The role of urinary Dickkopf-3/creatinine ratio in diagnosis of acute kidney injury before creatinine elevation in pediatric intensive care unit

The role of urinary Dickkopf-3/creatinine ratio in diagnosis of acute kidney injury before creatinine elevation in pediatric intensive care unit | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The role of urinary Dickkopf-3/creatinine ratio in diagnosis of acute kidney injury before creatinine elevation in pediatric intensive care unit Sefa Armağan Gökçeli, Neslihan Günay, İnayet Güntürk, Mehmet Akif Dündar, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5342903/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Early identification of AKI is crucial to lowering morbidity and mortality in pediatric intensive care units (PICU). Dickkopf-3(DKK3) is a glycoprotein produced by stressed tubular epithelium, plays role in Wnt/β-catenin pathway and demonstrates tubulointerstitial damage. The aim of this study to investigate the possible role of urinary DKK3 in detecting AKI before creatinine elevation in PICU and whether elevated urinary DKK3 is associated with worse outcomes. Methods 117 patients were included in the study. Urine DKK3 levels were measured on PICU admission. Patients who developed AKI and those who did not during the 10-days follow-up were compared in terms of urine DKK3 levels, clinical and laboratory variables. Univariate and multiple binary logistic regression analyses were performed to examine risk factors for the development of AKI and mortality. Results Forty-two (35.8%) patients experienced AKI and 39(33%) patients died. Median urine DKK3 level was statistically significantly higher in patients developing AKI (p < 0.001). In multivariate logistic regression model, only LogDKK3/Cr (AOR:3.619; 95%CI:1.478–8.876) was independently associated with AKI. The predictors of mortality by logistic regression model, PELOD (AOR:1.115; 95% CI:1.026–1.212) and LogDKK3/Cr (AOR:3.914; 95%CI:1.397–10.961) were independently associated with mortality. Urine DKK3/Cr more than 63311 pg/ml increases the risk of AKI 5.547 times (95% CI:1.618–19.022, p = 0.006) and more than 86963 pg/ml increases the risk of mortality 5.569 times (95% CI:1.329–22.499, p = 0.019). Conclusions Urine DKK3 is a useful biomarker in predicting the development of AKI according to KDIGO SCr for patients in PICU and high levels are a risk factor for AKI and mortality. Acute Kidney Injury Biomarker Dickkopf-3 Pediatrics Figures Figure 1 INTRODUCTION Acute kidney injury (AKI) is a prevalent illness distinguished by an acute decrease in glomerular filtration rate (GFR) [ 1 , 2 ]. The specific incidence and frequency of AKI in the pediatric age range is not known precisely and varies by country, age, and underlying etiology. Patients in intensive care units have a higher risk of developing AKI than the general population [ 3 ], and early identification of AKI is crucial to lowering morbidity and mortality. Today, the most widely used parameter to diagnosis AKI is an increase in serum creatinine (SCr) and/or a decrease in urine output [ 4 ]. However, it is often inadequate for early prediction of AKI in clinical practice as there may not be any detectable increase in SCr until kidney function decreases to 50%. Also SCr may be affected by many factors such as diet, muscle mass and genetics [ 5 ]. Therefore, there are many studies on new biomarkers such as Neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), liver-type fatty acid binding protein (L-FABP), tissue inhibitor of metalloproteinase-2 (TIMP)-2), insulin-like growth factor binding protein-7 (IGFBP-7) and calprotectin to predict AKI. But to date, no biomarker has been found to determine AKI risk, diagnosis and long-term prognosis [ 6 , 7 ]. A recent consensus statement by Ostermann M et al. recommended that AKI biomarker studies be directed at determining whether biomarker elevations without SCr elevations are associated with worse kidney and patient outcomes [ 8 ]. Dickkopf-3, which has recently been known to implicate role in the pathogenesis of some disease, is a glycoprotein produced by stressed tubular epithelium and plays a role in various processes including cell differentiation, proliferation and apoptosis via the Wnt/β-catenin pathway [ 9 ]. New research suggests that urine Dickkopf-3 (DKK3) demonstrate tubulointerstitial damage and may serve as a valuable marker for early diagnosis of AKI, independent of the underlying disease [ 10 , 11 ]. It is known that activation of the Wnt/β-catenin signaling pathway is an important physiological response in the recovery of AKI and the DKK family has a key role in regulating this response. Prolonged activity of the Wnt/β catenin signaling pathway, which should be temporarily activated during acute injury, causes epithelial cells to transform into mesenchymal cells and cause fibrosis [ 12 ]. Evaluation of whether this signaling pathway is active can be used both to predict the development of AKI and to anticipate complications related to AKI such as chronic kidney disease (CKD) [ 13 ]. It is possible that the levels of DKK3 secreted into the urine in the case of tubular stress may be a short-term, noninvasive diagnostic biomarker of GFR loss. In this study, we aimed to investigate the possible role of urinary DKK3 in detecting kidney injury before creatinine elevation in children treated in the pediatric intensive care unit (PICU) and whether elevated urinary DKK3 is associated with worse kidney and patient outcomes. METHODS Design of Study: This study is a prospective study designed to evaluate patients admitted to Erciyes University Pediatric Intensive Care Unit between June 2020 and April 2021. The study protocol was approved by the local institutional Ethics Committee (2020/610) to comply with Helsinki clinical research standards. There were 242 patients aged 1 month − 18 years who were admitted to PICU on the dates specified above. 125 patients had known kidney disease before PICU admission, SCr value > 90th persentile [ 14 , 15 ] on admission and staying in PICU less than 48 hours were excluded from the study. The remaining 117 patients were included in the study. Additionally, a control group of 28 healthy volunteers of similar age was created to compare urine DKK3/Cr levels. Data: The Pediatric Risk of Mortality (PRISM), Pediatric Logistic Organ Dysfunction (PELOD) and Vasoactive-Inotropic Scores (VIS) (more detailed in supplementary file) of patients who met the inclusion criteria were calculated. In the first 24 hours of hospitalization, urine sampling for complete urine analysis, urine culture, urine microprotein and creatinine and blood sampling for complete blood count, serum biochemistry, plasma bicarbonate (HCO 3 ), prothrombin time (PT), activated partial thromboplastin clotting time (aPTT), international normalized ratio (INR), C-reactive protein and blood culture were done. Demographic characteristics (age, gender, date of birth), types of PICU admission (outside health center, other clinics in the same hospital, home), date of hospitalization and discharge from PICU, date of death if deceased, underlying diseases, main reasons of PICU admission, medication history, anthropometric measurements and vital signs, the Glasgow Coma Scale (GCS) and fluid balance were noted. During the follow-up, the requirement of mechanic ventilation (MV) and kidney replacement therapy (KRT) were documented. SCr level was measured daily daily for the first 4 days and on the 7th and 10th days after PICU admission. The definition and staging of AKI were made in line with the KDIGO 2012 criteria and the highest AKI stage was used for statistical comparisons [ 16 ]. Modified Schwartz formula was used to calculate estimated GFR (eGFR) [ 17 ]. During this 10-day stay, patients who developed kidney damage and patients who did not develop were compared in terms of baseline urine DKK3/Cr levels, clinical and laboratory variables. Urine sampling and calculation of urine DKK3 level: Urine samples were taken from the patients who met the study criteria in the first 24 hours of hospitalization and control groups and centrifuged at 370 g for 10 minutes to remove the sediments and stored at − 80°C until used. For the direct assay of urine samples, after thawing, DKK3 level was