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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Anaemia is a common complication in chronic kidney disease and is associated with a higher comorbidity and mortality&#46;<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">1&#8211;4</span></a> One of the most significant causes is erythropoietin secretion deficiency&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">5&#44;6</span></a> Therefore&#44; treatment with erythropoiesis-stimulating agents &#40;ESAs&#41; is included within the management of anaemia in these patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">5&#44;7&#8211;10</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Most patients with chronic kidney disease present an adequate control of their anaemia with medium doses of these drugs&#46;<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">7</span></a> However&#44; a significant percentage of them &#40;from 5&#37; to 10&#37;&#44; according to some studies&#41;<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">4&#44;10&#44;11</span></a> have higher requirements of ESAs due to multiple causes&#58; iron deficiency&#44; haemolysis&#44; neoplasia&#44; infections&#44; inflammation&#44; vitamin deficiencies&#44; toxins and inadequate dialysis&#46;<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">10&#44;11</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">This clinical condition&#44; as a whole&#44; is called &#8220;erythropoietin resistance&#8221;&#44; which is linked to a worse prognosis in patients on haemodialysis&#46;<a class="elsevierStyleCrossRefs" href="#bib0220"><span class="elsevierStyleSup">12&#44;13</span></a> It is worth highlighting that it is a clinical concept which is difficult to define&#46; An arbitrary&#44; but data-based&#44; definition is that provided by the European guidelines from 1999&#58; &#8220;Failure to attain the target haemoglobin concentration while receiving more than 300<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week or 20&#44;000<span class="elsevierStyleHsp" style=""></span>IU&#47;week of erythropoietin&#8221; also specifying &#8220;or a continued need for such dosage to maintain the target haemoglobin concentration&#8221;&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">14</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Furthermore&#44; the usefulness of the erythropoietin resistance index &#40;ERI&#41; as a good marker of resistance to erythropoietin and a factor associated with occurrence of adverse effects in chronic haemodialysis has been reported&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;15&#8211;18</span></a> Some groups have established that an erythropoietin resistance index greater than 9<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week&#47;g&#47;dl could be considered as resistant&#46;<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">19&#44;20</span></a> In one study it was demonstrated that ERI values above 15<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week&#47;g&#47;dl had greater mortality&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">15</span></a> Likewise&#44; other authors have suggested that erythropoietin requirements greater than 109<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week&#44; without taking into account the haemoglobin values&#44; are a warning sign of possible erythropoietin resistance&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">21</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Moreover&#44; the platelet-to-lymphocyte ratio &#40;PLR&#41; and neutrophil-to-lymphocyte ratio &#40;NLR&#41; are emerging biological markers of inflammation and endothelial dysfunction&#44;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;22</span></a> initially applied to heart disease patients<a class="elsevierStyleCrossRefs" href="#bib0270"><span class="elsevierStyleSup">22&#8211;24</span></a> and&#44; more recently&#44; to patients with end-stage chronic kidney disease&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;25&#44;26</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">Currently&#44; there are few studies on the relationship between these ratios and erythropoietin resistance&#46; One of the most representative includes a sample of 104&#160;patients belonging to a single site&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">11</span></a></p><p id="par0035" class="elsevierStylePara elsevierViewall">The objective of our study was to evaluate the relationship between these ratios and erythropoietin resistance in our prevalent population on chronic haemodialysis&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Design and population</span><p id="par0040" class="elsevierStylePara elsevierViewall">The study protocol was designed in accordance with the Declaration of Helsinki&#46; The data were gathered in a registry which guaranteed the anonymity of the participants and was only known about by the research team&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">It was a cross-sectional study carried out at four Avericum centres across the province of Las Palmas &#40;Spain&#41;&#46; The records of the haemodialysis sessions of 534 prevalent patients in June 2017 were assessed&#46; The dialysis prescription was 3&#46;5&#8211;4<span class="elsevierStyleHsp" style=""></span>h with a blood flow between 300 and 450<span class="elsevierStyleHsp" style=""></span>ml&#47;min&#44; using a standard dialysis concentrate of bicarbonate and high-permeability polyethersulfone haemodialysis filters &#40;Elisio&#174; &#8211; Nipro&#174; Model&#41; with a surface area greater than 1&#46;7<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span> and an ultrafiltration rate greater than 74<span class="elsevierStyleHsp" style=""></span>ml&#47;h&#47;mmHg&#41;&#46; The erythropoiesis-stimulating agent used in all patients was Epoetin Beta &#40;Neorecormon&#174; &#8211; Roche Farma AG&#174;&#41;&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">The exclusion criteria were not receiving treatment with ESAs at the time of the study &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>76&#41; and medical conditions which may have influenced the absolute counts of platelets&#44; lymphocytes and haemoglobin&#58; admission to hospital for an infection&#44; cancer or haematological causes in the previous three months &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>24&#41;&#46; Transfusion in the last three months &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4&#41;&#44; active onco-haematological diseases &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>13&#41; and patients undergoing steroid treatment &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>26&#41; were also part of the exclusion criteria&#46; Some of the patients fulfilled more than one exclusion criterion &#40;total number of patients excluded&#58; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>137&#41;&#46; Therefore&#44; after applying the criteria&#44; the study sample was 397 patients&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Erythropoietin resistance was defined as those patients who had erythropoietin doses of greater than 20&#44;000<span class="elsevierStyleHsp" style=""></span>IU and haemoglobin values of less than 11<span class="elsevierStyleHsp" style=""></span>g&#47;dl&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">14</span></a></p><p id="par0060" class="elsevierStylePara elsevierViewall">For the PLR calculation&#44; the ratio between the absolute platelet count and the absolute lymphocyte count in the blood count was obtained&#46; In order to obtain the NLR&#44; the ratio between the absolute neutrophil count and the absolute lymphocyte count in the blood count was calculated&#46; And&#44; finally&#44; the ERI was obtained by calculating the weekly dose of erythropoietin &#40;IU&#41; divided by the dry weight &#40;kg&#41; and divided&#44; in turn&#44; by the serum haemoglobin levels &#40;g&#47;dl&#41;&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;15&#44;16</span></a></p><p id="par0065" class="elsevierStylePara elsevierViewall">Other variables analysed were&#58; albumin&#44; serum iron&#44; transferrin saturation index &#40;TSI&#41; and C-reactive protein &#40;CRP&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">The R program version 3&#46;3&#46;2 &#40;2017&#41; was used for the statistical analysis &#40;R Foundation for Statistical Computing&#44; Vienna&#44; Austria&#46; URL <a href="http://www.r-projet.org/"><span class="elsevierStyleUnderline">http&#58;&#47;&#47;www&#46;R-projet&#46;org&#47;</span></a>&#41;&#46; The results were considered statistically significant if the <span class="elsevierStyleItalic">p</span>-value was less than 0&#46;05&#46; The continuous variables were summarised as mean<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>standard deviation &#40;normal variables&#41; or median and quartiles &#40;non-normal variables&#41;&#46; The categorical variables were summarised as percentages&#46; The normality of the variables was analysed using the Shapiro&#8211;Wilk test&#46; The Pearson coefficient was used for correlations&#46; To evaluate whether there were significant differences according to the ERI quartile&#44; the Kruskal&#8211;Wallis test was used for quantitative variables&#44; and the chi-square test for categorical variables&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">When significant differences were detected between ERI quartiles&#44; the respective post hoc tests were carried out using the Tukey procedure&#44; when the transformation of the variable to the logarithmic scale enabled normality and homoscedasticity to be achieved&#44; or otherwise using the Dunn&#39;s test&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">To evaluate the predictive ability of the PLR and the NLR on the ERI&#44; regression models were adjusted in which the log &#40;ERI&#41; was used as a response variable&#46; The models were also adjusted for the age&#44; gender and weight of the individual&#46; In the case of the NLR&#44; to evaluate the particular effect of the neutrophil and lymphocyte counts &#40;which are part of the NLR definition&#41;&#44; these variables were introduced into the regression model and a step-by-step method was applied to select the set of variables with the best predictive ability&#46; A similar procedure was carried out with the PLR&#44; introducing in this case the platelets and lymphocytes as additional variables to then apply the step-by-step procedure&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Likewise&#44; in order to carry out an analysis of the ability of the PLR to diagnose erythropoietin resistance&#44; a logistic regression model&#44; adjusted for age and gender&#44; was estimated&#46; A step-by-step method was also applied to simplify the model and to eliminate non-explanatory variables&#46; The calculation of the ROC curve was carried out when only the PLR was used as the diagnostic criterion to predict erythropoietin resistance&#46;</p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Results</span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Baseline characteristics of the population</span><p id="par0090" class="elsevierStylePara elsevierViewall">The baseline characteristics of the patients included are described in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; A stratification of the ERI in quartiles &#40;Q1<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;59&#8211;4&#46;08&#44; Q2<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4&#46;08&#8211;7&#46;04&#44; Q3<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>7&#46;04&#8211;12&#46;55&#44; Q4<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>12&#46;55&#8211;80&#46;65&#41; was performed and the values of the different variables among the thus defined groups were compared &#40;<a class="elsevierStyleCrossRefs" href="#tbl0010">Tables 2 and 3</a>&#41;&#46; The dry weight&#44; lymphocytes&#44; haemoglobin&#44; concentrations of serum iron&#44; albumin and C-reactive protein showed significant differences among the ERI quartiles&#46; For all these variables &#40;except haemoglobin&#41;&#44; the post hoc Tukey tests &#40;with the variables transformed beforehand to the logarithmic scale&#41; showed that the first&#44; second and third quartiles did not display significant differences among them&#44; and that the significant differences occurred with regard to the fourth quartile&#46; In the case of haemoglobin&#44; the Dunn&#39;s post hoc test showed that its value is significantly higher in the first quartile of ERI&#44; did not show significant differences between the second and third quartiles and showed a significantly lower value in the fourth quartile&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">The correlation between the different study variables and the log value &#40;ERI&#41; was calculated &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46; The correlation is significant for all variables apart from age and neutrophils&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">Likewise&#44; correlations were carried out between different inflammation and iron kinetics parameters with the log &#40;ERI&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Relationship between the neutrophil-to-lymphocyte ratio &#40;NLR&#41; and the erythropoietin resistance index &#40;ERI&#41;</span><p id="par0105" class="elsevierStylePara elsevierViewall">Given the asymmetry of the NLR variable for each ERI quartile&#44; the comparison of the NLR values between the four ERI quartiles was performed initially using the non-parametric Kruskal&#8211;Wallis test&#58; this test showed significant differences in the distribution of the ERI for the different ERI quartiles &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;00058&#41;&#46; To determine the quartiles among which these differences occur&#44; ANOVA and a post hoc test were used&#46; For this&#44; the asymmetry was corrected&#44; transforming the NLR values to a logarithmic scale&#46; The analysis of variance of the log &#40;NLR&#41; confirmed that there are significant differences in the log &#40;NLR&#41; values according to the ERI quartiles &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0004296&#41;&#46; The Shapiro&#8211;Wilk test did not find evidence of lack of normality in the residuals &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;3808&#41; and Levene&#39;s test did not detect heteroscedasticity among groups &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;4492&#41;&#44; which validates the performance of ANOVA &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; The Tukey multiple comparison test was used to determine among which quartiles the NLR differences were found&#58; the log values &#40;NLR&#41; for the fourth ERI quartile differ significantly from the values in the first and second quartile&#46; The log value &#40;NLR&#41; in the third ERI quartile does not differ significantly from the others&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">To evaluate the predictive ability of the NLR on the log &#40;ERI&#41;&#44; a regression model was adjusted&#59; although the effect of the NLR on the log &#40;ERI&#41; turned out to be significant &#40;standardised beta<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;173&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; the <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> value turned out to be very low &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;029&#41;&#44; which indicates that&#44; although the ERI value tends to grow with the NLR&#44; the predictive ability of the latter variable is limited&#46; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows the overall regression line adjusted for all the data&#44; in which the growing trend of the ERI with the NLR is observed and in which the presence of considerable variability can be seen&#46; If we analyse this graph carefully&#44; we can observe that&#44; in particular&#44; the majority of the subjects &#40;90&#37;&#41; have NLR values lower than 6&#59; within this group&#44; only 3&#46;9&#37; are resistant to erythropoietin&#59; subjects with NLR &#62;6 only make up 10&#37; of the total&#59; but within this group there are proportionally more subjects with erythropoietin resistance &#40;18&#46;9&#37;&#41;&#46; In other words&#44; the risk of erythropoietin resistance is higher among subjects with high NLR values&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0115" class="elsevierStylePara elsevierViewall">This motivates adjusting a logistic regression model to predict the erythropoietin resistance depending on the NLR&#46; With this model&#44; we obtain that the OR of suffering from erythropoietin resistance is 1&#46;32 &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#59; 95&#37; CI&#58; 1&#46;118&#8211;1&#46;544&#41; for each unit of increase in the NLR&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Relationship between the platelet-to-lymphocyte ratio &#40;PLR&#41; and the erythropoietin resistance index &#40;ERI&#41;</span><p id="par0120" class="elsevierStylePara elsevierViewall">As with the NLR&#44; the asymmetry of distributions of the PLR for each ERI quartile led to the comparisons of the PLR according to ERI quartiles being carried out using the Kruskal&#8211;Wallis test&#44; with the differences turning out to be statistically significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;00001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><p id="par0125" class="elsevierStylePara elsevierViewall">Similarly&#44; to decide in which quartiles these differences occur&#44; an ANOVA of the log &#40;PLR&#41; was carried out&#44; with the differences being significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#46; The normality of the log &#40;PLR&#41; was analysed using the Shapiro&#8211;Wilk test &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;65&#41; and homoscedasticity with Levene&#39;s test &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;737&#41;&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">The Tukey test indicated that the differences were in the fourth ERI quartile compared to the rest&#46; No significant differences in the distribution of the log &#40;PLR&#41; were detected in the other three quartiles&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">In the regression adjustment to predict the log &#40;ERI&#41; based on the PLR&#44; a significant positive slope &#40;standardised beta<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;32&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; was obtained&#44; although&#44; once again&#44; the <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> value turned out to be low &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;103&#41; although higher than that obtained with the NLR&#44; which means that the predictive ability of the PLR is better than that of the NLR &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>&#41;&#46;</p><elsevierMultimedia ident="fig0020"></elsevierMultimedia><p id="par0140" class="elsevierStylePara elsevierViewall">As occurred with the NLR&#44; it is observed that the log &#40;ERI&#41; increases with the PLR value&#59; as in that case 90&#37; of the PLR values are below 233&#59; in this group&#44; some 3&#46;9&#37; of patients are resistant to erythropoietin&#59; however&#44; when the PLR is above 233&#44; 17&#46;5&#37; of the subjects are resistant to erythropoietin&#59; therefore&#44; the risk of being resistant to erythropoietin increases with the PLR value&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">To assess this risk&#44; the logistic regression model indicates that an increase of one unit in the PLR translates into an OR of 1&#46;011 &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#59; 95&#37; CI&#58; 1&#46;005&#8211;1&#46;015&#41; of presenting erythropoietin resistance&#46; An additional calculation makes it possible to estimate that the OR of suffering from erythropoietin resistance doubles for each increase of 67 units in the PLR value&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">Furthermore&#44; a multivariate regression analysis was carried out&#44; in which variables such as the TSI&#44; serum iron&#44; C-reactive protein and the PLR were included&#46; The correlation of the PLR with logERI continued to be significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; with the total predictive capacity of the model&#44; measured in terms of <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span>&#44; of 17&#46;26&#37;&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">To analyse the capacity of the PLR to predict erythropoietin resistance&#44; the area under the ROC curve was measured &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;681&#41; &#40;95&#37; CI&#58; 0&#46;541&#8211;0&#46;821&#41;&#46; A PLR cut-off point of 125&#46;5 would result in 80&#46;95&#37; sensitivity and 42&#46;82&#37; specificity &#40;<a class="elsevierStyleCrossRef" href="#fig0025">Fig&#46; 5</a>&#41;&#46;</p><elsevierMultimedia ident="fig0025"></elsevierMultimedia></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Discussion</span><p id="par0160" class="elsevierStylePara elsevierViewall">Cardiovascular risk in haemodialysis patients is well known&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">1</span></a> From the pathophysiological point of view&#44; inflammation plays a very important role&#46; Historically&#44; multiple parameters have been listed to measure this&#44; including C-reactive protein&#44; serum albumin and B-type natriuretic peptide&#46; The NLR and the PLR have emerged in recent years as markers of inflammation and endothelial damage in different types of patients&#46; Given the fact that they are easy to obtain&#44; inexpensive and routinely extracted in patients on haemodialysis&#44; they are a very interesting analytical parameter in this group of patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">6&#44;25&#44;26</span></a></p><p id="par0165" class="elsevierStylePara elsevierViewall">Likewise&#44; the management of anaemia with erythropoiesis-stimulating agents and intravenous iron have been set up as the basis for the treatment of patients on haemodialysis for many years&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">5&#44;10</span></a></p><p id="par0170" class="elsevierStylePara elsevierViewall">The ERI is a good marker of erythropoietin resistance and is related to both intercurrent processes &#40;neoplasia&#44; infections&#44; etc&#46;&#41; and to a worse prognosis in patients on haemodialysis&#44; which is why their detection and follow-up is very important&#46;<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">10&#44;11&#44;15&#44;16</span></a></p><p id="par0175" class="elsevierStylePara elsevierViewall">The objective of our study was to determine whether resistance to erythropoietin is related to the NLR and the PLR&#46; It is worth pointing out that patients who were admitted to hospital for infection&#44; cancer or haematological causes&#59; those who had received a blood transfusion in the last three months&#59; those who presented active onco-haematological comorbidities and those who were receiving steroid treatment were ruled out from the study&#46; All of these are factors which could&#44; a priori&#44; alter the count of these blood cells&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">Unlike a previous study&#44; which only found a significant association of the ERI with the PLR &#40;and not with the NLR&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">11</span></a> our study found an association with both parameters&#46; An explanation could be that the low number of lymphocytes&#44; the common parameter of both ratios&#44; could be the most important factor&#46; In isolation&#44; the reduction in absolute number of lymphocytes has been used as a marker of ischaemic heart disease&#46;<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">27&#44;28</span></a> One factor to bear in mind&#44; found in our study&#44; is that the fourth quartile had the lowest levels of albumin and dry weight&#46; Despite the fact that this result could be due to the influence of malnutrition&#44; other studies would be necessary to truly determine which of the causes of hypoalbuminaemia is that which influences this finding most &#40;for