&#91;26&#93;</a>&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2&#46;6&#46;3</span><span class="elsevierStyleSectionTitle" id="sect0085">Multiple imputation</span><p id="par0065" class="elsevierStylePara elsevierViewall">Under the assumption that LS was missing at random &#40;MAR&#41;&#44; we used univariate multiple imputation &#40;MI&#41; to create several complete versions of LS by replacing its missing values with plausible data values <a class="elsevierStyleCrossRef" href="#bib0300">&#91;27&#93;</a>&#46; Theoretically&#44; when the complete-data model is an LRM with outcome Y and predictors Xs and the missing data occur in Y only as in the present case&#44; complete case analysis &#40;CCA&#41; and MI are equivalent <a class="elsevierStyleCrossRefs" href="#bib0295">&#91;26&#44;28&#93;</a>&#46; However&#44; MI gains an advantage over CCA if additional predictors of Y are available that are not part of Xs&#44; as it is the case for the present analysis <a class="elsevierStyleCrossRefs" href="#bib0295">&#91;26&#44;28&#93;</a>&#46; Following current guidelines&#44; we nonetheless performed a CCA and compared its findings to those of MI <a class="elsevierStyleCrossRef" href="#bib0300">&#91;27&#93;</a>&#46; The target variable of the MI model was LS and the predictors were the seven biomarkers &#40;AST&#47;ALT&#44; APRI&#44; Forns index&#44; FIB-4&#44; GGT&#44; BARD and BAAT&#41; in addition to the other variables available in the study database &#40;sex&#44; age&#44; weight&#44; height&#44; BMI&#44; waist circumference&#44; glucose&#44; triglycerides&#44; cholesterol&#44; HDL-cholesterol&#44; LDL-cholesterol&#44; systolic blood pressure&#44; diastolic blood pressure&#44; ALT&#44; AST&#44; GGT&#44; platelets&#44; alcohol intake&#44; fatty liver&#44; metabolic syndrome and its components&#41;&#46; Because LS had a non-Gaussian distribution&#44; it was imputed using predictive mean matching with 5 knots on 100 MI datasets and the Abayomi procedure was used to check the agreement between the observed&#44; imputed and complete values <a class="elsevierStyleCrossRefs" href="#bib0295">&#91;26&#44;29&#93;</a>&#46; The imputer and the analyst were the same person and the scope of the MI model was narrow&#44; <span class="elsevierStyleItalic">i&#46;e&#46;</span> it was devised for testing only the present study hypothesis <a class="elsevierStyleCrossRef" href="#bib0295">&#91;26&#93;</a>&#46; Taking into account the design of the Bagnacavallo study&#44; MI was performed separately in ALE&#43; and ALE&#8722; citizens <a class="elsevierStyleCrossRef" href="#bib0295">&#91;26&#93;</a>&#46; We checked the linearity of the association of LS with the continuous biomarkers of liver fibrosis using fractional polynomials for MI <a class="elsevierStyleCrossRef" href="#bib0315">&#91;30&#93;</a>&#46; Evidence of non-linearity was detected only for GGT&#44; which was transformed using natural logarithms &#40;lnGGT&#41;&#46; To aid the clinical interpretation of the results&#44; we calculated and plotted the marginal probabilities of LS corresponding to the 5<span class="elsevierStyleSup">th</span>&#44; 25<span class="elsevierStyleSup">th</span>&#44; 50<span class="elsevierStyleSup">th</span>&#44; 75<span class="elsevierStyleSup">th</span> and 95<span class="elsevierStyleSup">th</span> internal percentile of each biomarker for ALE&#43; and ALE&#8722; citizens <a class="elsevierStyleCrossRefs" href="#bib0320">&#91;31&#44;32&#93;</a>&#46; Statistical analysis was performed using Stata 16&#46;1 &#40;Stata Corporation&#44; College Station&#44; TX&#44; USA&#41;&#46;</p></span></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">3</span><span class="elsevierStyleSectionTitle" id="sect0090">Results</span><p id="par0070" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> compares the features of the citizens with &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>636&#41; and without &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1523&#41; TE&#46; This comparison is aimed at studying the pattern of missing data and at identifying their potential predictors <a class="elsevierStyleCrossRefs" href="#bib0295">&#91;26&#44;27&#93;</a>&#46; The interpretation of this data must take into account the fact that the Bagnacavallo study was designed to perform liver ultrasonography in 100&#37; of ALE&#43; and in 50&#37; of ALE&#8722; citizens&#44; reaching 97&#37; of the former and 52&#37; of the latter <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#46; Thus&#44; ALE&#43; citizens were virtually sampled in their entirety by the study design&#46; No patient had decompensated liver cirrhosis&#44; heart failure&#44; or ALT greater than five times the ULN&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> reports and <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> plots the LRMs used to evaluate the association between LS and the seven biomarkers&#46; Because there were just 4 citizens with BAAT<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4 &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#44; we collapsed the categories 