measured following the instructions in the commercial kit (Sigma Aldrich Human DKK3 ELISA kit, Catalog Number: RAB0145-1KT, Lot: 1201H254) (Supplementary File). Briefly, the reaction is based on the formation of antigen-antibody complexes without competition. DKK3 (unlabeled antigen) found in urine samples binds to antibody coated wells. The biotin-labeled antibody is then added. Following incubation of antibody-antigen-labeled antibody complexes (sandwich) with added enzyme (HRP-Streptavidin) followed by substrate, the intensity of color increases in direct proportion to the concentration of DKK3 present in the sample (more detailed in supplementary file, supplementary Fig. 1). Statistical analysis: To determine the sample size, the frequency of AKI in the pediatric intensive care unit was determined to be 26% [ 18 ]. The confidence level was taken as 95% and the tolerance value as 8%, and the minimum sample size was determined as 115. All statistical analyzes were performed with SPSS Statistics 22.0 program (Statistical Package for Social Sciences, SPSS Inc., Chicago, IL, USA). Normality of the continuous data were checked using the Shapiro-Wilk Test. Data with normal distribution were expressed as mean ± standard deviation (SD), and variables which were not normally distributed were expressed as median [interquartile range (IQR)]. Categorical variables were expressed as percentages and were compared using the Pearson chi-square test or Fisher’s exact test. Kruskal-Wallis and Mann-Whitney U tests were used to compare not normally distributed variables. Variables compared between patients with non-AKI and AKI were PRISM and PELOD scores, demographic characteristics, types of PICU admission, urine protein to creatinine ratio (PCR), mortality, GCS, DKK3/Cr, SCr and eGFR at diagnosis, requirement of MV and length of PICU stay Univariate and multiple binary logistic regression analyses (method: Enter) were performed to examine risk factors for the development of AKI and mortality. Only independent variables whose effects were significant in univariate analysis were included in the multiple logistic analysis. Urine DKK3 to creatinine ratio was log transformed because of the skewed distribution and put into the regression analysis. We also evaluated association between log DKK3/Cr and clinical and laboratory variables with univariate and stepwise multivariate regression. In addition, we formed the receiver operating characteristic (ROC) curves and determined the area under the curve (AUCs) to calculate the sensitivity and specificity of urinary DKK3 to creatinine ratio for predicting AKI. The diagnostic value of the DKK3/Cr was evaluated using ROC curves. In all statistical analyses, p < 0.05 was considered statistically significant. RESULTS Of the 242 patients admitted to the PICU, 117 patients (70 boys and 47 girls) who met the inclusion criteria were included in the study. The median age on PICU admission was 25.3 (95.9) months and the mean follow-up duration were 6.6 ± 2.8 days. On admission, 72 patients (61.5%) were admitted from pediatrics wards to PICU, 15 patients (12.8%) had nephrotic range proteinuria, and 75 patients (64.1%) had co-morbid disease. Reasons for PICU admission were respiratory diseases (24.8%) followed by post-cardiac surgery (12%), trauma (12%) and brain surgery (9.4%). The most common co-morbid disease was cardiac (17.9%) and neurologic diseases (17.9%) followed by malignity (12.8%), gastrointestinal disorders (7.7%) and others (7.7%). During the follow-up, 62 patients (52.9%) required MV, 42 patients (35.8%) experienced AKI including stage 1 in 38%, stage 2 in 30.9% and stage 3 in 30.9%, and 39 patients (33%) died. Four children (9.5% of patients with AKI) required kidney replacement therapy. While the median (IQR) urine DKK3/Cr was 22920 (51753) pg/mg in AKI patients, 9005 (11323) pg/mg in non-AKI patients and 1293 (1090) pg/mg in control group. There was a statistical significance among the groups (p < 0.001). Comparison between AKI and non-AKI patients in terms of clinical and laboratory parameters at baseline and follow-up : Comparisons are given in Table 1 . The number of patients having nephrotic range proteinuria, mortality and requirement for central venous line was significantly higher in the AKI group compared to non-AKI. Baseline eGFR, PT, INR, aPTT, lactate, UPCR, urine DKK3 to creatinine ratio, PRISM, PELOD and VIS scores at baseline were significantly higher in AKI patients, and SCr, albumin, hemoglobin levels were significantly lower in AKI compared to non-AKI patients. There was no statistically significant difference between groups in terms of gender, age, follow-up duration, requirement for MV, GCS, levels of acute phase proteins and HCO 3 (Table 1 ). Table 1 Comparison between AKI and non-AKI patients for clinical and laboratory parameters at baseline Variables AKI p No AKI Ø ( n = 75) AKI + (n = 42) Girl, n(%)* Age at diagnosis, year (median(IQR))** Follow-up time at PICU, days, (median(IQR))** Duration of mechanic ventilation (days), (median(IQR))** Mortality, n(%)* Nephrotic range proteinuria, n(%)* Intubation and mechanic ventilation, n(%)* Central venous line, n(%)* Comorbid disease, n(%)* 29/38.6 35.5 (84.3) 6 (6) 0 (6) 10(13,3) 3(4,0) 35(46,7) 45(60,0) 44(58,7) 18/42,9 20,6 (81,3) 7(6) 3(8) 29(69,0) 12(28,6) 27(64,3) 35(83,3) 31(73,8) 0.7 0,13 0,8 0,03 < 0.001 < 0.001 0.08 0.01 0.11 Admitted from, n(%)* Outside (home or local hospital) Pediatric wards 0.05 34(45,3) 41(54,7) 11(26,2) 31(73,8) Severity scores on admission GCS (mean ± SD)*** PRISM (median(IQR))** PELOD (median(IQR))** VIS day 1 (median(IQR))** VIS at the time of AKI (median(IQR))** 9.52 ± 3.33 8,36 ± 3.25 0.07 4 (7) 7 (10) 0.007 2 (9) 10.5 (10) 0.002 0 (0) 0 (13) 0.001 - 17.5 (45) - Laboratory parameters on admission 11,3 ± 1.9 11240 (8510) 294000 (171000) 0,31 (0,19) 113,3 (26,0) 3,78(0,68) 13,0(2,1) 1,13(0,19) 27,1(8,7) 8,5 (38,9) 0,19 (1,17) 21,0 (5,5) 1,7 (1,3) 0,45 (0,50) 9005 (11323) 3.9 ± 0.5 10.3 ± 2.6 11070 (11140) 267500 (216500) 0,27 (0,21) 129,5 (104,5) 3,49 (0,73) 13,9(3,5) 1,24(0,29) 30,8(9,2) 9,8 (84,6) 0,44 (1,75) 20,1 (7,8) 2,4 (3) 1,10 (1,65) 22920 (51753) 4.3 ± 0.5 0,03 0,8 0,6 0,009 0,03 0,03 0,05 0,06 0,02 0,3 0,09 0,6 0,02 0,001 0,001 < 0.001 Hemoglobin (g/dL)*** WBC (/mm 3 )** Platelets (×10 3 /mm 3 )** Creatinine (mg/dl)** eGFR Day 1 (ml/min/1.73 m 2 )** Albumin (g/dL)** PT (secs) INR aPTT (secs) CRP (mg/dL)** Procalcitonin (ng/mL) ** HCO 3 (mmol/l) ** Lactate (mmol/l) ** UPCR (mg/g creatinine) ** Urine DKK3/Cr (pg/mg) ** LogUrine DKK3/Cr (pg/mg) *** Abbreviations: PRISM- Pediatric Risk of Mortality , PELOD- Pediatric Logistic Organ Dysfunction , MV- Mechanic ventilation , GSK- Glasgow Coma Scale , VIS- Vasoactive-Inotropic Score , AKI- Acute kidney injury , BUN- Blood urea nitrogen , WBC- White blood cell , eGFR- estimated glomerular filtration rate , PT- Prothrombin time , INR -International normalized ratio , aPTT- Activated partial thromboplastin time , CRP- C-reactive protein , UPCR- Urine protein to creatinine ratio , HCO 3 -Bicarbonate , DKK3- Dickkopf Related Protein 3 , Cr- Creatinine Data with normal distribution are expressed as mean ± standard deviation, parameters with non-normal distribution are expressed as median [interquartile range (IQR)]. Categorical variables are expressed as percentages. *Chi-square test **Mann-Whitney U test ***Independent sample t test The association of increased urine logDKK3 creatinine ratio and predictors of AKI and mortality: Univariate linear regression analyses revealed statistically significant association between urine logDKK3/Cr and age, weight, the type of hospital admission, having comorbidity, requirement and duration of MV, GCS, VIS, PRISM and PELOD scores, AKI, SCr, eGFR, albumin, and having nephrotic range proteinuria on admission (Table 2 ). By multivariate stepwise regression model, duration of MV, SCr, nephrotic range proteinuria on admission and having AKI during the follow-up were independently associated with urine logDKK3/Cr (Table 2 ). Table 2 Association of variables with urine log DKK3/Cr Independent Variables Univariate regression Stepwise multivariate regression B SE p B SE p Age (months) -0.003 0.001 0.001 Weight (kg) -0.009 0.003 0.003 Gender 0.043 0.107 0.7 Co-morbidity 0.400 