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        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Time-dependent ROC curves &#40;cumulative&#47;dynamic&#41; in the exploratory sample&#46; Cases of AKI versus control&#58; &#40;A&#41; Severe AKI &#40;stage III&#41;&#46; &#40;B&#41; Moderate AKI &#40;stage II&#41;&#46; &#40;C&#41; Mild AKI &#40;stage I&#41;&#46; The unbroken line corresponds to the 1-day prediction and the dotted line corresponds to the 2-day prediction&#46;</p>"
        ]
      ]
    ]
    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Background</span><p id="par0005" class="elsevierStylePara elsevierViewall">Cardiac surgery-associated acute kidney injury &#40;CSA-AKI&#41; has received considerable attention in recent years&#46;<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">1&#44;2</span></a> Despite its multifactorial origin&#44; some characteristics of CSA-AKI make it an interesting topic for research&#58; high incidence&#44; a known time of onset&#44; a detailed epidemiology&#44; and several accurate and validated prediction models based on well-defined risk factors&#46;<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">3&#44;4</span></a> For all these reasons&#44; cardiac surgery patients are frequently included in studies on biomarkers of acute kidney injury&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">The last decade has seen the introduction of new biomarkers&#44;<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">5</span></a> some of which have been widely tested&#44;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">6&#8211;8</span></a> However&#44; despite more than 10 years of intense research&#44; the new biomarkers of acute kidney injury are not yet ready for clinical use&#46; Clinicians treating this syndrome are still in need of a therapeutic tool to help their patients&#46; The study of the predictive capacity of these biomarkers in different settings&#44; including cardiac surgery &#40;CS&#41;&#44; has provided a considerable body of new evidence&#46; Unfortunately&#44; none of these biomarkers has reached the clinical phase&#44;<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">9</span></a> and diagnosis and discrimination are still based on serum creatinine &#40;sCr&#41; concentration and urine output&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">The estimated glomerular filtration rate &#40;eGFR&#41; based on sCr levels has already been a focus of research in CSA-AKI&#46;<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">10</span></a> Preoperative eGFR has been shown to be superior to sCr in predicting the need for renal replacement therapy &#40;RRT&#41; in the postoperative period&#44;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">11</span></a> and is independently associated with other negative outcomes&#44; such as prolonged hospitalisation or in-hospital mortality&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">12</span></a> In this study&#44; we hypothesised that postoperative eGFR may be useful as an early predictor of AKI after CS&#46; To test this hypothesis&#44; we studied the predictive capacity of several common parameters used to measure postoperative renal function in a cohort of cardiac surgery patients&#46; Specifically&#44; we evaluated the use of eGFR calculated using the MDRD-4 &#40;4-variable Modification of Diet in Renal Disease&#41; formula&#44; serum urea and their respective changes over time as biomarkers to predict AKI one or two days in advance&#46; Biomarkers were defined according to the criteria put forward by the Biomarkers Definition Working Group&#46;<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">13</span></a></p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study design and population</span><p id="par0020" class="elsevierStylePara elsevierViewall">Retrospective cohort study performed in a tertiary teaching referral hospital&#46; Data from each adult cardiac surgery patient admitted to the cardiac surgery Intensive Care Unit &#40;ICU&#41; were collected prospectively from the Anaesthesia and Resuscitation department database&#46; Only patients undergoing major surgical interventions between 1 January 2002 and 31 December 2013 were considered&#46; The following types of surgery were included&#58; coronary artery bypass grafting &#40;CABG&#41;&#44; valve repair or replacement surgery&#44; combined procedures &#40;CABG<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>valve surgery&#41;&#44; and aortic surgery&#46; Patients undergoing complex repair of congenital heart diseases&#44; pericardiectomies&#44; and transcatheter aortic valve implantation were excluded&#46; We also excluded patients with chronic kidney disease who received any type of RRT before surgery&#44; kidney transplant recipients&#44; cases of early &#40;&#60;24<span class="elsevierStyleHsp" style=""></span>h&#41; postoperative death&#44; patients requiring a left ventricular assist device &#40;LVAD&#41;&#44; and patients without a baseline sCr value&#44; or cases where the start date of postoperative RRT was not known&#46; In patients undergoing multiple major surgical interventions during the same stay&#44; only data from the first intervention were considered&#46; A small group of patients included in the study were operated 2 or more times on different admissions over the 12-year period&#46; The study was approved by the Institutional Ethics Committee&#46; Given its retrospective nature&#44; the patients&#8217; informed consent was not required&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Definitions and primary endpoint</span><p id="par0025" class="elsevierStylePara elsevierViewall">AKI was defined using the sCr criterion put forward by the Acute Kidney Injury Network &#40;AKIN&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">14</span></a> considering three different categories of severity&#46; Patients were always assigned to the category of greatest severity&#46; Baseline kidney function was assessed by preoperative sCr&#44; taking the value closest to the date of the intervention&#46; Day 0 was the day of admission to the ICU after surgery&#46; Serum creatinine concentration was measured at least once a day while in the ICU and also&#44; only if clinically necessary&#44; during the postoperative period on the ward&#46; CSA-AKI