3 &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>172&#41; and 4 &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4&#41; of BAAT to one category &#40;&#8805;3&#44; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>176&#41; for further modeling&#46; LS was significantly associated with APRI&#44; Forns index&#44; lnGGT&#44; BARD and BAAT but not with ALT&#47;AST and FIB-4&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0080" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> reports and <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> plots the marginal means and robust 95&#37; confidence intervals of LS estimated by the LRM for the 5<span class="elsevierStyleSup">th</span>&#44; 25<span class="elsevierStyleSup">th</span>&#44; 50<span class="elsevierStyleSup">th</span>&#44; 75<span class="elsevierStyleSup">th</span>&#44; and 95<span class="elsevierStyleSup">th</span> internal percentile of each continuous biomarker&#46; As shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#44; LS was always higher in ALE&#43; than in ALE&#8722; citizens&#46; It can be readily appreciated from both <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> and <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> that the mean change of LS between the 5th and 95th internal percentile of any continuous biomarker was &#8804; 1<span class="elsevierStyleHsp" style=""></span>kPa&#46; <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> and <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> also show that the mean change of LS between scores 0 and 3 of BARD and between scores 0 and &#8805;3 of BAAT was &#62;1<span class="elsevierStyleHsp" style=""></span>kPa but of doubtful clinical relevance&#46; In the case of BARD and BAAT&#44; the imprecision of the estimates is partly attributable to their discrete nature <a class="elsevierStyleCrossRef" href="#bib0240">&#91;15&#93;</a>&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">4</span><span class="elsevierStyleSectionTitle" id="sect0095">Discussion</span><p id="par0085" class="elsevierStylePara elsevierViewall">In the present analysis of the Bagnacavallo study <a class="elsevierStyleCrossRef" href="#bib0245">&#91;16&#93;</a>&#44; we have shown that the mean change in LS associated with an increase from the 5<span class="elsevierStyleSup">th</span> to the 95<span class="elsevierStyleSup">th</span> internal percentile of AST&#47;ALT ratio&#44; APRI&#44; Forns index&#44; FIB-4&#44; and LnGGT is &#8804;1<span class="elsevierStyleHsp" style=""></span>kPa and of doubtful biological relevance&#46; While the mean change of LS between scores 0 and 3 of BARD and scores 0 and &#8805;3 of BAAT is &#8805;1<span class="elsevierStyleHsp" style=""></span>kPa&#44; it is of doubtful clinical relevance&#46; Thus&#44; under the assumption that LS&#44; as measured by TE&#44; is a surrogate index of liver fibrosis in the general population <a class="elsevierStyleCrossRef" href="#bib0180">&#91;3&#93;</a>&#44; our findings cast some doubts on the ability of biomarkers developed in tertiary care centers to detect liver fibrosis in the general population&#46; The most likely reason for this finding is the so-called spectrum bias&#44; <span class="elsevierStyleItalic">i&#46;e&#46;</span> the fact that the performance of a diagnostic test is known to vary substantially with the prevalence of the underlying disease <a class="elsevierStyleCrossRef" href="#bib0225">&#91;12&#93;</a>&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">Our study has several strengths&#46; First&#44; LS was measured on a random subsample of citizens from the general population&#44; who are expected to differ from individuals enrolled in primary&#44; secondary&#44; and tertiary care <a class="elsevierStyleCrossRef" href="#bib0330">&#91;33&#93;</a>&#59; second&#44; we analyzed LS as continuous&#44; avoiding the loss of efficiency and generalizability produced by dichotomization <a class="elsevierStyleCrossRef" href="#bib0240">&#91;15&#93;</a>&#59; third&#44; we took missing data into account using MI <a class="elsevierStyleCrossRef" href="#bib0300">&#91;27&#93;</a>&#46; Our study has&#44; nonetheless&#44; some limitations&#46; First&#44; only 29&#37; of our subjects had undergone measurement of TE&#46; This was determined mostly by the availability of FibroScan in the last few months of the study&#44; which can be plausibly considered a random event&#46; The amount of missing data is not a problem <span class="elsevierStyleItalic">per se</span> provided that the MAR assumption is met <a class="elsevierStyleCrossRef" href="#bib0295">&#91;26&#93;</a>&#46; To increase the plausibility of the MAR assumption&#44; we built an MI model taking into account all the variables available in the study dataset <a class="elsevierStyleCrossRef" href="#bib0295">&#91;26&#93;</a>&#46; We also performed a CCA&#44; which confirmed the results of the MI analysis &#40;data not shown&#41;&#46; Second&#44; the Bagnacavallo study population is a general population&#44; and as such&#44; it represents the &#8220;population at risk&#8221; of