0.102 < 0.001 Admission from 0.170 0.062 0.007 Hospital stay duration -0.013 0.024 0.6 Intubation 0.398 0.098 < 0.001 MV duration time 0.058 0.012 < 0.001 0.035 0.010 < 0.001 GCS -0.034 0.015 0.03 PRISM 0.031 0.008 < 0.001 PELOD 0.016 0.006 0.004 VIS 0.006 0.002 0.009 AKI 0.439 0.001 < 0.001 0.749 0.13 < 0.001 eGFR admission 0.002 0.001 0.003 SCr admission -1,271 0.297 < 0.001 -0.816 0.230 0.001 BUN 0.009 0.010 0.3 Albumin − .222 0.071 0.002 Nephrotic proteinuria 0.786 0.138 < 0.001 0.270 0.127 0.040 DKK3- Dickkopf Related Protein 3 , Cr- Creatinine , MV-m echanic ventilation , GCS- Glasgow Coma Scale , PRISM- Pediatric Risk of Mortality , PELOD- Pediatric Logistic Organ Dysfunction , VIS- Vasoactive-Inotropic Score , AKI- acute kidney injury , eGFR- estimated glomerular filtration rate, S Cr serum creatinine , BUN- blood urea nitrogen The predictors of AKI in univariate binary logistic regression were PRISM and PELOD scores, SCr levels on admission and LogDKK3/Cr (Table 3 ). By multivariable logistic regression model, only LogDKK3/Cr (AOR 3.619; 95% CI 1.478–8.876) was independently associated with AKI (Table 3 ). Table 3 Logistic regression analysis of risk factors for AKI Independent Variables Univariate regression Multivariate logistic regression OR 95% CI p AOR 95% CI p Age (months) 0.998 0.992–1.004 0.6 Gender 1.190 0.552–2.564 0.7 Co-morbidity 1.986 0.868–4.541 0.1 Duration of MV 1.090 0.988–1.202 0.08 GCS 0.898 0.799–1.010 0.07 PRISM 1.070 1.019–1.125 0.007 1.074 0.984–1.172 0.112 PELOD 1.130 1.049–1.217 0.001 1.030 0.972–1.091 0.317 VIS 5.190 0.000-4.815 0.9 SCr admission 0.047 0.003–0.736 0.029 0.292 0.160–5.245 0.404 Urine log DKK3/Cr 4.970 2.186–11.302 < 0.001 3.619 1.478–8.876 0.005 PRISM Pediatric Risk of Mortality , PELOD Pediatric Logistic Organ Dysfunction , MV Mechanic ventilation , GCS Glasgow Coma Scale , VIS Vasoactive-Inotropic Score , AKI acute kidney injury , AOR adjusted odds ratio , DKK3 Dickkopf Related Protein 3 , SCr serum c reatinine The predictors of PICU mortality in univariate binary logistic regression were having comorbidity, duration of MV, GCS, PRISM and PELOD scores, SCr levels on admission and LogDKK3/Cr (Table 4 ). By multivariable logistic regression model, PELOD (AOR 1.115; 95% CI 1.026–1.212) and LogDKK3/Cr (AOR 3.914; 95% CI 1.397–10.961) were independently associated with mortality (Table 4 ). Table 4 Logistic regression analysis of risk factors for mortality Independent Variables Univariate regression Multivariate logistic regression OR 95% CI p AOR 95% CI p Age (months) 0.998 0.992–1.004 0.5 Gender 1.236 0.567–2.698 0.6 Co-morbidity 3.721 1.466–9.446 0.006 2.220 0.746–6.603 0.15 Duration of MV 1.240 1.114–1.380 < 0.001 1.103 0.958–1.271 0.17 GCS 0.842 0.743–0.954 0.007 1.148 0.906–1.454 0.26 PRISM 1.123 1.043–1.208 0.002 1.034 0.926–1.154 0.5 PELOD 1.116 1.056–1.179 < 0.001 1.115 1.026–1.212 0.010 VIS day 1 1.023 0.998–1.048 0.07 SCr admission 0.079 0.005–1.184 0.066 Urine log DKK3/Cr 6.423 2.283–16.917 < 0.001 3.914 1.397–10.961 0.009 PRISM Pediatric Risk of Mortality , PELOD Pediatric Logistic Organ Dysfunction , MV Mechanic ventilation , GCS Glasgow Coma Scale , VIS Vasoactive-Inotropic Score , AOR adjusted odds ratio , DKK3 Dickkopf Related Protein 3 , Cr Creatinine The association of the cut-off value of urine DKK3 creatinine ratio with AKI and mortality: Urine DKK3/Cr more than 63311 pg/ml increases the risk of AKI 5.547 times (OR 5.547; 95% CI 1.618–19.022, p = 0.006). Urine DKK3/Cr more than 86963 pg/ml increases the risk of mortality 5.569 times (OR 5.569; 95% CI 1.329–22.499, p = 0.019). On PICU admission, urine DKK3/creatinine predicted AKI with AUC 0.73 (95% CI 0.638–0.827) (p = 0.048) (Fig. 1a). Sensitivity and specificity at the cutoff 63311 pg/mg were 26.2% and 94.7%, respectively (Table 5 ). On PICU admission, urine DKK3/Cr predicted mortality with AUC 0.75 (95% CI 0.642–0.852) (p = 0.05) (Fig. 1b). Sensitivity and specificity at the 86963 pg/mg were 28.6% and 94.8%, respectively (Table 5 ). Table 5 The sensitivity and specificity of a cut-off value of urine DKK3/Creatinine for predicting for AKI and mortality DKK3/Creatinine (63311) pg/mg AKI DKK3/Creatinine (86983) pg/mg Mortality Present n (%) Absent n (%) Total n (%) Present n (%) Absent n (%) Total n (%) High, n(%) Low, n(%) Total 10 (23.8) 32 (76.2) 42(100) 4 (5.3) 71 (94.7) 75 (100) 14 (12) 103(88) 117(100) High, n(%) Low, n(%) Total 7 (17.9) 32 (82.1) 39 (100) 3 (3.8) 75 (96.2) 78 (100) 10 (8.5) 107 (91.5) 117(100) Sensitivity of DKK3/Creatinin for AKI: 23.8%; Specificity of DKK3/Creatinin for AKI: 94.7 Sensitivity of DKK3/Creatinin for mortality: 17.9%; Specificity of DKK3/Creatinin for mortality: 96.2% Positive predictive value of DKK3/Creatinin for AKI: 71.4% Positive predictive value of DKK3/Creatinin for AKI: 70.0% Negative predictive value of DKK3/Creatinin for mortality: 68.9% Negative predictive value of DKK3/Creatinin for mortality: 70.1% DISCUSSION This study presents the first largest study investigating the possible role of urine DKK3 excretion to predict AKI in PICU and demonstrates that the children with AKI have had more nephrotic range proteinuria, mortality and multiorgan dysfunction scores and urine DKK3 to creatinine ratio than those without AKI. This study also shows that AKI and mortality is common among the PICU patients and urine DKK3 on PICU admission is a predictor of both AKI development and mortality. Finally, baseline urinary DKK3 excretion above the threshold has high specificity and low sensitivity for predicting both AKI and mortality. Frequency and severity of AKI in PICU varies between studies. AKI and AKI stage 1 have been reported in 12.6–26.9% and 50.3–56.9% of patients in PICU, respectively [ 18 , 19 ]. In our cohort, we found that 35.8% of patients in PICU developed AKI during the follow-up and the percentage of patients at different stages of AKI was similar (stage 1, 38%, stage 2 and 3, 30.9%). This discrepancy may be due to the number of patients with co-morbid disease, which is 64.1% and inclusion criterion of present study. El Halal et al investigated the effect of source of patient admission on mortality [ 20 ]. They found that 55.2% of the cases had co-morbidity and that mortality was statistically higher among children with co-morbidity than those without co-morbidity (13.9% vs. 6.4%). Arıkan et al. evaluated 150 intensive care patients in term of mortality rate and requirement of dialysis in PICU within 28 days and found as 14.6 and 8.9%, respectively. They also showed that risk of AKI and death increases as the length of stay in MV increases [ 21 ]. Similar to the study of Arıkan et al., in our study, the risk of developing AKI and death were increased as the length of stay in MV increased. Our results in terms of dialysis treatment were found to be 3.4%, similar to the study of Louzada et al [ 19 ]. To date, a variety of biomarker studies have been conducted for the early detection of AKI [ 6 , 22 , 23 ]. NGAL, IL-18, KIM-1 and LFABP are the most studied biomarkers. Studies evaluating the usefulness of NGAL for the early diagnosis of AKI demonstrated that sensitivity and specificity were 69-76.9% and 79–90, respectively [ 22 , 23 ]. Sensitivity and specificity were 91% and 81% for KIM-1, 50.6–64% and 86.2–92% for IL-18 [ 23 , 25 ], 64-66.8% and 67.5–93% for L-FABP [ 23 , 26 ] respectively. In our study, the urine DKK3/Cr cut-off value (> 63311 pg/mg) showed 26.2% sensitivity and 94.7% specificity for the early detection of AKI. Early urine DKK3 measurement was moderately useful in demonstrating early prediction of AKI, with an average AUC of 0.73. Recently, Kuai et al. investigated the possible role of urine renin/Cr as a biomarker of early AKI in children and found a sensitivity of 0.805 for AKI stage 3 and 0.801 for mortality in the ROC analysis [ 27 ]. In our study, we measured urine DKK3 in the first 24 hours of hospitalization and a sensitivity of 0.732 for the development of AKI and 0.747 for mortality was found. The low ROC analysis values in our study may be related to the higher number of patients who developed AKI compared to Kuai et al. study, in which only stage 3 AKI patients were included into the ROC analysis [ 27 ]. To the best of our knowledge, there is no study examining the possible role of urine