example&#58; malnutrition&#44; inflammation&#44; liver disease&#44; etc&#46;&#41;&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">It should be noted that pathophysiological stress causes cortisol release &#40;not analysed in our study&#41; which reduces lymphocyte levels&#46; This could translate into an altered immune response which would result in erythropoietin resistance&#46; Furthermore&#44; lymphopenia could be caused by apoptosis of these cells in atherosclerotic lesions&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">22</span></a></p><p id="par0190" class="elsevierStylePara elsevierViewall">Individually&#44; platelets are involved in atherosclerosis&#44; in the activation of proinflammatory cytokines and&#44; through interaction with the endothelium&#44; they are probably also related to leucocyte chemotaxis and to arterial wall inflammation&#46;<a class="elsevierStyleCrossRefs" href="#bib0305"><span class="elsevierStyleSup">29&#44;30</span></a></p><p id="par0195" class="elsevierStylePara elsevierViewall">Neutrophils have demonstrated an important role in endothelial dysfunction&#44; atherogenesis and plaque destabilisation&#46; Activated neutrophils adhere to and penetrate the endothelial wall easily and are involved in the generation and release of free radicals&#44; hydrolytic enzymes and cytokines&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">31</span></a></p><p id="par0200" class="elsevierStylePara elsevierViewall">In our study&#44; the PLR has a significant correlation with the logERI similar to that presented by C-reactive protein and serum iron&#44; which is consistent given that the main causes of erythropoietin resistance are inflammation and iron deficiency&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">14</span></a></p><p id="par0205" class="elsevierStylePara elsevierViewall">Regarding the NLR&#44; the correlation with the logERI is significant but less than that found with the PLR&#46; Our results improve on aspects envisaged by other authors&#44; probably due to the fact that our study had a higher number of samples&#46;<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">32</span></a> However&#44; the reasons for this difference are still not known&#44; although it is suggested that the PLR would be higher because&#44; at the same time&#44; it is a better inflammatory marker than the NLR&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;25</span></a></p><p id="par0210" class="elsevierStylePara elsevierViewall">However&#44; given the low <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> value in both correlations&#44; the predictive power of these associations is low&#46; Nevertheless&#44; when combined with other variables of inflammation and iron kinetics&#44; the PLR did provide additional explanatory power&#46;</p><p id="par0215" class="elsevierStylePara elsevierViewall">The strengths of the study are its sample size&#44; which was much larger than that of previous studies&#44; and its multicentre nature&#46;<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">25</span></a></p><p id="par0220" class="elsevierStylePara elsevierViewall">The following can be mentioned within the limitations of the study&#58; the fact that the recruited population belongs to a single province in Spain and that&#44; although the results obtained demonstrate statistically significant associations&#44; they have a limited predictive power&#46;</p><p id="par0225" class="elsevierStylePara elsevierViewall">In view of the results obtained&#44; the mean values of the two ratios could be used as cut-off points for subsequent studies that deem the stratification of these parameters necessary&#46;</p><p id="par0230" class="elsevierStylePara elsevierViewall">In conclusion&#44; the high values of the NLR and the PLR were associated with higher ERI values in a population at high cardiovascular risk&#44; such as prevalent patients on haemodialysis&#46; Both ratios can be a good cost-effective marker for the monitoring of erythropoietin resistance&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Authors</span><p id="par0235" class="elsevierStylePara elsevierViewall">Study design&#58; F&#46;V&#46;A and T&#46;M&#46;V&#46;</p><p id="par0240" class="elsevierStylePara elsevierViewall">Performance of the study&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P and G&#46;A&#46;</p><p id="par0245" class="elsevierStylePara elsevierViewall">Data collection&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P and G&#46;A&#46;</p><p id="par0250" class="elsevierStylePara elsevierViewall">Data analysis&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0255" class="elsevierStylePara elsevierViewall">Interpretation of the results&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P and G&#46;A&#46;</p><p id="par0260" class="elsevierStylePara elsevierViewall">Drafting of the manuscript&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0265" class="elsevierStylePara elsevierViewall">Review of the manuscript content&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0270" class="elsevierStylePara elsevierViewall">Approval of the final version of the manuscript&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0275" class="elsevierStylePara elsevierViewall">F&#46;V&#46;A&#44; A&#46;S&#46;D&#46;P and G&#46;A accept responsibility for the integrity of the data analysis&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Conflicts of interest</span><p id="par0280" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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              "titulo" => "Baseline characteristics of the population"
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              "titulo" => "Relationship between the neutrophil-to-lymphocyte ratio &#40;NLR&#41; and the erythropoietin resistance index &#40;ERI&#41;"
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              "titulo" => "Relationship between the platelet-to-lymphocyte ratio &#40;PLR&#41; and the erythropoietin resistance index &#40;ERI&#41;"
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    "fechaRecibido" => "2018-06-26"
    "fechaAceptado" => "2019-09-07"
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          "clase" => "keyword"
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          "palabras" => array:4 [
            0 => "Chronic haemodialysis"
            1 => "Erythropoietin resistance"
            2 => "Platelet&#8211;lymphocyte ratio"
            3 => "Neutrophil&#8211;lymphocyte ratio"
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          "palabras" => array:4 [
            0 => "Hemodi&#225;lisis cr&#243;nica"
            1 => "Resistencia a la eritropoyetina"
            2 => "&#205;ndice plaqueta-linfocito"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The platelet-to-lymphocyte &#40;PLR&#41; and neutrophil-to-lymphocyte &#40;NLR&#41; ratios are emerging markers of inflammation&#46; Erythropoietin resistance is associated with increased morbidity and mortality in patients with chronic kidney disease and is influenced by inflammation&#44; among other factors&#46; Therefore&#44; it would be reasonable to expect a relationship between these markers and erythropoietin resistance&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Multicentre cross-sectional study&#46; The records of the haemodialysis sessions of 534 patients belonging to four of our dialysis centres were studied&#46; 137 patients were excluded&#44; so the final number of patients studied was 397&#46; NLR&#44; PLR and the erythropoietin resistance index &#40;ERI&#41; were calculated&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The ERI was divided into quartiles and compared with the mean NLR and PLR of the four groups&#44; with these differences being statistically significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;00058&#41;&#46; In the regression analysis&#44; the NLR value was able to predict ERI significantly &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;029&#41;&#46; The PLR value also predicted ERI significantly &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;103&#41;&#46; The ability of PLR to predict erythropoietin resistance was measured with the area under the ROC curve &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;681&#41; &#40;95&#37; CI&#44; 0&#46;541&#8211;0&#46;821&#41;&#46; A PLR cut-off point of 125&#46;5 would result in a sensitivity of 80&#46;95&#37; and 42&#46;82&#37; specificity&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Both PLR and NLR could be considered acceptable markers of erythropoietin resistance&#46; The PLR was a better predictor for the ERI than the NLR&#46;</p></span>"
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          0 => array:2 [
            "identificador" => "abst0005"
            "titulo" => "Introduction"
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            "titulo" => "Methods"
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          2 => array:2 [
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducci&#243;n</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Los &#237;ndices plaquetas-linfocito &#40;IPL&#41; y neutr&#243;filo-linfocito &#40;INL&#41; son marcadores emergentes de inflamaci&#243;n&#46; La resistencia a la eritropoyetina est&#225; relacionada con una mayor morbimortalidad en los pacientes con enfermedad renal cr&#243;nica y est&#225; influida&#44; entre otros factores&#44; por la inflamaci&#243;n&#46; Por lo tanto&#44; cabr&#237;a esperar una relaci&#243;n entre estos marcadores y la resistencia a la eritropoyetina&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudio transversal-multic&#233;ntrico&#46; Se estudiaron los registros de las sesiones de hemodi&#225;lisis de 534 pacientes pertenecientes a 4 de nuestros centros de di&#225;lisis&#46; Se excluy&#243; a 137 pacientes&#44; por lo que el n&#250;mero final de pacientes estudiado fue de 397&#46; Se calcul&#243; el INL&#44; el IPL y&#44; como medida de resistencia a la eritropoyetina&#44; se calcul&#243; el &#237;ndice de respuesta a la eritropoyetina &#40;IRE&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Se dividi&#243; el IRE en cuartiles y se compararon con las medias de INL e IPL de los 4 grupos&#44; siendo estas diferencias estad&#237;sticamente significativas &#40;p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;00058&#41;&#46; En los an&#225;lisis de regresi&#243;n&#44; el valor de INL pudo predecir el IRE de forma significativa &#40;p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41; &#40;R<span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;029&#41;&#46; Asimismo&#44; el valor de IPL tambi&#233;n predijo el IRE de forma significativa &#40;p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41; &#40;R<span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;103&#41;&#46; La capacidad del IPL para predecir resistencia a la eritropoyetina se midi&#243; con el &#225;rea bajo la curva ROC &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;681&#41; &#40;IC 95&#37;&#58; 0&#44;541-0&#44;821&#41;&#46; Un punto de corte de IPL de 125&#44;5 resultar&#237;a en un 80&#44;95&#37; de sensibilidad y 42&#44;82&#37; de especificidad&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Tanto el IPL como el INL podr&#237;an considerarse unos aceptables marcadores de resistencia a la eritropoyetina&#46; El IPL result&#243; ser un mejor predictor que el INL para el IRE&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Valga F&#44; Monz&#243;n T&#44; Henriquez F&#44; Santana-del-Pino A&#44; Ant&#243;n-P&#233;rez G&#46; &#205;ndices plaquetas-linfocito y neutr&#243;filo-linfocito como marcadores de resistencia a la eritropoyetina en pacientes en hemodi&#225;lisis cr&#243;nica&#58; estudio transversal-multic&#233;ntrico&#46; Nefrologia&#46; 2020&#59;40&#58;320&#8211;327&#46;</p>"