the so-called &#8220;ecology of care model&#8221; <a class="elsevierStyleCrossRefs" href="#bib0245">&#91;16&#44;33&#93;</a>&#46; This implies that our findings do not necessarily extend to populations made of subjects consulting a physician for primary care&#44; as are most of the studied populations <a class="elsevierStyleCrossRef" href="#bib0175">&#91;2&#93;</a>&#44; <span class="elsevierStyleItalic">i&#46;e&#46;</span> populations made of &#8220;subjects consulting a physician&#8221; according to the ecology of care model <a class="elsevierStyleCrossRef" href="#bib0330">&#91;33&#93;</a>&#46; Third&#44; although we performed standardized measurements of TE <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a>&#44; the XL probe was not available during the study period&#46; Not surprisingly&#44; TE availability was less common among obese citizens &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41; and BMI is one of the predictors we took into account to make the MAR assumption of MI more plausible&#46; However&#44; the M probe used in the present study overestimates LS by a median of 1&#46;4<span class="elsevierStyleHsp" style=""></span>kPa <a class="elsevierStyleCrossRef" href="#bib0170">&#91;1&#93;</a> so that&#44; to the degree that they are influenced by obesity&#44; our estimates of LS &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41; are biased upward&#44; meaning that our conclusion of the low performance of biomarkers in the general population would be reinforced by such systematic error&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">TE cut-points of 8 or 9<span class="elsevierStyleHsp" style=""></span>kPa are presently suggested for the diagnosis of liver fibrosis in the general population <a class="elsevierStyleCrossRefs" href="#bib0175">&#91;2&#44;3&#93;</a>&#46; Even if dichotomization always involves a loss in efficiency and reduces the generalizability of the findings <a class="elsevierStyleCrossRefs" href="#bib0225">&#91;12&#44;15&#93;</a>&#44; it is of interest that the 95&#37;CI of the mean LS did not include 8<span class="elsevierStyleHsp" style=""></span>kPa for all continuous biomarkers &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; While the 95&#37;CI of the mean LS included 8<span class="elsevierStyleHsp" style=""></span>kPa for a BARD score of 3 in ALE&#8722; citizens&#44; they were wide&#44; ranging from 4&#46;8 to 8&#46;2<span class="elsevierStyleHsp" style=""></span>kPa &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; More interestingly&#44; in ALE&#43; citizens&#44; the mean LS corresponding to a BARD score of 3 was 8&#46;0<span class="elsevierStyleHsp" style=""></span>kPa&#44; even if its 95&#37;CI were again wide &#40;6&#46;3&#8211;9&#46;8<span class="elsevierStyleHsp" style=""></span>kPa&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; The fact that the 95&#37;CI of mean LS included 8 for a BAAT score &#8805;3 is less relevant because of its wide 95&#37;CI &#40;6&#46;5&#8211;8&#46;1&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">5</span><span class="elsevierStyleSectionTitle" id="sect0100">Conclusion</span><p id="par0100" class="elsevierStylePara elsevierViewall">In conclusion&#44; in the Bagnacavallo Study&#44; we found only modest associations between LS as measured by TE and seven commonly employed biomarkers of liver fibrosis&#46;<span class="elsevierStyleDefList"><span class="elsevierStyleSectionTitle" id="sect0105">Abbreviations</span><span class="elsevierStyleDefTerm">95&#37;CI</span><span class="elsevierStyleDefDescription"><p id="par0125" class="elsevierStylePara elsevierViewall">95&#37; confidence interval</p></span><span class="elsevierStyleDefTerm">AFLD</span><span class="elsevierStyleDefDescription"><p id="par0130" class="elsevierStylePara elsevierViewall">alcoholic fatty liver disease</p></span><span class="elsevierStyleDefTerm">ALE</span><span class="elsevierStyleDefDescription"><p id="par0135" class="elsevierStylePara elsevierViewall">altered liver enzymes</p></span><span class="elsevierStyleDefTerm">ALT</span><span class="elsevierStyleDefDescription"><p id="par0140" class="elsevierStylePara elsevierViewall">alanine aminotransferase</p></span><span class="elsevierStyleDefTerm">AST</span><span class="elsevierStyleDefDescription"><p id="par0145" class="elsevierStylePara elsevierViewall">aspartate aminotransferase</p></span><span class="elsevierStyleDefTerm">BMI</span><span class="elsevierStyleDefDescription"><p id="par0150" class="elsevierStylePara elsevierViewall">body mass index</p></span><span class="elsevierStyleDefTerm">FL</span><span class="elsevierStyleDefDescription"><p id="par0155" class="elsevierStylePara elsevierViewall">fatty liver</p></span><span class="elsevierStyleDefTerm">GGT</span><span class="elsevierStyleDefDescription"><p id="par0160" class="elsevierStylePara elsevierViewall">gamma-glutamyl-transferase</p></span><span class="elsevierStyleDefTerm">HBV</span><span class="elsevierStyleDefDescription"><p id="par0165" class="elsevierStylePara elsevierViewall">hepatitis B virus</p></span><span