DKK3 for the prediction of AKI in children hospitalized in the PICU. In children with chronic kidney disease (CKD), Federico G et al. evaluated 72 patients with nephronophthisis and glomerulopathy and demonstrated that urine DKK3/Cr was positively correlated with the percentage of interstitial fibrosis and tubular atrophy (IFTA), and DKK3/Cr is more reliable biomarker showing kidney damage than SCr [ 9 ]. In an adult study, Schunk S et al. investigated the capacity of baseline urine DKK3 for the prediction of AKI after cardiac surgery in 733 patients and detected that cut-off value of 471 pg/mg was associated with risk of AKI [ 13 ]. In our study, urinary DKK3/cut-off point value for the development of AKI according to KDIGO SCr was found to be 63311 pg/mg in a total of 117 patients hospitalized in PICU, and it was determined that this value could predict the development of AKI with a sensitivity of 73.2%. In addition, it was found that the cut-off value of 86963 pg/mg could predict the development of mortality with a sensitivity of 74.7%. In our study, AKI developed more frequently in patients with high baseline urine DKK3/Cr value in PICU. These data show that urine DKK3 may be used a reliable biomarker in terms of predicting the development of AKI and the risk of death in these patients without a known history of kidney damage. This approach can enable patients to anticipate at risk so that necessary measures such as effective fluid support can be taken. It can also prevent the prolongation of hospitalization of patients due to AKI and reduce the cost. The high urinary DKK3 level in AKI patients in our study may be associated with the WNT/β-catenin signaling pathway in the pathogenesis of AKI development [ 28 ]. DKK3 is a protein that inhibits the WNT/β-catenin signaling pathway. Therefore, as we have shown in our study, since the WNT/β-catenin pathway is more active in advanced stages of AKI, DKK3, which inhibits WNT/β-catenin pathway, is released into the urine more [ 28 ]. With this aspect, it may be a suitable biomarker for clinical use. Understanding clinical and laboratory risk factors for development of AKI in PICU at the time of diagnosis may provide important advantages to clinicians to guide treatment and follow-up. However, predictors of AKI in PICU patients are different due to differences in study designs and reasons of AKI [ 29 – 36 ]. Proteinuria [ 29 – 31 ], age, multi-organ dysfunction [ 32 ], serum chloride [ 33 ], higher eGFR [ 34 ], higher PRISM score [ 32 , 35 ], required mechanical ventilation, documented infection and having SCr [ 35 ], at baseline and concomitant use of vancomycin and furosemide [ 36 ], have been reported to be independent predictors for AKI. In this study, in the multivariate logistic regression model, PRISM and LogDKK3/Cr at baseline are independently predicted AKI. Our study results are consistent with some previous studies that PICU patients with high PRISM score had a high risk of the development of AKI [ 32 ]. To date, as previously mentioned, there is no pediatric study addressing urine DKK3 in AKI; therefore, we compared our results with adult studies showing that higher urinary DKK3 before the cardiac surgery or invasive cardiovascular procedures was significantly associated with increased risk of AKI [ 13 , 37 ]. Additionally, we demonstrate that urine DKK3/Cr more than cut-off value increases the risk of AKI 5.547 times and the risk of mortality 5.569 times. Initially detected proteinuria in adults in intensive care unit is a risk factor for AKI [ 29 – 31 ]. In our study, urine DKK3/Cr value was found to be higher in patients with nephrotic range proteinuria at baseline and AKI was significantly more common in the same patients. Studies show that the Wnt/β-catenin signaling pathway is active in kidney diseases with podocyte damage, and proteinuria can be reduced with regulatory molecules [ 12 ]. Our study supports the literature because more intense proteinuria is observed in cases where this pathway is likely active. The strengths of this study include the following: 1) This is the first study showing baseline urine DKK3/Cr value as a significant risk factor for AKI in children stayed in PICU; 2) number of patients in our cohort, representing the largest pediatric series in this topic in the literature, 3) data were collected from patients with normal SCr and without history of kidney disease. Our study also has limitations: All participants in our study were enrolled from only single center, it remains to be validated with further studies including patients with difference race 12 . Due to the low prevalence of AKI (9.5% of patients with AKI) requiring KRT, the relationship between urinary DKK3 to creatinine ratio and KRT for AKI could not be evaluated in this study. The sample size of our cohort is small and the number of patients with AKI is also small. We could not test the strength of the urinary DKK3 cutoff value, which increases the risk of developing AKI, in the validation cohort. There is no long-term follow-up of the patients in this study. The answer to the question of how long in advance DKK3 can provide information about the development of long-term kidney damage can only be answered by larger studies with long-term follow-up. Despite all these limitations, we still think that this study gives valuable information about the possible role of urine DKK3 for the prediction of AKI in PICU. In conclusion, Urine DKK3 is a clinically useful biomarker in predicting the development of AKI according to KDIGO SCr in patients hospitalized in PICU. A high level of urine DKK3 is a risk factor for both AKI and mortality in children in PICU. Although the cost of urine DKK3 measurement seems high compared to serum creatinine, there has been hope that such biomarkers could reduce hospitalization costs by predicting early diagnosis of AKI in intensive care patients and providing insight into patient surveillance. Additionally, larger prospective studies are needed to validate our results. Contributions: Research ideas and study design: SAG, ID, MHP; data acquisition: SAG, ID, MAD, BNA, NG; laboratory studies: IG, CY; data analysis/interpretation: ID, SY, NG; statistical analysis: ID, NG; supervision or mentorship: MHP, ID. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated and resolved, including with documentation in the literature if appropriate. Declarations Financial Disclosure: The authors declare that they have no relevant financial interests. Acknowledgment: This study was supported by Erciyes University Research Foundation (TTU-2021-10826) and accepted as an oral presentation in 54th annual scientific meeting of the European Society for Pediatric Nephrology. 22–25 June 2022, Ljubljana, Slovenia. We thank the pediatric intensive care team at Erciyes University, Children Hospital, for their administrative assistance. Data Availability Statement: Data for this study was obtained via e-mail from the corresponding author. e-mail: [email protected] References Roy JP, Devarajan P (2020) Acute kidney injury: diagnosis and management. Indian J Pediatr 87:600–607 Devarajan P (2020) The current state of the art in acute kidney injury. Front Pediatr 8:70 Bai Z, Fang F, Xu Z, Lu C, Wang X, Chen J, Pan J, Wang J, Li Y (2018) Serum and urine FGF23 and IGFBP-7 for the prediction of acute kidney injury in critically ill children. BMC Pediatr 18:192 Sutherland SM, Byrnes JJ, Kothari M, Longhurst CA, Dutta S, Garcia P, Goldstein SL (2015) AKI in hospitalized children: comparing the pRIFLE, AKIN, and KDIGO definitions. Clin J Am Soc Nephrol 10:554–561 Makris K, Spanou L (2016) Acute kidney injury: diagnostic approaches and controversies. Clin Biochem Rev 37:153–175 Palermo J, Dart AB, De Mello A, Devarajan P, Gottesman R, Garcia Guerra G, Hansen G, Joffe AR, Mammen C, Majesic N, Morgan C, Skippen P, Pizzi M, Palijan A, Zappitelli M (2017) Biomarkers for early acute kidney injury diagnosis and severity prediction: a pilot multicenter Canadian study of children admitted to the ICU. Pediatr Crit Care Med 18:e235–e244 Schrezenmeier EV, Barasch J, Budde K, Westhoff T, Schmidt-Ott KM (2017) Biomarkers in acute kidney injury - pathophysiological basis and clinical performance. Acta Physiol (Oxf) 219:554–572 Ostermann M, Zarbock A, Goldstein S, Kashani