was diagnosed solely on the basis of sCr levels measured during the first postoperative week&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">Given that sCr elevation usually occurs between one and three days after the intervention&#44; the objective of this study was to evaluate the AKI predictive capacity of renal function parameters measured in routine lab tests or calculated 1 or 2 days in advance&#46; Specifically&#44; we analysed serum urea and eGFR MDRD-4&#44;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">15</span></a> defined as&#58;</p><p id="par0035" class="elsevierStylePara elsevierViewall">eGFR MDRD-4<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>175<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span> &#40;sCr&#47;88&#46;4&#41;<span class="elsevierStyleSup">&#8722;1&#46;154</span><span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span> &#40;age&#41;<span class="elsevierStyleSup">&#8722;0&#46;203</span><span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>&#40;0&#46;742 if female&#41;<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>&#40;1&#46;212 if black&#41;&#44; and their respective changes over time&#58; increased urea &#40;&#916;urea&#41; and reduced eGFR MDRD-4 &#40;&#916;MDRD-4&#41;&#46; The primary endpoint is the time from the measurement of the biomarkers to the diagnosis of AKI&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Statistical analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">We performed a descriptive analysis of the frequency of AKI&#44; classified according to severity&#44; during the first week after the intervention&#46; We compared the clinical characteristics and risk factors of groups with and without AKI using standard statistical methods&#58; the Student&#39;s <span class="elsevierStyleItalic">t</span>-test or the Mann&#8211;Whitney test to compare continuous variables&#44; and the chi-square test or Fisher&#39;s exact test to compare proportions&#46; Data were summarised in terms of mean &#40;standard deviation&#41;&#44; median &#40;interquartile range&#41; or proportion &#40;absolute and relative frequencies&#41;&#44; as appropriate&#46; A <span class="elsevierStyleItalic">p</span>-value &#60;0&#46;05 was considered to be statistically significant&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">The total sample was randomised into two sub-samples of similar size&#46; The first sample &#40;exploratory&#41; was used to perform the main analysis&#44; and the second to validate the results&#46; Block randomisation was performed using normal or high sCr as the blocking factor in order to guarantee that both samples presented a similar number of episodes and that groups were homogeneous&#46; Patients were assigned to the normal sCr category if their baseline sCr value was below the 75th percentile &#40;93&#46;7<span class="elsevierStyleHsp" style=""></span>&#956;mol&#47;l for women and 111&#46;38<span class="elsevierStyleHsp" style=""></span>&#956;mol&#47;l for men&#41;&#59; if not&#44; they were assigned to the high category&#46; Baseline sCr was chosen as a blocking factor because this variable has already shown a significant association with the development of post-CS AKI in a predictive model<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">3</span></a> previously validated in our institution&#46;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">16</span></a> Time-dependent ROC curves were calculated to assess the capacity of each parameter to predict an episode of AKI 1 or 2 days in advance&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">17</span></a> The ROC curve is one of the best statistical tools to describe the discrimination capacity of a diagnostic test when the value of the test is measured on a continuous or ordinal scale&#44; and the result is measured on a binary scale &#40;event&#47;non-event&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">18</span></a> The values obtained from a diagnostic test range from null to perfect&#44; and span the &#91;0&#46;5&#59; 1&#93; interval in their corresponding areas under the curve &#40;AUC&#41;&#46; The greater the AUC&#44; the better the discrimination capacity of the test&#46; An AUC of more than 0&#46;7 shows that the test&#44; marker or model has an acceptable discriminatory power&#46;<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">19</span></a> In our study&#44; however&#44; the primary endpoint is not a binary value but rather the time to an event&#44; defined as the time from measurement of the parameter to diagnosis of AKI&#46; In such data&#44; therefore&#44; other definitions of sensitivity and specificity are needed&#44;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">20</span></a> and the definitions of cumulative sensitivity and dynamic specificity proposed by Heagerty et al&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">17</span></a> are used in this study&#46; All patients presenting with AKI before a certain postoperative time point were defined as cases &#40;their data were used to estimate cumulative sensitivity&#41;&#44; while all the rest were controls &#40;their data were used to estimate dynamic specificity&#41;&#46; This means that the status of each patient can change from control to case depending on the postoperative time point&#46; In this study&#44; unlike in diagnostic studies&#44; all patients are assumed to be controls when the parameter is measured<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">18</span></a>&#59; therefore&#44; parameter measurements from patients with AKI at this time point&#44; if any&#44; will not be included in the analysis&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">The predictive capacity of each parameter was analysed on the basis of the 3 categories of AKI&#44; I &#40;mild&#41;&#44; II &#40;moderate&#41;&#44; and III &#40;severe&#41;&#44; and the time &#40;in days&#41; from surgery to biomarker measurement &#40;the day of surgery&#44; 1 day later and 2 days later&#41;&#46; A time-dependent ROC curve was constructed for each parameter and for each postoperative day using the <span class="elsevierStyleItalic">survivalROC</span> package of the statistical software R&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">17</span></a> The information obtained from the different ROC curves is summarised