class="elsevierStyleDefTerm">HCV</span><span class="elsevierStyleDefDescription"><p id="par0170" class="elsevierStylePara elsevierViewall">hepatitis C virus</p></span><span class="elsevierStyleDefTerm">HDL</span><span class="elsevierStyleDefDescription"><p id="par0175" class="elsevierStylePara elsevierViewall">high density lipoprotein</p></span><span class="elsevierStyleDefTerm">IQR</span><span class="elsevierStyleDefDescription"><p id="par0180" class="elsevierStylePara elsevierViewall">interquartile range</p></span><span class="elsevierStyleDefTerm">LDL</span><span class="elsevierStyleDefDescription"><p id="par0185" class="elsevierStylePara elsevierViewall">low density lipoprotein</p></span><span class="elsevierStyleDefTerm">LRM</span><span class="elsevierStyleDefDescription"><p id="par0190" class="elsevierStylePara elsevierViewall">linear regression model</p></span><span class="elsevierStyleDefTerm">LS</span><span class="elsevierStyleDefDescription"><p id="par0195" class="elsevierStylePara elsevierViewall">liver stiffness</p></span><span class="elsevierStyleDefTerm">MAR</span><span class="elsevierStyleDefDescription"><p id="par0200" class="elsevierStylePara elsevierViewall">missing at random</p></span><span class="elsevierStyleDefTerm">MI</span><span class="elsevierStyleDefDescription"><p id="par0205" class="elsevierStylePara elsevierViewall">multiple imputation</p></span><span class="elsevierStyleDefTerm">MS</span><span class="elsevierStyleDefDescription"><p id="par0210" class="elsevierStylePara elsevierViewall">metabolic syndrome</p></span><span class="elsevierStyleDefTerm">NAFLD</span><span class="elsevierStyleDefDescription"><p id="par0215" class="elsevierStylePara elsevierViewall">non-alcoholic fatty liver disease</p></span><span class="elsevierStyleDefTerm">NIH</span><span class="elsevierStyleDefDescription"><p id="par0220" class="elsevierStylePara elsevierViewall">National Institutes of Health</p></span><span class="elsevierStyleDefTerm">TE</span><span class="elsevierStyleDefDescription"><p id="par0225" class="elsevierStylePara elsevierViewall">transient elastography</p></span><span class="elsevierStyleDefTerm">ULN</span><span class="elsevierStyleDefDescription"><p id="par0230" class="elsevierStylePara elsevierViewall">upper limit of normal</p></span></span></p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Funding statement</span><p id="par0105" class="elsevierStylePara elsevierViewall">The present analysis was sponsored by a research grant from <span class="elsevierStyleGrantSponsor" id="gs1">Gilead Sciences</span> &#40;Milan&#44; Italy&#41; to the Italian Liver Foundation&#46; The Sponsor had no role in the design and conduct of the study&#59; in the collection&#44; analysis&#44; and interpretation of the data&#59; or in the preparation and review of the manuscript&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Conflict of interest</span><p id="par0110" class="elsevierStylePara elsevierViewall">The authors declare no conflict of interest&#46;</p></span></span>"
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          "titulo" => "Introduction"
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              "titulo" => "Clinical and laboratory assessment"
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              "titulo" => "Liver ultrasonography"
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              "titulo" => "Transient elastography"
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          "titulo" => "References"
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    "pdfFichero" => "main.pdf"
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    "fechaRecibido" => "2020-01-08"
    "fechaAceptado" => "2020-04-29"
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          "clase" => "keyword"
          "titulo" => "Keywords"
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          "palabras" => array:6 [
            0 => "Epidemiology"
            1 => "Cross-sectional study"
            2 => "Chronic liver disease"
            3 => "Liver fibrosis"
            4 => "Elasticity imaging technique"
            5 => "Biomarkers"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction and objectives</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Surrogate biomarkers of liver fibrosis developed in tertiary care are increasingly used in general populations&#46; We evaluated the association between liver stiffness &#40;LS&#41; and five continuous &#40;AST&#47;ALT&#44; APRI&#44; Forns Index&#44; FIB-4&#44; GGT&#41; and two discrete biomarkers &#40;BARD&#44; BAAT&#41; in a general population&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">636 &#40;29&#37;&#41; of the 2159 citizens of the Bagnacavallo Study had LS measured by transient elastography&#46; Using linear regression with univariate multiple imputation&#44; we evaluated the association of LS with the above biomarkers in the total sample of 2159 citizens&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The mean change of LS between the 5<span class="elsevierStyleSup">th</span> and 9<span