K, Macedo E, Murugan R, Bell M, Forni L, Guzzi L, Joannidis M, Kane-Gill SL, Legrand M, Mehta R, Murray PT, Pickkers P, Plebani M, Prowle J, Ricci Z, Rimmelé T, Rosner M, Shaw AD, Kellum JA, Ronco C (2020) Recommendations on acute kidney injury biomarkers from the acute disease quality initiative consensus conference: a consensus statement. JAMA Netw Open 3:e2019209 Federico G, Meister M, Mathow D, Heine GH, Moldenhauer G, Popovic ZV, Nordström V, Kopp-Schneider A, Hielscher T, Nelson PJ, Schaefer F, Porubsky S, Fliser D, Arnold B, Gröne HJ (2016) Tubular Dickkopf-3 promotes the development of renal atrophy and fibrosis. JCI insight 1:e84916 Schunk SJ, Speer T, Petrakis I, Fliser D (2021) Dickkopf 3-a novel biomarker of the 'kidney injury continuum'. Nephrol Dial Transpl 36:761–767 Zewinger S, Rauen T, Rudnicki M, Federico G, Wagner M, Triem S, Schunk SJ, Petrakis I, Schmit D, Wagenpfeil S, Heine GH, Mayer G, Floege J, Fliser D, Gröne HJ, Speer T (2018) Dickkopf-3 (DKK3) in urine identifies patients with short-term risk of eGFR loss. J Am Soc Nephrol 29:2722–2733 Zhou D, Tan RJ, Fu H, Liu Y (2016) Wnt/β-catenin signaling in kidney injury and repair: a double-edged sword. Lab Invest 96:156–167 Schunk SJ, Zarbock A, Meersch M, Küllmar M, Kellum JA, Schmit D, Wagner M, Triem S, Wagenpfeil S, Gröne HJ, Schäfers HJ, Fliser D, Speer T, Zewinger S (2019) Association between urinary dickkopf-3, acute kidney injury, and subsequent loss of kidney function in patients undergoing cardiac surgery: an observational cohort study. Lancet 394:488–496 Boer DP, de Rijke YB, Hop WC, Cransberg K, Dorresteijn EM (2010) Reference values for serum creatinine in children younger than 1 year of age. Pediatr Nephrol 25:2107–2113 Ziegelasch N, Vogel M, Müller E, Tremel N, Jurkutat A, Löffler M, Terliesner N, Thiery J, Willenberg A, Kiess W, Dittrich K (2019) Cystatin C serum levels in healthy children are related to age, gender, and pubertal stage. Pediatr Nephrol 34:449–457 Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group (2012) KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int Suppl 1–138 Schwartz GJ, Muñoz A, Schneider MF, Mak RH, Kaskel F, Warady BA, Furth SL (2009) New equations to estimate GFR in children with CKD. J Am Soc Nephrol 20:629–637 Kaddourah A, Basu RK, Bagshaw SM, Goldstein SL (2017) Epidemiology of acute kidney injury in critically ill children and young adults. N Engl J Med 376:11–20 Louzada CF, Ferreira AR (2021) Evaluation of the prevalence and factors associated with acute kidney injury in a pediatric intensive care unit. J Pediatr (Rio J) 97:426–432 El Halal MG, Barbieri E, Filho RM, Trotta Ede A, Carvalho PR (2012) Admission source and mortality in a pediatric intensive care unit. Indian J Crit Care Med 16:81–86 Akcan-Arikan A, Zappitelli M, Loftis LL, Washburn KK, Jefferson LS, Goldstein SL (2007) Modified RIFLE criteria in critically ill children with acute kidney injury. Kidney Int 71:1028–1035 Zhou F, Luo Q, Wang L, Han L (2016) Diagnostic value of neutrophil gelatinase-associated lipocalin for early diagnosis of cardiac surgery-associated acute kidney injury: a meta-analysis. Eur J Cardiothorac Surg 49:746–755 Van den Eynde J, Schuermans A, Verbakel JY, Gewillig M, Kutty S, Allegaert K, Mekahli D (2022) Biomarkers of acute kidney injury after pediatric cardiac surgery: a meta-analysis of diagnostic test accuracy. Eur J Pediatr 181:1909–1921 Assadi F, Sharbaf FG (2019) Urine KIM-1 as a potential biomarker of acute renal injury after circulatory collapse in children. Pediatr Emerg Care 35:104–107 Li Y, Fu C, Zhou X, Xiao Z, Zhu X, Jin M, Li X, Feng X (2012) Urine interleukin-18 and cystatin-C as biomarkers of acute kidney injury in critically ill neonates. Pediatr Nephrol 27:851–860 Yoneyama F, Okamura T, Takigiku K, Yasukouchi S (2020) Novel urinary biomarkers for acute kidney injury and prediction of clinical outcomes after pediatric cardiac surgery. Pediatr Cardiol 41:695–702 Kuai Y, Huang H, Dai X, Zhang Z, Bai Z, Chen J, Fang F, Pan J, Li X, Wang J, Li Y (2022) In PICU acute kidney injury stage 3 or mortality is associated with early excretion of urinary renin. Pediatr Res 91:1149–1155 Zhu X, Li W, Li H (2018) miR-214 ameliorates acute kidney injury via targeting DKK3 and activating of Wnt/β-catenin signaling pathway. Biol Res 51:31 Takahashi EA, Kallmes DF, Fleming CJ, McDonald RJ, McKusick MA, Bjarnason H, Harmsen WS, Misra S (2017) Predictors and outcomes of postcontrast acute kidney injury after endovascular renal artery intervention. J Vasc Interv Radiol 28:1687–1692 Tao Y, Dong W, Li Z, Chen Y, Liang H, Li R, Mo L, Xu L, Liu S, Shi W, Zhang L, Liang X (2017) Proteinuria as an independent risk factor for contrast-induced acute kidney injury and mortality in patients with stroke undergoing cerebral angiography. J Neurointerv Surg 9:445–448 Li SY, Chuang CL, Yang WC, Lin SJ (2015) Proteinuria predicts postcardiotomy acute kidney injury in patients with preserved glomerular filtration rate. J Thorac Cardiovasc Surg 149:894–899 Rustagi RS, Arora K, Das RR, Pooni PA, Singh D (2017) Incidence, risk factors and outcome of acute kidney injury in critically ill children - a developing country perspective. Paediatr Int Child Health 37:35–41 Baalaaji M, Jayashree M, Nallasamy K, Singhi S, Bansal A (2018) Predictors and outcome of acute kidney injury in children with diabetic ketoacidosis. Indian Pediatr 55:311–314 MacDonald C, Norris C, Alton GY, Urschel S, Joffe AR, Morgan CJ (2016) Acute kidney injury after heart transplant in young children: risk factors and outcomes. Pediatr Nephrol 31:671–678 Alkandari O, Eddington KA, Hyder A, Gauvin F, Ducruet T, Gottesman R, Phan V, Zappitelli M (2011) Acute kidney injury is an independent risk factor for pediatric intensive care unit mortality, longer length of stay and prolonged mechanical ventilation in critically ill children: a two-center retrospective cohort study. Crit Care 10(3):R146 Bonazza S, Bresee LC, Kraft T, Ross BC, Dersch-Mills D (2016) Frequency of and risk factors for acute kidney injury associated with vancomycin use in the pediatric intensive care unit. J Pediatr Pharmacol Ther 21:486–493 Roscigno G, Quintavalle C, Biondi-Zoccai G, De Micco F, Frati G, Affinito A, Nuzzo S, Condorelli G, Briguori C (2021) Urinary Dickkopf-3 and contrast-associated kidney damage. J Am Coll Cardiol 77:2667–2676 Supplementary Files GraphicalAbstract.pptx SupplementaryFile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5342903","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":371737429,"identity":"128e6955-edc8-4205-bba4-733e7022b488","order_by":0,"name":"Sefa Armağan Gökçeli","email":"","orcid":"","institution":"KAYSERİ STATE HOSPITAL","correspondingAuthor":false,"prefix":"","firstName":"Sefa","middleName":"Armağan","lastName":"Gökçeli","suffix":""},{"id":371737430,"identity":"e3a09fd6-c237-46d7-918f-3b977aa5aa39","order_by":1,"name":"Neslihan Günay","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYHACxgOJDQwMEiDmxwawQOMBQnrgWhhnNoBoxgbCWhihWph5GyC24dVizt7+4MDDHXZ5ku3tzz7b7rCp020/DLSlxiYalxbLnjMGBxLPJBdL85wxnp17Jk3C7EwiUMuxtNwGHFoMbuQA/dLGnDhPIoeZObftsIQZ0GtApx7GreX+8wdALfVALemPmS1BWs4/JKDlBgPQYW2HE2dLJBgzM4K03CBky5kckJbjiTN7zhgz9ralSW67AbQlAZ9fjh9/+PBnW3XijOPtjxl+ttnwm51Pf/jgQ40NTi04QAJpykfBKBgFo2AUoAEAHuhpKLL56hsAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0995-8501","institution":"Kayseri City Education and Research Hospital: Kayseri Sehir Egitim ve Arastirma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"Neslihan","middleName":"","lastName":"Günay","suffix":""},{"id":371737431,"identity":"f0134722-2569-46c0-bced-d00ef752b8f6","order_by":2,"name":"İnayet Güntürk","email":"","orcid":"","institution":"Niğde Ömer Halisdemir Üniversitesi: Nigde Omer Halisdemir Universitesi","correspondingAuthor":false,"prefix":"","firstName":"İnayet","middleName":"","lastName":"Güntürk","suffix":""},{"id":371737432,"identity":"d49a8314-95dd-4241-a704-c269204ec962","order_by":3,"name":"Mehmet Akif Dündar","email":"","orcid":"","institution":"Kayseri City Education and Research Hospital: Kayseri Sehir Egitim ve Arastirma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"Akif","lastName":"Dündar","suffix":""},{"id":371737433,"identity":"3e31b425-0f4f-4fbc-b7e5-b61c345a1ebb","order_by":4,"name":"Başak Nur