by their respective AUCs and their sensitivity at a fixed specificity&#46; In order to extrapolate the results obtained to the entire population from which the sample was extracted&#44; the confidence intervals &#40;CI&#41; for these AUCs were calculated using the bootstrap method&#46; We also show the optimal cut-off points with their corresponding specificities at a fixed sensitivity&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Finally&#44; we estimated the predictive capacity of the parameters in the second sample &#40;validation sample&#41;&#46; If the results obtained from this sample were equivalent to those from the exploratory sample&#44; then it is safe to say that they are reliable and reproducible&#46; The simplest method&#44; and the one most widely used to prove equivalence&#44; is Schuirmann&#39;s two one-sided test &#40;TOST&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">21</span></a> Equivalence is demonstrated when the 90&#37; CI for the AUC difference is within the acceptance limits &#40;0&#46;8&#8211;1&#46;2&#41; &#40;the limits would be &#91;0&#46;8&#8211;1&#46;25&#93; if the log transformation is applied&#41;&#46; To construct the CI&#44; 500 bootstrap samples from the exploratory sample and 500 bootstrap samples from the validation sample were selected and their corresponding AUCs calculated&#46; The CI was obtained using the rtost function of R&#39;s <span class="elsevierStyleItalic">equivalent</span> package&#46;</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Results</span><p id="par0060" class="elsevierStylePara elsevierViewall">A total of 4167 major cardiac surgeries were performed over the 12-year study period&#46; A total of 205 interventions were excluded &#40;85 due to the type of surgery&#44; 48 due to preoperative RRT&#44; 38 due to early death&#44; 19 due to previous kidney transplant&#44; 15 were the second intervention during the same admission&#44; five due to missing data&#44; and three involved an LVAD&#41;&#46; Some patients met more than one exclusion criterion&#46; Of the remaining 3962 cases&#44; a preliminary exploratory sample of 1980 cases was randomly selected&#46; <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the main demographic and clinical characteristics of this sample&#46; The information relating to the validation sample can be seen in <a class="elsevierStyleCrossRef" href="#sec0060">Table 1B of the additional material</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0065" class="elsevierStylePara elsevierViewall">The frequency and severity of AKI in both samples are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">Only the results of the best biomarker &#40;eGFR MDRD-4&#41; are shown&#46; The results for the rest of the parameters &#40;urea&#44; &#916;urea&#44; &#916;MDRD-4 and &#916;sCr&#41; can be seen in Appendix B of the additional material&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a> shows the time-dependent ROC curves corresponding to the 3 categories of AKI&#44; also taking into account the time from surgery to AKI&#46; The curves in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>A are derived exclusively from data of cases with severe AKI &#40;AKIN stage III&#41; and controls&#44; those in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>B from cases with moderate AKI &#40;AKIN stage II&#41; and controls&#44; and finally those in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>C from mild cases and controls&#46; These curves show the estimated cumulative sensitivity and dynamic specificity of eGFR MDRD-4&#46; Estimates have been calculated for prediction one day &#40;continuous line&#41; and two days &#40;dotted line&#41; in advance&#46; As shown&#44; sensitivity and specificity depend not only on the time between measurement and diagnosis of the event&#44; but also on the time from CS to the measurement&#46; One-day predictions are always better &#40;continuous line&#41;&#44; particularly when MDRD-4 is measured two days after surgery&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0080" class="elsevierStylePara elsevierViewall">The information provided by these curves can be easily interpreted from their corresponding AUCs &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; The eGFR MDRD-4 biomarker showed a high predictive capacity for AKI in all categories &#40;i&#46;e&#46;&#44; mild&#44; moderate and severe&#41; regardless of the day the measurement was taken&#44; with AUC values higher than 0&#46;7 in all cases&#46; Similar results are obtained when sensitivity values are calculated with a specificity of 80&#37; &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">The optimal cut-off points for eGFR MDRD-4&#44; with a sensitivity of 80&#37;&#44; are shown in <a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#46; Appendix B of the additional material &#40;Table A&#46;4&#41; shows similar analyses using baseline changes in sCr &#40;&#916;sCr&#41; as the biomarker&#46; As expected&#44; sCr is not a good predictor&#44; with low AUC values in all cases&#46; Although serum urea&#44; &#916;urea and &#916;MDRD-4 showed an acceptable predictive capacity in some cases&#44; they were never superior to MDRD-4&#46;</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia><p id="par0090" class="elsevierStylePara elsevierViewall">The results obtained from the exploratory sample were validated in the validation sample &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1982&#41;&#46; The 90&#37; CIs obtained from the equivalence tests are shown in <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#46; The results from this second sample were similar to those obtained from the first&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Discussion</span><p id="par0095" class="elsevierStylePara elsevierViewall">In this study&#44; we used time-dependent ROC curves to evaluate the capacity of certain common&#44; inexpensive kidney function laboratory biomarkers to predict onset of CSA-AKI one or two days in advance&#46; The main finding is that eGFR calculated using the MDRD-4 formula is a reliable predictor of AKI after major CS&#46; The limitations of sCr for the early diagnosis of AKI are well known&#44; and have also been confirmed using this methodology&#46; In the specific context of CS&#44; the usual delay before sCr values become elevated