class="elsevierStyleSup">5th</span> internal percentile of any continuous biomarker was &#8804;1<span class="elsevierStyleHsp" style=""></span>kPa&#46; The mean change of LS between scores 0 and 3 of BARD and scores 0 and &#8805;3 of BAAT was &#62;1<span class="elsevierStyleHsp" style=""></span>kPa but of doubtful clinical relevance&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">We found a modest association between LS and seven biomarkers of liver fibrosis in a general population&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0050">Francesco Giuseppe Foschi and Giorgio Bedogni contributed equally to the present work&#46;</p>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0055">Please see a list of the members of the Bagnacavallo Study Group in Appendix A&#46;</p>"
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            "apendice" => "<p id="par0120" class="elsevierStylePara elsevierViewall">Francesca Dazzani&#44; Arianna Lanzi&#44; Gaia Saini&#44; Margherita Rimini&#44; Alessandra Ravaioli&#44; Giulia Rovesti&#44; Lauro Bucchi&#44; Fabio Falcini&#44; Mauro Bernardi&#44; Pietro Andreone&#44; Giuseppe Francesco Stefanini&#46;</p>"
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          "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Association between liver stiffness and seven biomarkers of liver fibrosis&#46; Values are regression coefficients and robust 95&#37; confidence intervals from linear regression &#40;see <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; Abbreviations&#58; ALE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>altered liver enzymes&#59; Ln<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>natural logarithm&#46; Values whose 95&#37;CI do not cross the 0 line have an associated <span class="elsevierStyleItalic">p</span>-value<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#46;</p>"
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          "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Values of liver stiffness corresponding to the 5<span class="elsevierStyleSup">th</span>&#44; 25<span class="elsevierStyleSup">th</span>&#44; 50<span class="elsevierStyleSup">th</span>&#44; 75<span class="elsevierStyleSup">th</span> and 95<span class="elsevierStyleSup">th</span> internal percentiles of the continuous biomarkers and to the original scores of the discrete biomarkers &#40;see <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; Abbreviations&#58; ALE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>altered liver enzymes&#46;</p>"
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          "leyenda" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Abbreviations&#58; TE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>transient elastography&#59; BMI<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>body mass index&#59; NIH<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>National Institutes of Health&#59; FL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>fatty liver&#59; NAFLD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>non-alcoholic fatty liver disease&#59; AFLD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>alcoholic fatty liver disease&#59; HDL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>high-density lipoprotein&#59; LDL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>low-density lipoprotein&#59; ALT<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>alanine aminotransferase&#59; ULN<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>upper limit of normal of alanine aminotransferase &#40;40<span class="elsevierStyleHsp" style=""></span>U&#47;l&#41;&#59; AST<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>aspartate aminotransferase&#59; GGT<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>gamma-glutamyl-transferase&#46;</p>"
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;11&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Age &#40;years&#41;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">49 &#40;41&#59; 56&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">50 &#40;42&#59; 56&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;093&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">BMI &#40;kg&#47;m</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleItalic">&#41;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">25&#46;9 &#40;23&#46;4&#59; 29&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">24&#46;6 &#40;22&#46;4&#59; 27&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">BMI class &#40;NIH&#41;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Underweight&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Normal weight&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">601 &#40;39&#46;5&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Overweight&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">548 &#40;36&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">229 &#40;36&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Obesity class 1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Obesity class 