Akyıldız","email":"","orcid":"","institution":"Erciyes Universitesi Tip Fakultesi","correspondingAuthor":false,"prefix":"","firstName":"Başak","middleName":"Nur","lastName":"Akyıldız","suffix":""},{"id":371737434,"identity":"35c968e8-25a7-488c-b7ef-6f5d12588a44","order_by":5,"name":"Cevat Yazıcı","email":"","orcid":"","institution":"Erciyes Universitesi Tip Fakultesi","correspondingAuthor":false,"prefix":"","firstName":"Cevat","middleName":"","lastName":"Yazıcı","suffix":""},{"id":371737435,"identity":"a70bab23-637d-4a79-81fe-b61a65957125","order_by":6,"name":"Sibel Yel","email":"","orcid":"","institution":"Erciyes Universitesi Tip Fakultesi","correspondingAuthor":false,"prefix":"","firstName":"Sibel","middleName":"","lastName":"Yel","suffix":""},{"id":371737436,"identity":"850c09ff-36c5-496c-b277-1bd890b9f8ee","order_by":7,"name":"Muammer Hakan Poyrazoğlu","email":"","orcid":"","institution":"Erciyes Universitesi Tip Fakultesi","correspondingAuthor":false,"prefix":"","firstName":"Muammer","middleName":"Hakan","lastName":"Poyrazoğlu","suffix":""},{"id":371737437,"identity":"d598eb4b-2659-43a7-a332-0175e5f650ff","order_by":8,"name":"İsmail Dursun","email":"","orcid":"","institution":"Erciyes Universitesi Tip Fakultesi","correspondingAuthor":false,"prefix":"","firstName":"İsmail","middleName":"","lastName":"Dursun","suffix":""}],"badges":[],"createdAt":"2024-10-27 21:53:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5342903/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5342903/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69437881,"identity":"e1356e60-9fa7-4f62-a169-c2752703f70b","added_by":"auto","created_at":"2024-11-20 10:52:14","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44239,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operator characteristic (ROC) curve for urine DKK3 to creatinine ratio\u003c/strong\u003e. The area under curve is 0.73 (95% CI 0.638-0.827), demonstrating a good performance for the diagnosis of AKI (a) and is 0.75 (95% CI 0.642-0.852), demonstrating a good performance for the mortality (b).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5342903/v1/ec1375d4158493012cd54821.jpg"},{"id":70972655,"identity":"bfe71a1f-6fed-4727-bed3-373b74ab0dc1","added_by":"auto","created_at":"2024-12-09 18:09:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1045113,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5342903/v1/fa1c3060-d9ab-4452-956c-bd5f3b07ff74.pdf"},{"id":69437120,"identity":"a8516d51-d9f5-4816-bc7b-35d4fcf1e913","added_by":"auto","created_at":"2024-11-20 10:44:14","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":131204,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.pptx","url":"https://assets-eu.researchsquare.com/files/rs-5342903/v1/089ccb0713687888e99e0cca.pptx"},{"id":69437122,"identity":"3f8e592b-1149-49e9-8564-b38fd0ad3484","added_by":"auto","created_at":"2024-11-20 10:44:14","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":495335,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-5342903/v1/7d0f26b11bf347eda8e58984.docx"}],"financialInterests":"","formattedTitle":"The role of urinary Dickkopf-3/creatinine ratio in diagnosis of acute kidney injury before creatinine elevation in pediatric intensive care unit","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAcute kidney injury (AKI) is a prevalent illness distinguished by an acute decrease in glomerular filtration rate (GFR) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The specific incidence and frequency of AKI in the pediatric age range is not known precisely and varies by country, age, and underlying etiology. Patients in intensive care units have a higher risk of developing AKI than the general population [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and early identification of AKI is crucial to lowering morbidity and mortality.\u003c/p\u003e \u003cp\u003eToday, the most widely used parameter to diagnosis AKI is an increase in serum creatinine (SCr) and/or a decrease in urine output [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, it is often inadequate for early prediction of AKI in clinical practice as there may not be any detectable increase in SCr until kidney function decreases to 50%. Also SCr may be affected by many factors such as diet, muscle mass and genetics [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, there are many studies on new biomarkers such as Neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), liver-type fatty acid binding protein (L-FABP), tissue inhibitor of metalloproteinase-2 (TIMP)-2), insulin-like growth factor binding protein-7 (IGFBP-7) and calprotectin to predict AKI. But to date, no biomarker has been found to determine AKI risk, diagnosis and long-term prognosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. A recent consensus statement by Ostermann M et al. recommended that AKI biomarker studies be directed at determining whether biomarker elevations without SCr elevations are associated with worse kidney and patient outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDickkopf-3, which has recently been known to implicate role in the pathogenesis of some disease, is a glycoprotein produced by stressed tubular epithelium and plays a role in various processes including cell differentiation, proliferation and apoptosis via the Wnt/β-catenin pathway [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. New research suggests that urine Dickkopf-3 (DKK3) demonstrate tubulointerstitial damage and may serve as a valuable marker for early diagnosis of AKI, independent of the underlying disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is known that activation of the Wnt/β-catenin signaling pathway is an important physiological response in the recovery of AKI and the DKK family has a key role in regulating this response. Prolonged activity of the Wnt/β catenin signaling pathway, which should be temporarily activated during acute injury, causes epithelial cells to transform into mesenchymal cells and cause fibrosis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Evaluation of whether this signaling pathway is active can be used both to predict the development of AKI and to anticipate complications related to AKI such as chronic kidney disease (CKD) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It is possible that the levels of DKK3 secreted into the urine in the case of tubular stress may be a short-term, noninvasive diagnostic biomarker of GFR loss.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to investigate the possible role of urinary DKK3 in detecting kidney injury before creatinine elevation in children treated in the pediatric intensive care unit (PICU) and whether elevated urinary DKK3 is associated with worse kidney and patient outcomes.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign of Study:\u003c/h2\u003e \u003cp\u003e This study is a prospective study designed to evaluate patients admitted to Erciyes University Pediatric Intensive Care Unit between June 2020 and April 2021. The study protocol was approved by the local institutional Ethics Committee (2020/610) to comply with Helsinki clinical research standards.\u003c/p\u003e \u003cp\u003eThere were 242 patients aged 1 month \u0026minus;\u0026thinsp;18 years who were admitted to PICU on the dates specified above. 125 patients had known kidney disease before PICU admission, SCr value\u0026thinsp;\u0026gt;\u0026thinsp;90th persentile [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] on admission and staying in PICU less than 48 hours were excluded from the study. The remaining 117 patients were included in the study. Additionally, a control group of 28 healthy volunteers of similar age was created to compare urine DKK3/Cr levels.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData:\u003c/h3\u003e\n\u003cp\u003eThe Pediatric Risk of Mortality (PRISM), Pediatric Logistic Organ Dysfunction (PELOD) and Vasoactive-Inotropic Scores (VIS) (more detailed in supplementary file) of patients who met the inclusion criteria were calculated. In the first 24 hours of hospitalization, urine sampling for complete urine analysis, urine culture, urine microprotein and creatinine and blood sampling for complete blood count, serum biochemistry, plasma bicarbonate (HCO\u003csub\u003e3\u003c/sub\u003e), prothrombin time (PT), activated partial thromboplastin clotting time (aPTT), international normalized ratio (INR), C-reactive protein and blood culture were done.