after the intervention is amplified due to the haemodilution and positive fluid balance typical of cardiopulmonary bypass&#46; It is also well known that&#44; in the presence of AKI&#44; eGFR decrease precedes an increase in sCr&#46; Likewise&#44; the determination of GFR based on equations such as MDRD does not reflect real filtration in acute situations&#46; These formulas are unsuitable for patients with AKI&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">22</span></a> In our study&#44; however&#44; eGFR was used as a biomarker to predict a future event&#44; not as a parameter to quantify real-time kidney function&#46; Surprisingly&#44; the estimation of GFR based on sCr weighted by certain demographic characteristics &#40;age&#44; race&#44; gender&#41; was superior to GFR obtained from sCr alone in predicting the onset of AKI&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Severe CSA-AKI&#44; defined by the need for RRT&#44; has a poor prognosis&#44; with hospital mortality rates of around 50&#37;&#46; Various predictive indexes that include preoperative risk factors have been developed<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">3&#44;4&#44;23</span></a> and validated<a class="elsevierStyleCrossRefs" href="#bib0245"><span class="elsevierStyleSup">16&#44;24</span></a> to detect at-risk subjects and improve patient information&#46; New serum and urine biomarkers of AKI have greatly improved the early detection of an episode of AKI in different clinical scenarios&#44; starting with paediatric CS more than a decade ago&#46;<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">25</span></a> The usefulness of all these AKI biomarkers has been evaluated with conventional ROC curves&#46; These studies estimate the sensitivity and specificity of the biomarker&#44; the optimal cut-off points&#44; and the time from the peak value of the biomarker to the diagnosis of AKI&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">We took a different approach&#46; Cox regression models are used to process time to event data when the aim is to study the association between certain biomarkers and future events&#46; The main problem is that a biomarker can show a close association with the event&#44; and nevertheless&#44; not be useful for discrimination&#46; Heagerty<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">17</span></a> introduced the concept of the time-dependent ROC curve as an extension of standard ROC curves for the analysis of time to event data&#46; To our knowledge&#44; time-dependent ROC curves have not been used in the specific context of CSA-AKI with a real set of clinical data&#46; Pepe et al&#46;<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">26</span></a> compared different methods of estimating time-dependent ROC curves&#44; but used simulated data&#46; More recently&#44; Pitili et al&#46;<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">27</span></a> used time-dependent ROC curves to evaluate a combination of biomarkers to predict the onset of RRT in mechanically ventilated ICU patients&#46; In our study&#44; we used cumulative&#47;dynamic time-dependent ROC curves&#44; the most widely used approach&#46;<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">17</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">The information provided by time-dependent ROC curves should be interpreted in terms of proportions&#46; For example&#44; one day after surgery &#40;see <a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#44; using eGFR MDRD-4 as a biomarker and assuming a specificity of 80&#37;&#44; 89&#46;4&#37; of cases of severe AKI &#40;AKIN stage III&#41; can be predicted one day in advance&#44; and 85&#46;6&#37; two days in advance&#46; As expected&#44; when the biomarker is measured on the day of surgery&#44; the predictive capacity decreases&#46; For example&#44; on the day of surgery&#44; only 67&#46;4&#37; of patients with severe AKI and 45&#46;4&#37; of patients with moderate AKI &#40;AKIN stage II&#41; can be predicted one day in advance&#46; This same result has also been reported with some of the latest biomarkers&#44;<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">28</span></a> and is due to both the brief interval from the start of injury to measurement&#44; and to the haemodilution that occurs during cardiopulmonary bypass &#40;CPB&#41;&#44; which is when the parameters are measured on admission to the ICU&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">We have also provided the optimal cut-off points &#40;<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>&#41;&#44; which are extremely useful when applying the biomarker in daily practice&#46; The eGFR MDRD-4 values measured on the day of surgery did not discriminate between cases and controls in any of the three AKI categories&#46; However&#44; if measured one day after surgery&#44; a patient will be classified as AKIN stage III 24<span class="elsevierStyleHsp" style=""></span>h in advance if their eGFR MDRD-4 is less than or equal to 51<span class="elsevierStyleHsp" style=""></span>ml&#47;min&#47;1&#46;73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>&#44; as AKIN stage II when 51<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>MDRD-4<span class="elsevierStyleHsp" style=""></span>&#8804;<span class="elsevierStyleHsp" style=""></span>75&#44; as AKIN stage I when 75<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>MDRD-4<span class="elsevierStyleHsp" style=""></span>&#8804;<span class="elsevierStyleHsp" style=""></span>80&#44; and as no AKI when their eGFR MDRD-4 is &#62;80&#46; From our point of view&#44; this information is particularly valuable&#44; since many patients are discharged to the ward the day after surgery&#46; Using these cut-off points&#44; the value of eGFR MDRD-4 the day after surgery can help decide the best option for the patient&#46; These options include&#58; discharge from the ICU &#40;versus remaining in the unit or transfer to an intermediate care unit&#41;&#44; administration of nephrotoxic drugs &#40;suspension&#44; switch or restart&#41;&#44; the need for strict glycaemic control&#44; the maintenance of haemodynamic monitoring&#44; and consultation with specialists from the Nephrology Department&#46;<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">29</span></a> Recently&#44; Meersch et