2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Obesity class 3&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">22 &#40;1&#46;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0 &#40;0&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Fatty liver</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Fatty liver degree</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>None&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">839 &#40;55&#46;1&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">424 &#40;66&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Light&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">384 &#40;25&#46;2&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">151 &#40;23&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Moderate&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">206 &#40;13&#46;5&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">47 &#40;7&#46;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Severe&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">94 &#40;6&#46;2&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14 &#40;2&#46;2&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Fatty liver type</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>No FL&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">839 &#40;55&#46;1&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">424 &#40;66&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>NAFLD&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">440 &#40;28&#46;9&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">127 &#40;20&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>AFLD&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">244 &#40;16&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">85 &#40;13&#46;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Waist circumference &#40;cm&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">102&#46;0 &#40;95&#46;0&#59; 110&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">98&#46;0 &#40;93&#46;0&#59; 105&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">High waist circumference</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1089 &#40;71&#46;5&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">406 &#40;63&#46;8&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Glucose &#40;mg&#47;dl&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">90 &#40;84&#59; 97&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">89 &#40;83&#59; 96&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;070&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">High fasting glucose</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">310 &#40;20&#46;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">106 &#40;16&#46;7&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;048&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Triglycerides &#40;mg&#47;dl&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">104 &#40;74&#59; 157&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">95 &#40;67&#59; 142&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;007&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">High triglycerides</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">419 &#40;27&#46;5&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">145 &#40;22&#46;8&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;023&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Total cholesterol &#40;mg&#47;dl&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">206 &#40;183&#59; 234&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">213 &#40;189&#59; 236&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">HDL cholesterol &#40;mg&#47;dl&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">58 &#40;48&#59; 69&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">63 &#40;51&#59; 75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Low HDL</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">219 &#40;14&#46;4&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">64 &#40;10&#46;1&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;007&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">LDL cholesterol &#40;mg&#47;dl&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">128 &#40;105&#59; 152&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">128 &#40;107&#59; 150&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;000&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Systolic blood pressure &#40;mm Hg&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">130 &#40;120&#59; 140&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">125 &#40;120&#59; 135&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;025&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Diastolic blood pressure &#40;mm Hg&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">80 &#40;80&#59; 90&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">80 &#40;80&#59; 90&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;000&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">High blood pressure</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">959 &#40;63&#46;0&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">364 &#40;57&#46;2&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;013&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Metabolic syndrome</span>&nbsp;\t\t\t\t\t\t\n