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&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\ttable-entry\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</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 ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Aetiology&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\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>Not related&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">108 &#40;27&#46;20&#41;&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"><span class="elsevierStyleHsp" style=""></span>Nephroangiosclerosis&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">44 &#40;11&#46;08&#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"><span class="elsevierStyleHsp" style=""></span>Diabetic nephropathy&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">132 &#40;33&#46;25&#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"><span class="elsevierStyleHsp" style=""></span>Chronic glomerulonephritis&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">38 &#40;9&#46;57&#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"><span class="elsevierStyleHsp" style=""></span>Hepatorenal polycystic disease&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 &#40;6&#46;05&#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"><span class="elsevierStyleHsp" style=""></span>Systemic diseases&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">9 &#40;2&#46;27&#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"><span class="elsevierStyleHsp" style=""></span>Tubulointerstitial nephritis&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">27 &#40;6&#46;80&#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"><span class="elsevierStyleHsp" style=""></span>Other&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">15 &#40;3&#46;78&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Baseline characteristics of the population&#46;</p>"
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        "tabla" => array:1 [
          "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="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&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="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 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="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 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="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 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="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\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">Female gender &#40;&#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">24 &#40;32&#46;75&#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">38 &#40;24&#46;24&#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">33 &#40;38&#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">35 &#40;33&#46;33&#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">0&#46;1851&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">Age &#40;years&#41;&#40;median q25&#8211;q75&#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">68 &#40;59&#59;74&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">70 &#40;60&#59;78&#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;55&#59;73&#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">67 &#40;58&#59;75&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;0855&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">Active smokers &#40;&#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">18 &#40;18&#46;18&#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">11 &#40;11&#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">16 &#40;16&#46;16&#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">20 &#40;20&#46;2&#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">0&#46;3328&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">Dry weight &#40;kg&#41;&#40;median q25&#8211;q75&#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">78 &#40;68&#46;75&#59;90&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">75 &#40;61&#46;88&#59;84&#46;62&#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">71 &#40;63&#46;5&#59;81&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">69&#46;5 &#40;60&#46;25&#59;79&#46;25&#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">0&#46;0003&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">Haemoglobin &#40;g&#47;dl&#41;&#40;median q25&#8211;q75&#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">11&#46;8 &#40;11&#46;4&#59;12&#46;2&#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">11&#46;4 &#40;10&#46;9&#59;12&#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">11&#46;4 &#40;10&#46;75&#59;12&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
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                  \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">&#62;0&#46;0001&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Neutrophils &#40;10<span class="elsevierStyleSup">3</span>&#47;&#956;l&#41;&#40;median q25&#8211;q75&#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;3 &#40;3&#46;5&#59;5&#46;25&#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;17 &#40;3&#46;44&#59;5&#46;42&#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;21 &#40;3&#46;35&#59;5&#46;05&#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;41 &#40;3&#46;32&#59;5&#46;32&#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
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                  \t\t\t\t">0&#46;9066&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
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                  \t\t\t\t">Platelets &#40;10<span class="elsevierStyleSup">3</span>&#47;&#956;l&#41;&#40;median q25&#8211;q75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">173 &#40;145&#46;5&#59;211&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">181 &#40;154&#59;225&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">188 &#40;153&#59;239&#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\ttop\n
                  \t\t\t\t">210 &#40;151&#59;243&#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">0&#46;0618&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">Lymphocytes &#40;10<span class="elsevierStyleSup">3</span>&#47;&#956;l&#41;&#40;median q25&#8211;q75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">1&#46;5 &#40;1&#46;11&#59;1&#46;87&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">1&#46;62 &#40;1&#46;18&#59;1&#46;9&#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</td><td class="td" title="\n
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                  \t\t\t\t">1&#46;2 &#40;0&#46;9&#59;1&#46;56&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;0001&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">TSI &#40;&#37;&#41;&#40;median q25&#8211;q75&#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">24&#46;14 &#40;19&#46;67&#59;29&#46;37&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">23&#46;22 &#40;19&#46;31&#59;31&#46;54&#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">23&#46;61 &#40;18&#46;63&#59;29&#46;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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">21&#46;52 &#40;15&#46;65&#8211;29&#46;01&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;452&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">Serum iron &#40;&#956;g&#47;dl&#41;&#40;median q25&#8211;q75&#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">59&#46;04 &#40;48&#59;72&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">53 &#40;41&#46;5&#59;66&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">49 &#40;38&#46;75&#59;62&#46;71&#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">43&#46;5 &#40;32&#59;60&#46;08&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;0001&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">Ferritin &#40;ng&#47;ml&#41;&#40;median q25&#8211;q75&#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">276&#46;38 &#40;179&#46;62&#59;426&#46;03&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">333&#46;8 &#40;220&#46;36&#59;461&#46;25&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">322&#46;33 &#40;224&#46;38&#59;458&#46;03&#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">314&#46;34 &#40;196&#46;55&#8211;431&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;168&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 ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">CRP &#40;mg&#47;l&#41;&#40;median q25&#8211;q75&#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">3&#46;65 &#40;1&#46;42&#59;7&#46;65&#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">3&#46;8 &#40;1&#46;5&#59;7&#46;9&#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">3&#46;74 &#40;1&#46;69&#59;7&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">6&#46;52 &#40;2&#46;84&#59;23&#46;31&#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">0&#46;0001&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 ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Albumin &#40;g&#47;dl&#41;&#40;median q25&#8211;q75&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;023&nbsp;\t\t\t\t\t\t\n
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                  """
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              "imagenFichero" => array:1 [
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        "descripcion" => array:1 [
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      7 => array:8 [
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        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
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          "leyenda" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">The values of the ratios do not have units&#46;</p>"
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            0 => array:2 [
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">128 &#40;&#177;49&#46;10&#41;&nbsp;\t\t\t\t\t\t\n
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                    0 => array:2 [
                      "titulo" => "Heart failure in patients with kidney disease"
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                        0 => array:2 [
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                          "autores" => array:2 [
                            0 => "C&#46; Tuegel"
                            1 => "N&#46; Bansal"
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                    0 => array:2 [
                      "doi" => "10.1136/heartjnl-2016-310794"
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                        "tituloSerie" => "Heart"
                        "fecha" => "2017"
                        "volumen" => "103"
                        "paginaInicial" => "1848"
                        "paginaFinal" => "1853"
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                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28716974"
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                          "estado" => "S300"
                          "issn" => "00223476"
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                      "titulo" => "Health-related quality of life of children with pre-dialysis chronic kidney disease"
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                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "H&#46;S&#46; Baek"
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                            2 => "H&#46;J&#46; Choi"
                            3 => "H&#46;I&#46; Cheong"
                            4 => "I&#46;S&#46; Ha"
                            5 => "K&#46;H&#46; Han"
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                      ]
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                    0 => array:1 [
                      "Revista" => array:5 [
                        "tituloSerie" => "Pediatr&#46; Nephrol&#46;"
                        "fecha" => "2017"
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Original article
Platelet-to-lymphocyte and neutrophil-to-lymphocyte ratios as markers of erythropoietin resistance in chronic haemodialysis patients: A multicentre cross-sectional study
Índices plaquetas-linfocito y neutrófilo-linfocito como marcadores de resistencia a la eritropoyetina en pacientes en hemodiálisis crónica: estudio transversal-multicéntrico
Francisco Valgaa,b,
Corresponding author
fvalga@hotmail.com

Corresponding author.