al&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">30</span></a> showed that the implementation of a &#8220;KDIGO measures bundle in cardiothoracic surgery&#8221; in patients undergoing CS with a high risk of AKI&#44; identified by means of a new AKI biomarker measured four hours after CPB&#44; reduced the frequency and severity of CSA-AKI&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">This study has several limitations&#46; First&#44; its retrospective&#44; single-site design called for prospective&#44; external validation&#58; the cut-off points obtained may not be transferable to other institutions&#46; Secondly&#44; defining AKI on the basis of the AKIN&#39;s sCr criterion is open to criticism&#58; we were unable to diagnose AKI using the urine output criterion because the database did not include this variable &#8211; a common problem in most retrospective studies&#46; In the specific context of CS&#44; diagnosing AKI on the basis of the urine output criterion is controversial&#44; and has recently been called into question&#46;<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">31</span></a> There is no consensus on the optimal definition and classification of AKI in CS&#44; although some authors propose a modified RIFLE classification to avoid over-diagnosis of AKI when both AKIN criteria are used&#46;<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">32</span></a> This phenomenon mainly affects patients at AKIN stage I&#46; However&#44; in our sample&#44; the predictive capacity of MDRD-4 improved with the severity of AKI &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; Because prognosis is directly related to the severity of AKI&#44; we believe that over-diagnosis is unlikely in patients with mild AKI&#44; considering that using eGFR MDRD-4 as a biomarker is particularly useful in moderate and severe cases&#46; A final limitation is the effect of the use of baseline values of eGFR MDRD-4&#46; The performance of some new biomarkers &#40;for example&#44; urine NGAL&#41; is known to be affected by the presence of chronic kidney disease&#44;<a class="elsevierStyleCrossRef" href="#bib0330"><span class="elsevierStyleSup">33</span></a> and this means that the test is not informative&#46; We did not explore the role of baseline eGFR MDRD-4 values in predicting AKI due to the small number of cases with moderate or severe AKI&#46; In patients with a preoperative eGFR under 60<span class="elsevierStyleHsp" style=""></span>ml&#47;min&#47;1&#46;73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>&#44; the probability of presenting with an episode of AKI and the optimal cut-off points for MDRD-4 may differ from the figures given in <a class="elsevierStyleCrossRefs" href="#tbl0020">Tables 4 and 5</a>&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Conclusion</span><p id="par0125" class="elsevierStylePara elsevierViewall">Determination of eGFR MDRD-4 one or two days after surgery is a good predictive tool for AKI in patients undergoing major CS&#46; Until new&#44; more accurate biomarkers are found&#44; the cut-off points for this routine&#44; low-cost biomarker can help guide decision-making in the ICU&#46; The design of this study&#44; with its sample size&#44; primary endpoint defined as time to event&#44; and the availability of serial measures for the different parameters analysed&#44; is the ideal setting for using time-dependent ROC methodology&#44; and this research will hopefully help to raise awareness and increase acceptance of this methodology&#46;</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Funding</span><p id="par0130" class="elsevierStylePara elsevierViewall">This study was partially funded by research project no&#46; MTM2016-75351-R of the Spanish Ministry of Economy&#44; Industry and Competitiveness&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Conflicts of interest</span><p id="par0135" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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    "fechaRecibido" => "2017-10-24"
    "fechaAceptado" => "2018-01-22"
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          "clase" => "keyword"
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            0 => "Acute kidney injury"
            1 => "Cardiac surgery"
            2 => "MDRD-4"
            3 => "Prediction"
            4 => "Serum creatinine"
            5 => "Time-dependent ROC curve"
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            0 => "Insuficiencia renal aguda"
            1 => "Cirug&#237;a card&#237;aca"
            2 => "MDRD-4"
            3 => "Predicci&#243;n"
            4 => "Creatinina s&#233;rica"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Acute kidney injury &#40;AKI&#41; diagnosis is still based on serum creatinine and diuresis&#46; However&#44; increases in creatinine are typically delayed 48<span class="elsevierStyleHsp" style=""></span>h or longer after injury&#46; Our aim was to determine the utility of routine postoperative renal function blood tests&#44; to predict AKI one or 2<span class="elsevierStyleHsp" style=""></span>days in advance in a cohort of cardiac surgery patients&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Using a prospective database&#44; we selected a sample of patients who had undergone major cardiac surgery between January 2002 and December 2013&#46; The ability of the parameters to predict AKI was based on Acute Kidney Injury Network serum creatinine criteria&#46; A cohort of 3962 cases was divided into 2 groups of similar size&#44; one being exploratory and the other a validation sample&#46; The exploratory group was used to show primary objectives and the validation group to confirm results&#46; The ability to predict AKI of several kidney function parameters measured in routine postoperative blood tests&#44; was measured with time-dependent ROC curves&#46; The primary endpoint was time from measurement to AKI diagnosis&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">AKI developed in 610 &#40;30&#46;8&#37;&#41; and 623 &#40;31&#46;4&#37;&#41; patients in the exploratory and validation samples&#44; respectively&#46; Estimated glomerular filtration rate using the MDRD-4 equation showed the best AKI prediction capacity&#44; with values for the AUC ROC curves between 0&#46;700 and 0&#46;946&#46; We obtained different cut-off values for estimated glomerular filtration rate depending on the degree of AKI severity and on the time elapsed between surgery and parameter measurement&#46; Results were confirmed in the validation sample&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Postoperative estimated glomerular filtration rate using the MDRD-4 equation showed good ability to predict AKI following cardiac surgery one or 2<span class="elsevierStyleHsp" style=""></span>days in advance&#46;</p></span>"