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                  """
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        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at2"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:3 [
          "leyenda" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Abbreviations&#58; ALE<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>altered liver enzymes&#59; Ln<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>natural logarithm&#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="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="7" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Liver stiffness &#40;kPa&#41;</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Model 7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">ALE&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;3<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;7 to 1&#46;9&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;0<a class="elsevierStyleCrossRef" href="#tblfn0025">&#42;&#42;</a> &#91;0&#46;4 to 1&#46;7&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;3<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;7 to 1&#46;9&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;4<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;8 to 2&#46;0&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;1<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;5 to 1&#46;7&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;5<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;9 to 2&#46;1&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;2<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;6 to 1&#46;8&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AST&#47;ALT&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8722;0&#46;4 &#91;&#8722;0&#46;9 to 0&#46;0&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">APRI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;0<a class="elsevierStyleCrossRef" href="#tblfn0020">&#42;</a> &#91;0&#46;5 to 3&#46;5&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Forns index&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;2<a class="elsevierStyleCrossRef" href="#tblfn0025">&#42;&#42;</a> &#91;0&#46;1 to 0&#46;3&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">FIB-4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;3 &#91;&#8722;0&#46;1 to 0&#46;7&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">LnGGT&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;4<a class="elsevierStyleCrossRef" href="#tblfn0030">&#42;&#42;&#42;</a> &#91;0&#46;2 to 0&#46;6&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">BARD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;0 &#91;&#8722;0&#46;3 to 0&#46;4&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="5" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">Liver stiffness &#40;kPa&#41;</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="5" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">ALE&#8722; citizens</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Percentile<a class="elsevierStyleCrossRef" href="#tblfn0035"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">5<span class="elsevierStyleSup">th</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">25<span class="elsevierStyleSup">th</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">50<span class="elsevierStyleSup">th</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">75<span class="elsevierStyleSup">th</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95<span class="elsevierStyleSup">th</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AST&#47;ALT&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">5&#46;2 &#40;4&#46;9&#8211;5&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5&#46;1 &#40;4&#46;9&#8211;5&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">5&#46;0 &#40;4&#46;9&#8211;5&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">4&#46;9 &#40;4&#46;8&#8211;5&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;7 &#40;4&#46;5&#8211;5&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">APRI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;8 &#40;4&#46;6&#8211;4&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;9 &#40;4&#46;7&#8211;5&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">5&#46;0 &#40;4&#46;9&#8211;5&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">5&#46;1 &#40;5&#46;0&#8211;5&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">5&#46;4 &#40;5&#46;1&#8211;5&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Forns index&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">FIB-4&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">4&#46;9 &#40;4&#46;7&#8211;5&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">LnGGT&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">5&#46;6 &#40;5&#46;2&#8211;5&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