, Tania Monzóna,b, Fernando Henriqueza,b,c,d, Angelo Santana-del-Pinoe, Gloria Antón-Péreza,b,c,d
a Centro de diálisis Avericum-Negrín, Las Palmas de Gran Canaria, Islas Canarias, Spain
b Centro de diálisis Avericum-Guía, Santa María de Guía, Islas Canarias, Spain
c Centro de diálisis Avericum-Telde, Las Palmas de Gran Canaria, Islas Canarias, Spain
d Centro de diálisis Avericum-Lanzarote, Arrecife, Islas Canarias, Spain
e Departamento de Matemática, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Islas Canarias, Spain
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a significant percentage of them &#40;from 5&#37; to 10&#37;&#44; according to some studies&#41;<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">4&#44;10&#44;11</span></a> have higher requirements of ESAs due to multiple causes&#58; iron deficiency&#44; haemolysis&#44; neoplasia&#44; infections&#44; inflammation&#44; vitamin deficiencies&#44; toxins and inadequate dialysis&#46;<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">10&#44;11</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">This clinical condition&#44; as a whole&#44; is called &#8220;erythropoietin resistance&#8221;&#44; which is linked to a worse prognosis in patients on haemodialysis&#46;<a class="elsevierStyleCrossRefs" href="#bib0220"><span class="elsevierStyleSup">12&#44;13</span></a> It is worth highlighting that it is a clinical concept which is difficult to define&#46; An arbitrary&#44; but data-based&#44; definition is that provided by the European guidelines from 1999&#58; &#8220;Failure to attain the target haemoglobin concentration while receiving more than 300<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week or 20&#44;000<span class="elsevierStyleHsp" style=""></span>IU&#47;week of erythropoietin&#8221; also specifying &#8220;or a continued need for such dosage to maintain the target haemoglobin concentration&#8221;&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">14</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Furthermore&#44; the usefulness of the erythropoietin resistance index &#40;ERI&#41; as a good marker of resistance to erythropoietin and a factor associated with occurrence of adverse effects in chronic haemodialysis has been reported&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;15&#8211;18</span></a> Some groups have established that an erythropoietin resistance index greater than 9<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week&#47;g&#47;dl could be considered as resistant&#46;<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">19&#44;20</span></a> In one study it was demonstrated that ERI values above 15<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week&#47;g&#47;dl had greater mortality&#46;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">15</span></a> Likewise&#44; other authors have suggested that erythropoietin requirements greater than 109<span class="elsevierStyleHsp" style=""></span>IU&#47;kg&#47;week&#44; without taking into account the haemoglobin values&#44; are a warning sign of possible erythropoietin resistance&#46;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">21</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Moreover&#44; the platelet-to-lymphocyte ratio &#40;PLR&#41; and neutrophil-to-lymphocyte ratio &#40;NLR&#41; are emerging biological markers of inflammation and endothelial dysfunction&#44;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;22</span></a> initially applied to heart disease patients<a class="elsevierStyleCrossRefs" href="#bib0270"><span class="elsevierStyleSup">22&#8211;24</span></a> and&#44; more recently&#44; to patients with end-stage chronic kidney disease&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;25&#44;26</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">Currently&#44; 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and medical conditions which may have influenced the absolute counts of platelets&#44; lymphocytes and haemoglobin&#58; admission to hospital for an infection&#44; cancer or haematological causes in the previous three months &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>24&#41;&#46; Transfusion in the last three months &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4&#41;&#44; active onco-haematological diseases &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>13&#41; and patients undergoing steroid treatment &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>26&#41; were also part of the exclusion criteria&#46; Some of the patients fulfilled more than one exclusion criterion &#40;total number of patients excluded&#58; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>137&#41;&#46; Therefore&#44; after applying the criteria&#44; the study sample was 397 patients&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Erythropoietin resistance was defined as those patients who had erythropoietin doses of greater than 20&#44;000<span class="elsevierStyleHsp" style=""></span>IU and haemoglobin values of less than 11<span class="elsevierStyleHsp" style=""></span>g&#47;dl&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">14</span></a></p><p id="par0060" class="elsevierStylePara elsevierViewall">For the PLR calculation&#44; the ratio between the absolute platelet count and the absolute lymphocyte count in the blood count was obtained&#46; In order to obtain the NLR&#44; the ratio between the absolute neutrophil count and the absolute lymphocyte count in the blood count was calculated&#46; And&#44; finally&#44; the ERI was obtained by calculating the weekly dose of erythropoietin &#40;IU&#41; divided by the dry weight &#40;kg&#41; and divided&#44; in turn&#44; by the serum haemoglobin levels &#40;g&#47;dl&#41;&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;15&#44;16</span></a></p><p id="par0065" class="elsevierStylePara elsevierViewall">Other variables analysed were&#58; albumin&#44; serum iron&#44; transferrin saturation index &#40;TSI&#41; and C-reactive protein &#40;CRP&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">The R program version 3&#46;3&#46;2 &#40;2017&#41; was used for the statistical analysis &#40;R Foundation for Statistical Computing&#44; Vienna&#44; Austria&#46; URL <a href="http://www.r-projet.org/"><span class="elsevierStyleUnderline">http&#58;&#47;&#47;www&#46;R-projet&#46;org&#47;</span></a>&#41;&#46; The results were considered statistically significant if the <span class="elsevierStyleItalic">p</span>-value was less than 0&#46;05&#46; The continuous variables were summarised as mean<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>standard deviation &#40;normal variables&#41; or median and quartiles &#40;non-normal variables&#41;&#46; The categorical variables were summarised as percentages&#46; The normality of the variables was analysed using the Shapiro&#8211;Wilk test&#46; The Pearson coefficient was used for correlations&#46; To evaluate whether there were significant differences according to the ERI quartile&#44; the Kruskal&#8211;Wallis test was used for quantitative variables&#44; and the chi-square test for categorical variables&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">When significant differences were detected between ERI quartiles&#44; the respective post hoc tests were carried out using the Tukey procedure&#44; when the transformation of the variable to the logarithmic scale enabled normality and homoscedasticity to be achieved&#44; or otherwise using the Dunn&#39;s test&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">To evaluate the predictive ability of the PLR and the NLR on the ERI&#44; regression models were adjusted in which the log &#40;ERI&#41; was used as a response variable&#46; The models were also adjusted for the age&#44; gender and weight of the individual&#46; In the case of the NLR&#44; to evaluate the particular effect of the neutrophil and lymphocyte counts &#40;which are part of the NLR definition&#41;&#44; these variables were introduced into the regression model and a step-by-step method was applied to select the set of variables with the best predictive ability&#46; A similar procedure was carried out with the PLR&#44; introducing in this case the platelets and lymphocytes as additional variables to then apply the step-by-step procedure&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Likewise&#44; in order to carry out an analysis of the ability of the PLR to diagnose erythropoietin resistance&#44; a logistic regression model&#44; adjusted for age and gender&#44; was estimated&#46; A step-by-step method was also applied to simplify the model and to eliminate non-explanatory variables&#46; The calculation of the ROC curve was carried out when only the PLR was used as the diagnostic criterion to predict erythropoietin resistance&#46;</p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Results</span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Baseline characteristics of the population</span><p id="par0090" class="elsevierStylePara elsevierViewall">The baseline characteristics of the patients included are described in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46; A stratification of the ERI in quartiles &#40;Q1<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;59&#8211;4&#46;08&#44; Q2<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4&#46;08&#8211;7&#46;04&#44; Q3<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>7&#46;04&#8211;12&#46;55&#44; Q4<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>12&#46;55&#8211;80&#46;65&#41; was performed and the values of the different variables among the thus defined groups were compared &#40;<a class="elsevierStyleCrossRefs" href="#tbl0010">Tables 2 and 3</a>&#41;&#46; The dry weight&#44; lymphocytes&#44; haemoglobin&#44; concentrations of serum iron&#44; albumin and C-reactive protein showed significant differences among the ERI quartiles&#46; For all these variables &#40;except haemoglobin&#41;&#44; the post hoc Tukey tests &#40;with the variables transformed beforehand to the logarithmic scale&#41; showed that the first&#44; second and third quartiles did not display significant differences among them&#44; and that the significant differences occurred with regard to the fourth quartile&#46; In the case of haemoglobin&#44; the Dunn&#39;s post hoc test showed that its value is significantly higher in the first quartile of ERI&#44; did not show significant differences between the second and third quartiles and showed a significantly lower value in the fourth quartile&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">The correlation between the different study variables and the log value &#40;ERI&#41; was calculated &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46; The correlation is significant for all variables apart from age and neutrophils&#46;</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">Likewise&#44; correlations were carried out between different inflammation and iron kinetics parameters with the log &#40;ERI&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Relationship between the neutrophil-to-lymphocyte ratio &#40;NLR&#41; and the erythropoietin resistance index &#40;ERI&#41;</span><p id="par0105" class="elsevierStylePara elsevierViewall">Given the asymmetry of the NLR variable for each