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          0 => array:2 [
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            "titulo" => "Background"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Antecedentes y objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">El diagn&#243;stico de insuficiencia renal aguda &#40;IRA&#41; todav&#237;a se basa en la creatinina s&#233;rica y la diuresis&#46; Sin embargo&#44; el incremento de la creatinina a menudo se retrasa 48<span class="elsevierStyleHsp" style=""></span>h o m&#225;s con respecto al momento de la lesi&#243;n&#46; El objetivo de este estudio es determinar la utilidad de las pruebas anal&#237;ticas de funci&#243;n renal habituales en el postoperatorio&#44; para predecir la IRA con uno o 2<span class="elsevierStyleHsp" style=""></span>d&#237;as de antelaci&#243;n&#44; en una cohorte de pacientes intervenidos mediante cirug&#237;a card&#237;aca&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes y m&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">A partir de una base de datos prospectiva&#44; se seleccion&#243; una muestra de pacientes operados de cirug&#237;a card&#237;aca mayor&#44; entre enero de 2002 y diciembre de 2013&#46; La definici&#243;n de IRA se bas&#243; en el criterio de la creatinina s&#233;rica utilizado por la Acute Kidney Injury Network&#46; La cohorte de 3&#46;962 casos se dividi&#243; en 2<span class="elsevierStyleHsp" style=""></span>grupos de tama&#241;o similar&#44; uno exploratorio y otro de validaci&#243;n&#46; El grupo exploratorio se utiliz&#243; para demostrar los objetivos principales y el de validaci&#243;n para confirmar los resultados&#46; La capacidad de predicci&#243;n de la IRA&#44; de varios par&#225;metros de funci&#243;n renal medidos en la anal&#237;tica postoperatoria habitual&#44; se evalu&#243; utilizando curvas ROC tiempo-dependientes&#46; Como variable principal se consider&#243; el tiempo transcurrido desde la medida del marcador hasta el diagn&#243;stico de la IRA&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Se observaron 610 &#40;30&#44;8&#37;&#41; y 623 &#40;31&#44;4&#37;&#41; episodios de IRA en los grupos exploratorio y de validaci&#243;n&#44; respectivamente&#46; La tasa de filtrado glomerular estimada por la ecuaci&#243;n MDRD-4 demostr&#243; la mejor capacidad predictiva de IRA&#44; con valores del &#225;rea bajo la curva ROC entre 0&#44;700 y 0&#44;946&#46; Se calcularon distintos puntos de corte para dicho par&#225;metro&#44; en funci&#243;n de la gravedad de la IRA y del tiempo transcurrido entre la cirug&#237;a y su medici&#243;n&#46; Los resultados obtenidos se confirmaron en el grupo de validaci&#243;n&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La tasa de filtrado glomerular postoperatoria&#44; estimada por la ecuaci&#243;n MDRD-4&#44; mostr&#243; una alta capacidad de predicci&#243;n de IRA con uno o 2<span class="elsevierStyleHsp" style=""></span>d&#237;as de antelaci&#243;n&#44; en pacientes operados de cirug&#237;a card&#237;aca&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0030">Please cite this article as&#58; Candela-Toha &#193;&#44; Pardo MC&#44; P&#233;rez T&#44; Muriel A&#44; Zamora J&#46; La tasa de filtrado glomerular estimada es un biomarcador precoz de la insuficiencia renal aguda asociada a la cirug&#237;a card&#237;aca&#46; Nefrologia&#46; 2018&#59;38&#58;596&#8211;605&#46;</p>"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Time-dependent ROC curves &#40;cumulative&#47;dynamic&#41; in the exploratory sample&#46; Cases of AKI versus control&#58; &#40;A&#41; Severe AKI &#40;stage III&#41;&#46; &#40;B&#41; Moderate AKI &#40;stage II&#41;&#46; &#40;C&#41; Mild AKI &#40;stage I&#41;&#46; The unbroken line corresponds to the 1-day prediction and the dotted line corresponds to the 2-day prediction&#46;</p>"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">90&#37; CI for the difference in AUC &#40;log transformation&#41; between the exploratory and validation samples&#46;</p> <p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">The dotted lines show the equivalence margin with &#916;<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>20&#37; &#40;widest range&#41; and with &#916;<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#37; &#40;narrowest range&#41;&#46;</p>"
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          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">CABG&#58; coronary artery bypass grafting&#59; CHF&#58; congestive heart failure&#59; COPD&#58; chronic obstructive pulmonary disease&#59; CPB&#58; cardiopulmonary bypass&#59; DM&#58; diabetes mellitus&#59; eGFR&#58; preoperative glomerular filtration rate estimated by the MDRD-4 formula&#59; LVEF&#58; left ventricular ejection fraction&#59; sCr&#58; serum creatinine&#59; SD&#58; standard deviation&#46;</p>"
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                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Demographic characteristics and risk factors&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Exploratory sample &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1980&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">AKI &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>610&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Age &#40;SD&#41; in years</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67&#46;4 &#40;11&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">70&#46;9 &#40;9&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">65&#46;9 &#40;11&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Men &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;961&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Standard EuroSCORE &#40;SD&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;9 &#40;2&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">7&#46;2 &#40;2&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;4 &#40;2&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">History of CHF &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">29&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">17&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">LVEF &#60;35&#37; &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;294&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">COPD &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">7&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">5&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Previous cardiac surgery &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">12&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Emergency surgery &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&#46;046&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Type of surgery &#40;&#37;&#41;</span></td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Isolated CABG&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">30&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">24&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">33&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Valvular&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">51&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">53&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">50&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Combined<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Other surgeries<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">CPB times &#40;SD&#41; in min</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Ischaemia&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">64&#46;6 &#40;34&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">72&#46;4 &#40;36&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">61&#46;1 &#40;32&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Perfusion&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">89&#46;0 &#40;46&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">102&#46;5 &#40;51&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">83&#46;0 &#40;41&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">Preoperative kidney function</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>sCr&#44; mean &#40;SD&#41; in &#956;mol&#47;l&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">94&#46;62 &#40;31&#46;05&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">107&#46;36 &#40;41&#46;58&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">88&#46;94 &#40;22&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>eGFR&#44; mean &#40;SD&#41; in ml&#47;min&#47;1&#46;73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">70&#46;4 &#40;20&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">62&#46;4 &#40;22&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">73&#46;9 &#40;17&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>eGFR &#60;60<span class="elsevierStyleHsp" style=""></span>ml&#47;min&#47;1&#46;73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span> &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">31&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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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="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col">Type&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Exploratory sample</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Validation sample</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Frequency&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Percentage&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Frequency&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Percentage&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">No event&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1370&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">69&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1357&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">68&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="3" align="left" valign="top">AKI</td><td class="td" title="table-entry  " align="left" valign="top">Mild I&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">486&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">24&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">475&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">23&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Moderate II&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">64&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">71&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Severe III&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">60&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">77&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Total&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1980&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">100&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1982&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">100&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">MDRD-4 is measured&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col"><span class="elsevierStyleItalic">t</span><a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Type</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Severe III&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Moderate II&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Mild I&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">On the day of surgery</td><td class="td" title="table-entry  " align="left" valign="middle"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;833<br>&#40;0&#46;775&#59; 0&#46;912&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;733<br>&#40;0&#46;629&#59; 0&#46;814&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;788<br>&#40;0&#46;751&#59; 0&#46;830&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="middle"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;827<br>&#40;0&#46;763&#59; 0&#46;905&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;700<br>&#40;0&#46;638&#59; 0&#46;761&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;707<br>&#40;0&#46;672&#59; 0&#46;743&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">1 day after