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                  \t\t\t\t">0&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">3&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#8805;3<a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">BARD&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">BAAT&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">6&#46;1 &#40;5&#46;5&#8211;6&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab2333760.png"
              ]
            ]
            1 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
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                  \t\t\t\t  " colspan="5" align="center" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Percentile<a class="elsevierStyleCrossRef" href="#tblfn0035"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab2333763.png"
              ]
            ]
          ]
          "notaPie" => array:3 [
            0 => array:3 [
              "identificador" => "tblfn0035"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0035">Internal percentile for continuous predictors</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0040"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0040">original score values for discrete predictors</p>"
            ]
            2 => array:3 [
              "identificador" => "tblfn0045"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0045">BAAT scores 3 and 4 were collapsed because of the low number of subjects with a BAAT score of 4 &#40;see also <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Marginal means and robust 95&#37; confidence intervals of liver stiffness estimated from linear regression for the 5<span class="elsevierStyleSup">th</span>&#44; 25<span class="elsevierStyleSup">th</span>&#44; 50<span class="elsevierStyleSup">th</span>&#44; 75<span class="elsevierStyleSup">th</span>&#44; and 95<span class="elsevierStyleSup">th</span> internal percentiles of the continuous biomarkers &#40;AST&#47;ALT&#44; APRI&#44; Forns index&#44; FIB-4&#44; lnGGT&#41; and the original scores of the discrete &#40;BARD&#44; BAAT&#41; biomarkers&#46; The underlying regression models are given in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46;</p>"
        ]
      ]
    ]
    "bibliografia" => array:2 [
      "titulo" => "References"
      "seccion" => array:1 [
        0 => array:2 [
          "identificador" => "bibs0015"
          "bibliografiaReferencia" => array:33 [
            0 => array:3 [
              "identificador" => "bib0170"
              "etiqueta" => "&#91;1&#93;"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "EASL-ALEH Clinical Practice Guidelines&#58; non-invasive tests for evaluation of liver disease severity and prognosis"
                      "autores" => array:1 [
                        0 => array:2 [
                          "colaboracion" => "European Association for Study of Liver&#44; Asociacion Latinoamericana para el Estudio del Higado"
                          "etal" => false
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.jhep.2015.04.006"
                      "Revista" => array:6 [
                        "tituloSerie" => "J Hepatol"
                        "fecha" => "2015"
                        "volumen" => "63"
                        "paginaInicial" => "237"
                        "paginaFinal" => "264"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/25911335"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            1 => array:3 [
              "identificador" => "bib0175"
              "etiqueta" => "&#91;2&#93;"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Transient elastography for screening of liver fibrosis&#58; cost-effectiveness analysis from six prospective cohorts in Europe and Asia"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "M&#46; Serra-Burriel"
                            1 => "I&#46; Graupera"
                            2 => "P&#46; Tor&#225;n"
                            3 => "M&#46; Thiele"
                            4 => "D&#46; Roulot"
                            5 => "V&#46; Wai-Sun Wong"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.jhep.2019.08.019"
                      "Revista" => array:3 [
                        "tituloSerie" => "J Hepatol"
                        "fecha" => "2019"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24211739"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            2 => array:3 [
              "identificador" => "bib0180"
              "etiqueta" => "&#91;3&#93;"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Screening for liver fibrosis in the general population&#58; a call for action"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "P&#46; Gin&#232;s"
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Article information
ISSN: 16652681
Original language: English
DOI:10.1016/j.aohep.2020.04.003
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