ERI quartile&#44; the comparison of the NLR values between the four ERI quartiles was performed initially using the non-parametric Kruskal&#8211;Wallis test&#58; this test showed significant differences in the distribution of the ERI for the different ERI quartiles &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;00058&#41;&#46; To determine the quartiles among which these differences occur&#44; ANOVA and a post hoc test were used&#46; For this&#44; the asymmetry was corrected&#44; transforming the NLR values to a logarithmic scale&#46; The analysis of variance of the log &#40;NLR&#41; confirmed that there are significant differences in the log &#40;NLR&#41; values according to the ERI quartiles &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;0004296&#41;&#46; The Shapiro&#8211;Wilk test did not find evidence of lack of normality in the residuals &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;3808&#41; and Levene&#39;s test did not detect heteroscedasticity among groups &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;4492&#41;&#44; which validates the performance of ANOVA &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; The Tukey multiple comparison test was used to determine among which quartiles the NLR differences were found&#58; the log values &#40;NLR&#41; for the fourth ERI quartile differ significantly from the values in the first and second quartile&#46; The log value &#40;NLR&#41; in the third ERI quartile does not differ significantly from the others&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">To evaluate the predictive ability of the NLR on the log &#40;ERI&#41;&#44; a regression model was adjusted&#59; although the effect of the NLR on the log &#40;ERI&#41; turned out to be significant &#40;standardised beta<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;173&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; the <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> value turned out to be very low &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;029&#41;&#44; which indicates that&#44; although the ERI value tends to grow with the NLR&#44; the predictive ability of the latter variable is limited&#46; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows the overall regression line adjusted for all the data&#44; in which the growing trend of the ERI with the NLR is observed and in which the presence of considerable variability can be seen&#46; If we analyse this graph carefully&#44; we can observe that&#44; in particular&#44; the majority of the subjects &#40;90&#37;&#41; have NLR values lower than 6&#59; within this group&#44; only 3&#46;9&#37; are resistant to erythropoietin&#59; subjects with NLR &#62;6 only make up 10&#37; of the total&#59; but within this group there are proportionally more subjects with erythropoietin resistance &#40;18&#46;9&#37;&#41;&#46; In other words&#44; the risk of erythropoietin resistance is higher among subjects with high NLR values&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0115" class="elsevierStylePara elsevierViewall">This motivates adjusting a logistic regression model to predict the erythropoietin resistance depending on the NLR&#46; With this model&#44; we obtain that the OR of suffering from erythropoietin resistance is 1&#46;32 &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#59; 95&#37; CI&#58; 1&#46;118&#8211;1&#46;544&#41; for each unit of increase in the NLR&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Relationship between the platelet-to-lymphocyte ratio &#40;PLR&#41; and the erythropoietin resistance index &#40;ERI&#41;</span><p id="par0120" class="elsevierStylePara elsevierViewall">As with the NLR&#44; the asymmetry of distributions of the PLR for each ERI quartile led to the comparisons of the PLR according to ERI quartiles being carried out using the Kruskal&#8211;Wallis test&#44; with the differences turning out to be statistically significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;00001&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><p id="par0125" class="elsevierStylePara elsevierViewall">Similarly&#44; to decide in which quartiles these differences occur&#44; an ANOVA of the log &#40;PLR&#41; was carried out&#44; with the differences being significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#46; The normality of the log &#40;PLR&#41; was analysed using the Shapiro&#8211;Wilk test &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;65&#41; and homoscedasticity with Levene&#39;s test &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;737&#41;&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">The Tukey test indicated that the differences were in the fourth ERI quartile compared to the rest&#46; No significant differences in the distribution of the log &#40;PLR&#41; were detected in the other three quartiles&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">In the regression adjustment to predict the log &#40;ERI&#41; based on the PLR&#44; a significant positive slope &#40;standardised beta<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;32&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; was obtained&#44; although&#44; once again&#44; the <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> value turned out to be low &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;103&#41; although higher than that obtained with the NLR&#44; which means that the predictive ability of the PLR is better than that of the NLR &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>&#41;&#46;</p><elsevierMultimedia ident="fig0020"></elsevierMultimedia><p id="par0140" class="elsevierStylePara elsevierViewall">As occurred with the NLR&#44; it is observed that the log &#40;ERI&#41; increases with the PLR value&#59; as in that case 90&#37; of the PLR values are below 233&#59; in this group&#44; some 3&#46;9&#37; of patients are resistant to erythropoietin&#59; however&#44; when the PLR is above 233&#44; 17&#46;5&#37; of the subjects are resistant to erythropoietin&#59; therefore&#44; the risk of being resistant to erythropoietin increases with the PLR value&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">To assess this risk&#44; the logistic regression model indicates that an increase of one unit in the PLR translates into an OR of 1&#46;011 &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#59; 95&#37; CI&#58; 1&#46;005&#8211;1&#46;015&#41; of presenting erythropoietin resistance&#46; An additional calculation makes it possible to estimate that the OR of suffering from erythropoietin resistance doubles for each increase of 67 units in the PLR value&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">Furthermore&#44; a multivariate regression analysis was carried out&#44; in which variables such as the TSI&#44; serum iron&#44; C-reactive protein and the PLR were included&#46; The correlation of the PLR with logERI continued to be significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41;&#44; with the total predictive capacity of the model&#44; measured in terms of <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span>&#44; of 17&#46;26&#37;&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">To analyse the capacity of the PLR to predict erythropoietin resistance&#44; the area under the ROC curve was measured &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;681&#41; &#40;95&#37; CI&#58; 0&#46;541&#8211;0&#46;821&#41;&#46; A PLR cut-off point of 125&#46;5 would result in 80&#46;95&#37; sensitivity and 42&#46;82&#37; specificity &#40;<a class="elsevierStyleCrossRef" href="#fig0025">Fig&#46; 5</a>&#41;&#46;</p><elsevierMultimedia ident="fig0025"></elsevierMultimedia></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Discussion</span><p id="par0160" class="elsevierStylePara elsevierViewall">Cardiovascular risk in haemodialysis patients is well known&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">1</span></a> From the pathophysiological point of view&#44; inflammation plays a very important role&#46; Historically&#44; multiple parameters have been listed to measure this&#44; including C-reactive protein&#44; serum albumin and B-type natriuretic peptide&#46; The NLR and the PLR have emerged in recent years as markers of inflammation and endothelial damage in different types of patients&#46; Given the fact that they are easy to obtain&#44; inexpensive and routinely extracted in patients on haemodialysis&#44; they are a very interesting analytical parameter in this group of patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">6&#44;25&#44;26</span></a></p><p id="par0165" class="elsevierStylePara elsevierViewall">Likewise&#44; the management of anaemia with erythropoiesis-stimulating agents and intravenous iron have been set up as the basis for the treatment of patients on haemodialysis for many years&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">5&#44;10</span></a></p><p id="par0170" class="elsevierStylePara elsevierViewall">The ERI is a good marker of erythropoietin resistance and is related to both intercurrent processes &#40;neoplasia&#44; infections&#44; etc&#46;&#41; and to a worse prognosis in patients on haemodialysis&#44; which is why their detection and follow-up is very important&#46;<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">10&#44;11&#44;15&#44;16</span></a></p><p id="par0175" class="elsevierStylePara elsevierViewall">The objective of our study was to determine whether resistance to erythropoietin is related to the NLR and the PLR&#46; It is worth pointing out that patients who were admitted to hospital for infection&#44; cancer or haematological causes&#59; those who had received a blood transfusion in the last three months&#59; those who presented active onco-haematological comorbidities and those who were receiving steroid treatment were ruled out from the study&#46; All of these are factors which could&#44; a priori&#44; alter the count of these blood cells&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">Unlike a previous study&#44; which only found a significant association of the ERI with the PLR &#40;and not with the NLR&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">11</span></a> our study found an association with both parameters&#46; An explanation could be that the low number of lymphocytes&#44; the common parameter of both ratios&#44; could be the most important factor&#46; In isolation&#44; the reduction in absolute number of lymphocytes has been used as a marker of ischaemic heart disease&#46;<a class="elsevierStyleCrossRefs" href="#bib0295"><span class="elsevierStyleSup">27&#44;28</span></a> One factor to bear in mind&#44; found in our study&#44; is that the fourth quartile had the lowest levels of albumin and dry weight&#46; Despite the fact that this result could be due to the influence of malnutrition&#44; other studies would be necessary to truly determine which of the causes of hypoalbuminaemia is that which influences this finding most &#40;for example&#58; malnutrition&#44; inflammation&#44; liver disease&#44; etc&#46;&#41;&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">It should be noted that pathophysiological stress causes cortisol release &#40;not analysed in our study&#41; which reduces lymphocyte levels&#46; This could translate