surgery</td><td class="td" title="table-entry  " align="left" valign="middle"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;946<br>&#40;0&#46;901&#59; 0&#46;972&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;823<br>&#40;0&#46;747&#59; 0&#46;910&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;763<br>&#40;0&#46;721&#59; 0&#46;795&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="middle"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;919<br>&#40;0&#46;835&#59; 0&#46;962&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;797<br>&#40;0&#46;722&#59; 0&#46;875&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;712<br>&#40;0&#46;673&#59; 0&#46;742&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">2 days after surgery</td><td class="td" title="table-entry  " align="left" valign="middle"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;939<br>&#40;0&#46;810&#59; 0&#46;978&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;820<br>&#40;0&#46;717&#59; 0&#46;936&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;794<br>&#40;0&#46;767&#59; 0&#46;832&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="middle"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;936<br>&#40;0&#46;815&#59; 0&#46;974&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;759<br>&#40;0&#46;655&#59; 0&#46;882&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0&#46;775<br>&#40;0&#46;749&#59; 0&#46;810&#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">AUC &#40;95&#37; CI&#41; of time-dependent ROC curves &#40;cumulative&#47;dynamic&#41; for eGFR MDRD-4 in the exploratory sample&#46;</p>"
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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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">MDRD-4 is measured&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col"><span class="elsevierStyleItalic">t</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Type</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Severe III&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Moderate II&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Mild I&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">On the day of surgery</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">45&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">60&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">38&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">50&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">1 day after surgery</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">89&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">70&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">62&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">85&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">63&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">52&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">2 days after surgery</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">87&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">77&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">64&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">87&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">66&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">59&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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              "nota" => "<p class="elsevierStyleNotepara" id="npar0020"><span class="elsevierStyleItalic">t</span> is the time interval&#44; in days&#44; between measurement of the biomarker and clinical diagnosis of AKI&#46;</p>"
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          "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Sensitivity values as a percentage for a fixed specificity of 80&#37;&#46; Exploratory sample&#46;</p>"
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        "etiqueta" => "Table 5"
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          "leyenda" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">The units of the cut-off points for eGFR MDRD-4 are ml&#47;min&#47;1&#46;73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">MDRD-4 is measured&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col"><span class="elsevierStyleItalic">t</span><a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="6" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Type</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Severe III</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Moderate II</th><th class="td" title="table-head  " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Mild I</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Cut-off point&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Specificity &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Cut-off point&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Specificity &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Cut-off point&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Specificity &#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">On the day of surgery</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">76&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">67&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">81&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">76&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">62&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">73&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">68&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">84&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">57&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">86&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">45&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " rowspan="2" align="left" valign="middle">1 day after surgery</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">t</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">50&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">92&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">75&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">61&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">79&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">50&#46;6&nbsp;\t\t\t\t\t\t\n
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