into an altered immune response which would result in erythropoietin resistance&#46; Furthermore&#44; lymphopenia could be caused by apoptosis of these cells in atherosclerotic lesions&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">22</span></a></p><p id="par0190" class="elsevierStylePara elsevierViewall">Individually&#44; platelets are involved in atherosclerosis&#44; in the activation of proinflammatory cytokines and&#44; through interaction with the endothelium&#44; they are probably also related to leucocyte chemotaxis and to arterial wall inflammation&#46;<a class="elsevierStyleCrossRefs" href="#bib0305"><span class="elsevierStyleSup">29&#44;30</span></a></p><p id="par0195" class="elsevierStylePara elsevierViewall">Neutrophils have demonstrated an important role in endothelial dysfunction&#44; atherogenesis and plaque destabilisation&#46; Activated neutrophils adhere to and penetrate the endothelial wall easily and are involved in the generation and release of free radicals&#44; hydrolytic enzymes and cytokines&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">31</span></a></p><p id="par0200" class="elsevierStylePara elsevierViewall">In our study&#44; the PLR has a significant correlation with the logERI similar to that presented by C-reactive protein and serum iron&#44; which is consistent given that the main causes of erythropoietin resistance are inflammation and iron deficiency&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">14</span></a></p><p id="par0205" class="elsevierStylePara elsevierViewall">Regarding the NLR&#44; the correlation with the logERI is significant but less than that found with the PLR&#46; Our results improve on aspects envisaged by other authors&#44; probably due to the fact that our study had a higher number of samples&#46;<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">32</span></a> However&#44; the reasons for this difference are still not known&#44; although it is suggested that the PLR would be higher because&#44; at the same time&#44; it is a better inflammatory marker than the NLR&#46;<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">11&#44;25</span></a></p><p id="par0210" class="elsevierStylePara elsevierViewall">However&#44; given the low <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> value in both correlations&#44; the predictive power of these associations is low&#46; Nevertheless&#44; when combined with other variables of inflammation and iron kinetics&#44; the PLR did provide additional explanatory power&#46;</p><p id="par0215" class="elsevierStylePara elsevierViewall">The strengths of the study are its sample size&#44; which was much larger than that of previous studies&#44; and its multicentre nature&#46;<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">25</span></a></p><p id="par0220" class="elsevierStylePara elsevierViewall">The following can be mentioned within the limitations of the study&#58; the fact that the recruited population belongs to a single province in Spain and that&#44; although the results obtained demonstrate statistically significant associations&#44; they have a limited predictive power&#46;</p><p id="par0225" class="elsevierStylePara elsevierViewall">In view of the results obtained&#44; the mean values of the two ratios could be used as cut-off points for subsequent studies that deem the stratification of these parameters necessary&#46;</p><p id="par0230" class="elsevierStylePara elsevierViewall">In conclusion&#44; the high values of the NLR and the PLR were associated with higher ERI values in a population at high cardiovascular risk&#44; such as prevalent patients on haemodialysis&#46; Both ratios can be a good cost-effective marker for the monitoring of erythropoietin resistance&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Authors</span><p id="par0235" class="elsevierStylePara elsevierViewall">Study design&#58; F&#46;V&#46;A and T&#46;M&#46;V&#46;</p><p id="par0240" class="elsevierStylePara elsevierViewall">Performance of the study&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P and G&#46;A&#46;</p><p id="par0245" class="elsevierStylePara elsevierViewall">Data collection&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P and G&#46;A&#46;</p><p id="par0250" class="elsevierStylePara elsevierViewall">Data analysis&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0255" class="elsevierStylePara elsevierViewall">Interpretation of the results&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P and G&#46;A&#46;</p><p id="par0260" class="elsevierStylePara elsevierViewall">Drafting of the manuscript&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0265" class="elsevierStylePara elsevierViewall">Review of the manuscript content&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0270" class="elsevierStylePara elsevierViewall">Approval of the final version of the manuscript&#58; F&#46;V&#46;A&#44; T&#46;M&#46;V&#44; F&#46;H&#46;P&#44; A&#46;S&#46;D&#46;P and G&#46;A&#46;</p><p id="par0275" class="elsevierStylePara elsevierViewall">F&#46;V&#46;A&#44; A&#46;S&#46;D&#46;P and G&#46;A accept responsibility for the integrity of the data analysis&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Conflicts of interest</span><p id="par0280" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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              "titulo" => "Baseline characteristics of the population"
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              "titulo" => "Relationship between the neutrophil-to-lymphocyte ratio &#40;NLR&#41; and the erythropoietin resistance index &#40;ERI&#41;"
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              "titulo" => "Relationship between the platelet-to-lymphocyte ratio &#40;PLR&#41; and the erythropoietin resistance index &#40;ERI&#41;"
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    "fechaRecibido" => "2018-06-26"
    "fechaAceptado" => "2019-09-07"
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            0 => "Chronic haemodialysis"
            1 => "Erythropoietin resistance"
            2 => "Platelet&#8211;lymphocyte ratio"
            3 => "Neutrophil&#8211;lymphocyte ratio"
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          "palabras" => array:4 [
            0 => "Hemodi&#225;lisis cr&#243;nica"
            1 => "Resistencia a la eritropoyetina"
            2 => "&#205;ndice plaqueta-linfocito"
            3 => "&#205;ndice neutr&#243;filo-linfocito"
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      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The platelet-to-lymphocyte &#40;PLR&#41; and neutrophil-to-lymphocyte &#40;NLR&#41; ratios are emerging markers of inflammation&#46; Erythropoietin resistance is associated with increased morbidity and mortality in patients with chronic kidney disease and is influenced by inflammation&#44; among other factors&#46; Therefore&#44; it would be reasonable to expect a relationship between these markers and erythropoietin resistance&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Multicentre cross-sectional study&#46; The records of the haemodialysis sessions of 534 patients belonging to four of our dialysis centres were studied&#46; 137 patients were excluded&#44; so the final number of patients studied was 397&#46; NLR&#44; PLR and the erythropoietin resistance index &#40;ERI&#41; were calculated&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The ERI was divided into quartiles and compared with the mean NLR and PLR of the four groups&#44; with these differences being statistically significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;00058&#41;&#46; In the regression analysis&#44; the NLR value was able to predict ERI significantly &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;029&#41;&#46; The PLR value also predicted ERI significantly &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;0001&#41; &#40;<span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;103&#41;&#46; The ability of PLR to predict erythropoietin resistance was measured with the area under the ROC curve &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;681&#41; &#40;95&#37; CI&#44; 0&#46;541&#8211;0&#46;821&#41;&#46; A PLR cut-off point of 125&#46;5 would result in a sensitivity of 80&#46;95&#37; and 42&#46;82&#37; specificity&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Both PLR and NLR could be considered acceptable markers of erythropoietin resistance&#46; The PLR was a better predictor for the ERI than the NLR&#46;</p></span>"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducci&#243;n</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Los &#237;ndices plaquetas-linfocito &#40;IPL&#41; y neutr&#243;filo-linfocito &#40;INL&#41; son marcadores emergentes de inflamaci&#243;n&#46; La resistencia a la eritropoyetina est&#225; relacionada con una mayor morbimortalidad en los pacientes con enfermedad renal cr&#243;nica y est&#225; influida&#44; entre otros factores&#44; por la inflamaci&#243;n&#46; Por lo tanto&#44; cabr&#237;a esperar una relaci&#243;n entre estos marcadores y la resistencia a la eritropoyetina&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudio transversal-multic&#233;ntrico&#46; Se estudiaron los registros de las sesiones de hemodi&#225;lisis de 534 pacientes pertenecientes a 4 de nuestros centros de di&#225;lisis&#46; Se excluy&#243; a 137 pacientes&#44; por lo que el n&#250;mero final de pacientes estudiado fue de 397&#46; Se calcul&#243; el INL&#44; el IPL y&#44; como medida de resistencia a la eritropoyetina&#44; se calcul&#243; el &#237;ndice de respuesta a la eritropoyetina &#40;IRE&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Se dividi&#243; el IRE en cuartiles y se compararon con las medias de INL e IPL de los 4 grupos&#44; siendo estas diferencias estad&#237;sticamente significativas &#40;p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;00058&#41;&#46; En los an&#225;lisis de regresi&#243;n&#44; el valor de INL pudo predecir el IRE de forma significativa &#40;p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41; &#40;R<span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;029&#41;&#46; Asimismo&#44; el valor de IPL tambi&#233;n predijo el IRE de forma significativa &#40;p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;0001&#41; &#40;R<span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;103&#41;&#46; La capacidad del IPL para predecir resistencia a la eritropoyetina se midi&#243; con el &#225;rea bajo la curva ROC &#40;AUC<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#44;681&#41; &#40;IC 95&#37;&#58; 0&#44;541-0&#44;821&#41;&#46; Un punto de corte de IPL de 125&#44;5 resultar&#237;a en un 80&#44;95&#37; de sensibilidad y 42&#44;82&#37; de especificidad&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Tanto el IPL como el INL podr&#237;an considerarse unos aceptables marcadores de resistencia a la eritropoyetina&#46; El IPL result&#243; ser un mejor predictor que el INL para el IRE&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Valga F&#44; Monz&#243;n T&#44; Henriquez F&#44; Santana-del-Pino A&#44; Ant&#243;n-P&#233;rez G&#46; &#205;ndices plaquetas-linfocito y neutr&#243;filo-linfocito como marcadores de resistencia a la eritropoyetina en pacientes en hemodi&#225;lisis cr&#243;nica&#58; estudio transversal-multic&#233;ntrico&#46; Nefrologia&#46; 2020&#59;40&#58;320&#8211;327&#46;</p>"
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Systemic diseases&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Tubulointerstitial nephritis&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Other&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">15 &#40;3&#46;78&#41;&nbsp;\t\t\t\t\t\t\n
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                  """
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Female gender &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">24 &#40;32&#46;75&#37;&#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">33 &#40;38&#37;&#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">35 &#40;33&#46;33&#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
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                  \t\t\t\t">0&#46;1851&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
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                  \t\t\t\t">Age &#40;years&#41;&#40;median q25&#8211;q75&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">68 &#40;59&#59;74&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">70 &#40;60&#59;78&#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;55&#59;73&#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">67 &#40;58&#59;75&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;0855&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">Active smokers &#40;&#37;&#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
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">11 &#40;11&#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
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">16 &#40;16&#46;16&#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">20 &#40;20&#46;2&#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">0&#46;3328&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">Dry weight &#40;kg&#41;&#40;median q25&#8211;q75&#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">78 &#40;68&#46;75&#59;90&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">75 &#40;61&#46;88&#59;84&#46;62&#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">71 &#40;63&#46;5&#59;81&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">69&#46;5 &#40;60&#46;25&#59;79&#46;25&#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">0&#46;0003&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">Haemoglobin &#40;g&#47;dl&#41;&#40;median q25&#8211;q75&#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">11&#46;8 &#40;11&#46;4&#59;12&#46;2&#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">11&#46;4 &#40;10&#46;9&#59;12&#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
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                  \t\t\t\t">11&#46;4 &#40;10&#46;75&#59;12&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">10&#46;9 &#40;10&#46;1&#59;11&#46;55&#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">&#62;0&#46;0001&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">Neutrophils &#40;10<span class="elsevierStyleSup">3</span>&#47;&#956;l&#41;&#40;median q25&#8211;q75&#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
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                  \t\t\t\t">4&#46;3 &#40;3&#46;5&#59;5&#46;25&#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;17 &#40;3&#46;44&#59;5&#46;42&#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
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                  \t\t\t\t">4&#46;21 &#40;3&#46;35&#59;5&#46;05&#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">4&#46;41 &#40;3&#46;32&#59;5&#46;32&#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
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                  \t\t\t\t">0&#46;9066&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">Platelets &#40;10<span class="elsevierStyleSup">3</span>&#47;&#956;l&#41;&#40;median q25&#8211;q75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">173 &#40;145&#46;5&#59;211&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">181 &#40;154&#59;225&#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">188 &#40;153&#59;239&#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">210 &#40;151&#59;243&#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">0&#46;0618&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
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                  \t\t\t\t">Lymphocytes &#40;10<span class="elsevierStyleSup">3</span>&#47;&#956;l&#41;&#40;median q25&#8211;q75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;5 &#40;1&#46;11&#59;1&#46;87&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">1&#46;62 &#40;1&#46;18&#59;1&#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">1&#46;37 &#40;1&#46;04&#59;1&#46;73&#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">1&#46;2 &#40;0&#46;9&#59;1&#46;56&#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">&#60;0&#46;0001&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">TSI &#40;&#37;&#41;&#40;median q25&#8211;q75&#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;14 &#40;19&#46;67&#59;29&#46;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">23&#46;22 &#40;19&#46;31&#59;31&#46;54&#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">23&#46;61 &#40;18&#46;63&#59;29&#46;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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">21&#46;52 &#40;15&#46;65&#8211;29&#46;01&#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">0&#46;452&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">Serum iron &#40;&#956;g&#47;dl&#41;&#40;median q25&#8211;q75&#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">59&#46;04 &#40;48&#59;72&#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
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                  \t\t\t\t">53 &#40;41&#46;5&#59;66&#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">49 &#40;38&#46;75&#59;62&#46;71&#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">43&#46;5 &#40;32&#59;60&#46;08&#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">0&#46;0001&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">Ferritin &#40;ng&#47;ml&#41;&#40;median q25&#8211;q75&#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">276&#46;38 &#40;179&#46;62&#59;426&#46;03&#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">333&#46;8 &#40;220&#46;36&#59;461&#46;25&#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">322&#46;33 &#40;224&#46;38&#59;458&#46;03&#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
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                  \t\t\t\t">314&#46;34 &#40;196&#46;55&#8211;431&#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
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                  \t\t\t\t">0&#46;168&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">CRP &#40;mg&#47;l&#41;&#40;median q25&#8211;q75&#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
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">3&#46;8 &#40;1&#46;5&#59;7&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">3&#46;74 &#40;1&#46;69&#59;7&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;52 &#40;2&#46;84&#59;23&#46;31&#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">0&#46;0001&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">Albumin &#40;g&#47;dl&#41;&#40;median q25&#8211;q75&#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">3&#46;79 &#40;3&#46;52&#59;3&#46;99&#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">3&#46;76 &#40;3&#46;53&#59;3&#46;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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;79 &#40;3&#46;5&#59;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
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                  \t\t\t\t">3&#46;62 &#40;3&#46;34&#59;3&#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">0&#46;023&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Baseline characteristics according to ERI quartiles&#46;</p>"
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          "leyenda" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">The values of the ratios do not have units&#46;</p>"
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            0 => array:2 [
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                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
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 1&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\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Quartile 4&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">NLR&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">3&#46;22 &#40;&#177;1&#46;68&#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">3&#46;15 &#40;&#177;1&#46;53&#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">3&#46;49 &#40;&#177;1&#46;91&#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;21 &#40;&#177;2&#46;46&#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">PLR&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;&#177;49&#46;10&#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">134&#46;61 &#40;&#177;54&#46;04&#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&#46;63 &#40;&#177;60&#46;49&#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">185&#46;49 &#40;&#177;85&#46;87&#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">ERI&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;43 &#40;&#177;1&#46;13&#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;85 &#40;&#177;0&#46;94&#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">10&#46;33 &#40;&#177;1&#46;74&#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">25&#46;19 &#40;&#177;13&#46;62&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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          "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">ERI quartiles vs&#46; NLR and PLR means&#46;</p>"
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              "tabla" => array:1 [
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                  <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
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                  \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
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Correlation&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="center" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>&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
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Age&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;5744&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;2535&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">Dry weight&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;3124&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
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                  \t\t\t\t">&#60;0&#46;0001&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">Neutrophils&nbsp;\t\t\t\t\t\t\n
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