\u003c/p\u003e \u003cp\u003eDemographic characteristics (age, gender, date of birth), types of PICU admission (outside health center, other clinics in the same hospital, home), date of hospitalization and discharge from PICU, date of death if deceased, underlying diseases, main reasons of PICU admission, medication history, anthropometric measurements and vital signs, the Glasgow Coma Scale (GCS) and fluid balance were noted. During the follow-up, the requirement of mechanic ventilation (MV) and kidney replacement therapy (KRT) were documented.\u003c/p\u003e \u003cp\u003eSCr level was measured daily daily for the first 4 days and on the 7th and 10th days after PICU admission. The definition and staging of AKI were made in line with the KDIGO 2012 criteria and the highest AKI stage was used for statistical comparisons [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Modified Schwartz formula was used to calculate estimated GFR (eGFR) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. During this 10-day stay, patients who developed kidney damage and patients who did not develop were compared in terms of baseline urine DKK3/Cr levels, clinical and laboratory variables.\u003c/p\u003e\n\u003ch3\u003eUrine sampling and calculation of urine DKK3 level:\u003c/h3\u003e\n\u003cp\u003eUrine samples were taken from the patients who met the study criteria in the first 24 hours of hospitalization and control groups and centrifuged at 370 g for 10 minutes to remove the sediments and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until used. For the direct assay of urine samples, after thawing, DKK3 level was measured following the instructions in the commercial kit (Sigma Aldrich Human DKK3 ELISA kit, Catalog Number: RAB0145-1KT, Lot: 1201H254) (Supplementary File). Briefly, the reaction is based on the formation of antigen-antibody complexes without competition. DKK3 (unlabeled antigen) found in urine samples binds to antibody coated wells. The biotin-labeled antibody is then added. Following incubation of antibody-antigen-labeled antibody complexes (sandwich) with added enzyme (HRP-Streptavidin) followed by substrate, the intensity of color increases in direct proportion to the concentration of DKK3 present in the sample (more detailed in supplementary file, supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eTo determine the sample size, the frequency of AKI in the pediatric intensive care unit was determined to be 26% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The confidence level was taken as 95% and the tolerance value as 8%, and the minimum sample size was determined as 115.\u003c/p\u003e \u003cp\u003eAll statistical analyzes were performed with SPSS Statistics 22.0 program (Statistical Package for Social Sciences, SPSS Inc., Chicago, IL, USA). Normality of the continuous data were checked using the Shapiro-Wilk Test. Data with normal distribution were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and variables which were not normally distributed were expressed as median [interquartile range (IQR)]. Categorical variables were expressed as percentages and were compared using the Pearson chi-square test or Fisher\u0026rsquo;s exact test. Kruskal-Wallis and Mann-Whitney U tests were used to compare not normally distributed variables. Variables compared between patients with non-AKI and AKI were PRISM and PELOD scores, demographic characteristics, types of PICU admission, urine protein to creatinine ratio (PCR), mortality, GCS, DKK3/Cr, SCr and eGFR at diagnosis, requirement of MV and length of PICU stay\u003c/p\u003e \u003cp\u003eUnivariate and multiple binary logistic regression analyses (method: Enter) were performed to examine risk factors for the development of AKI and mortality. Only independent variables whose effects were significant in univariate analysis were included in the multiple logistic analysis. Urine DKK3 to creatinine ratio was log transformed because of the skewed distribution and put into the regression analysis. We also evaluated association between log DKK3/Cr and clinical and laboratory variables with univariate and stepwise multivariate regression. In addition, we formed the receiver operating characteristic (ROC) curves and determined the area under the curve (AUCs) to calculate the sensitivity and specificity of urinary DKK3 to creatinine ratio for predicting AKI. The diagnostic value of the DKK3/Cr was evaluated using ROC curves. In all statistical analyses, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOf the 242 patients admitted to the PICU, 117 patients (70 boys and 47 girls) who met the inclusion criteria were included in the study. The median age on PICU admission was 25.3 (95.9) months and the mean follow-up duration were 6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 days.\u003c/p\u003e \u003cp\u003eOn admission, 72 patients (61.5%) were admitted from pediatrics wards to PICU, 15 patients (12.8%) had nephrotic range proteinuria, and 75 patients (64.1%) had co-morbid disease. Reasons for PICU admission were respiratory diseases (24.8%) followed by post-cardiac surgery (12%), trauma (12%) and brain surgery (9.4%). The most common co-morbid disease was cardiac (17.9%) and neurologic diseases (17.9%) followed by malignity (12.8%), gastrointestinal disorders (7.7%) and others (7.7%).\u003c/p\u003e \u003cp\u003eDuring the follow-up, 62 patients (52.9%) required MV, 42 patients (35.8%) experienced AKI including stage 1 in 38%, stage 2 in 30.9% and stage 3 in 30.9%, and 39 patients (33%) died. Four children (9.5% of patients with AKI) required kidney replacement therapy. While the median (IQR) urine DKK3/Cr was 22920 (51753) pg/mg in AKI patients, 9005 (11323) pg/mg in non-AKI patients and 1293 (1090) pg/mg in control group. There was a statistical significance among the groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cb\u003eComparison between AKI and non-AKI patients in terms of clinical and laboratory parameters at baseline and follow-up\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eComparisons are given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The number of patients having nephrotic range proteinuria, mortality and requirement for central venous line was significantly higher in the AKI group compared to non-AKI. Baseline eGFR, PT, INR, aPTT, lactate, UPCR, urine DKK3 to creatinine ratio, PRISM, PELOD and VIS scores at baseline were significantly higher in AKI patients, and SCr, albumin, hemoglobin levels were significantly lower in AKI compared to non-AKI patients. There was no statistically significant difference between groups in terms of gender, age, follow-up duration, requirement for MV, GCS, levels of acute phase proteins and HCO\u003csub\u003e3\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison between AKI and non-AKI patients for clinical and laboratory parameters at baseline\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAKI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo AKI \u0026Oslash;\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAKI +\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirl, n(%)*\u003c/p\u003e \u003cp\u003eAge at diagnosis, year (median(IQR))**\u003c/p\u003e \u003cp\u003eFollow-up time at PICU, days, (median(IQR))**\u003c/p\u003e \u003cp\u003eDuration of mechanic ventilation (days), (median(IQR))**\u003c/p\u003e \u003cp\u003eMortality, n(%)*\u003c/p\u003e \u003cp\u003eNephrotic range proteinuria, n(%)*\u003c/p\u003e \u003cp\u003eIntubation and mechanic ventilation, n(%)*\u003c/p\u003e \u003cp\u003eCentral venous line, n(%)*\u003c/p\u003e \u003cp\u003eComorbid disease, n(%)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29/38.6\u003c/p\u003e \u003cp\u003e35.5 (84.3)\u003c/p\u003e \u003cp\u003e6 (6)\u003c/p\u003e \u003cp\u003e0 (6)\u003c/p\u003e \u003cp\u003e10(13,3)\u003c/p\u003e \u003cp\u003e3(4,0)\u003c/p\u003e \u003cp\u003e35(46,7)\u003c/p\u003e \u003cp\u003e45(60,0)\u003c/p\u003e \u003cp\u003e44(58,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18/42,9\u003c/p\u003e \u003cp\u003e20,6 (81,3)\u003c/p\u003e \u003cp\u003e7(6)\u003c/p\u003e \u003cp\u003e3(8)\u003c/p\u003e \u003cp\u003e29(69,0)\u003c/p\u003e \u003cp\u003e12(28,6)\u003c/p\u003e \u003cp\u003e27(64,3)\u003c/p\u003e \u003cp\u003e35(83,3)\u003c/p\u003e \u003cp\u003e31(73,8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003cp\u003e0,13\u003c/p\u003e \u003cp\u003e0,8\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,03\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0.08\u003c/p\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAdmitted from, n(%)*\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOutside (home or local hospital)\u003c/p\u003e \u003cp\u003ePediatric wards\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34(45,3)\u003c/p\u003e \u003cp\u003e41(54,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(26,2)\u003c/p\u003e \u003cp\u003e31(73,8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeverity scores on admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eGCS (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)***\u003c/p\u003e \u003cp\u003ePRISM (median(IQR))**\u003c/p\u003e \u003cp\u003ePELOD (median(IQR))**\u003c/p\u003e \u003cp\u003eVIS day 1 (median(IQR))**\u003c/p\u003e \u003cp\u003eVIS at the time of AKI (median(IQR))**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,36\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.5 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.5 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory parameters on admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11,3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003cp\u003e11240 (8510)\u003c/p\u003e \u003cp\u003e294000 (171000)\u003c/p\u003e \u003cp\u003e0,31 (0,19)\u003c/p\u003e \u003cp\u003e113,3 (26,0)\u003c/p\u003e \u003cp\u003e3,78(0,68)\u003c/p\u003e \u003cp\u003e13,0(2,1)\u003c/p\u003e \u003cp\u003e1,13(0,19)\u003c/p\u003e \u003cp\u003e27,1(8,7)\u003c/p\u003e \u003cp\u003e8,5 (38,9)\u003c/p\u003e \u003cp\u003e0,19 (1,17)\u003c/p\u003e \u003cp\u003e21,0 (5,5)\u003c/p\u003e \u003cp\u003e1,7 (1,3)\u003c/p\u003e \u003cp\u003e0,45 (0,50)\u003c/p\u003e \u003cp\u003e9005 (11323)\u003c/p\u003e \u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003cp\u003e11070 (11140)\u003c/p\u003e \u003cp\u003e267500 (216500)\u003c/p\u003e \u003cp\u003e0,27 (0,21)\u003c/p\u003e \u003cp\u003e129,5 (104,5)\u003c/p\u003e \u003cp\u003e3,49 (0,73)\u003c/p\u003e \u003cp\u003e13,9(3,5)\u003c/p\u003e \u003cp\u003e1,24(0,29)\u003c/p\u003e \u003cp\u003e30,8(9,2)\u003c/p\u003e \u003cp\u003e9,8 (84,6)\u003c/p\u003e \u003cp\u003e0,44 (1,75)\u003c/p\u003e \u003cp\u003e20,1 (7,8)\u003c/p\u003e \u003cp\u003e2,4 (3)\u003c/p\u003e \u003cp\u003e1,10 (1,65)\u003c/p\u003e \u003cp\u003e22920 (51753)\u003c/p\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0,03\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0,8\u003c/p\u003e \u003cp\u003e0,6\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,009\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,03\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,03\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,05\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,06\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,02\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0,3\u003c/p\u003e \u003cp\u003e0,09\u003c/p\u003e \u003cp\u003e0,6\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,02\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0,001\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)***\u003c/p\u003e \u003cp\u003eWBC (/mm\u003csup\u003e3\u003c/sup\u003e)**\u003c/p\u003e \u003cp\u003ePlatelets (\u0026times;10\u003csup\u003e3\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e)**\u003c/p\u003e \u003cp\u003eCreatinine (mg/dl)**\u003c/p\u003e \u003cp\u003eeGFR Day 1 (ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e)**\u003c/p\u003e \u003cp\u003eAlbumin (g/dL)**\u003c/p\u003e \u003cp\u003ePT (secs)\u003c/p\u003e \u003cp\u003eINR\u003c/p\u003e \u003cp\u003eaPTT (secs)\u003c/p\u003e \u003cp\u003eCRP (mg/dL)**\u003c/p\u003e \u003cp\u003eProcalcitonin (ng/mL) **\u003c/p\u003e \u003cp\u003eHCO\u003csub\u003e3\u003c/sub\u003e (mmol/l) **\u003c/p\u003e \u003cp\u003eLactate (mmol/l) **\u003c/p\u003e \u003cp\u003eUPCR (mg/g creatinine) **\u003c/p\u003e \u003cp\u003eUrine DKK3/Cr (pg/mg) **\u003c/p\u003e \u003cp\u003eLogUrine DKK3/Cr (pg/mg) ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAbbreviations: PRISM-\u003c/b\u003e\u003cem\u003ePediatric Risk of Mortality\u003c/em\u003e, \u003cb\u003ePELOD-\u003c/b\u003e\u003cem\u003ePediatric Logistic Organ Dysfunction\u003c/em\u003e, \u003cb\u003eMV-\u003c/b\u003e\u003cem\u003eMechanic ventilation\u003c/em\u003e, \u003cb\u003eGSK-\u003c/b\u003e\u003cem\u003eGlasgow Coma Scale\u003c/em\u003e, \u003cb\u003eVIS-\u003c/b\u003e\u003cem\u003eVasoactive-Inotropic Score\u003c/em\u003e, \u003cb\u003eAKI-\u003c/b\u003e\u003cem\u003eAcute kidney injury\u003c/em\u003e, \u003cb\u003eBUN-\u003c/b\u003e\u003cem\u003eBlood urea nitrogen\u003c/em\u003e, \u003cb\u003eWBC-\u003c/b\u003e\u003cem\u003eWhite blood cell\u003c/em\u003e, \u003cb\u003eeGFR-\u003c/b\u003e\u003cem\u003eestimated glomerular filtration rate\u003c/em\u003e, \u003cb\u003ePT-\u003c/b\u003e\u003cem\u003eProthrombin time\u003c/em\u003e, \u003cb\u003eINR\u003c/b\u003e\u003cem\u003e-International normalized ratio\u003c/em\u003e, \u003cb\u003eaPTT-\u003c/b\u003e\u003cem\u003eActivated partial thromboplastin time\u003c/em\u003e, \u003cb\u003eCRP-\u003c/b\u003e\u003cem\u003eC-reactive protein\u003c/em\u003e, \u003cb\u003eUPCR-\u003c/b\u003e\u003cem\u003eUrine protein to creatinine ratio\u003c/em\u003e, \u003cb\u003eHCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e\u003cem\u003e-Bicarbonate\u003c/em\u003e, \u003cb\u003eDKK3-\u003c/b\u003e\u003cem\u003eDickkopf Related Protein 3\u003c/em\u003e, \u003cb\u003eCr-\u003c/b\u003e\u003cem\u003eCreatinine\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eData with normal distribution are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, parameters with non-normal distribution are expressed as median [interquartile range (IQR)]. Categorical variables are expressed as percentages. *Chi-square test **Mann-Whitney U test ***Independent sample t test\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThe association of increased urine logDKK3 creatinine ratio and predictors of AKI and mortality:\u003c/h2\u003e \u003cp\u003eUnivariate linear regression analyses revealed statistically significant association between urine logDKK3/Cr and age, weight, the type of hospital admission, having comorbidity, requirement and duration of MV, GCS, VIS, PRISM and PELOD scores, AKI, SCr, eGFR, albumin, and having nephrotic range proteinuria on admission (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). By multivariate stepwise regression model, duration of MV, SCr, nephrotic range proteinuria on admission and having AKI during the follow-up were independently associated with urine logDKK3/Cr (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of variables with urine log DKK3/Cr\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndependent Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eStepwise multivariate regression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission from\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital stay duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntubation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMV duration time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRISM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePELOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCr admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1,271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNephrotic proteinuria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDKK3-\u003c/b\u003e\u003cem\u003eDickkopf Related Protein 3\u003c/em\u003e, \u003cb\u003eCr-\u003c/b\u003e\u003cem\u003eCreatinine\u003c/em\u003e, \u003cb\u003eMV-m\u003c/b\u003e\u003cem\u003eechanic ventilation\u003c/em\u003e, \u003cb\u003eGCS-\u003c/b\u003e\u003cem\u003eGlasgow Coma Scale\u003c/em\u003e, \u003cb\u003ePRISM-\u003c/b\u003e\u003cem\u003ePediatric Risk of Mortality\u003c/em\u003e, \u003cb\u003ePELOD-\u003c/b\u003e\u003cem\u003ePediatric Logistic Organ Dysfunction\u003c/em\u003e, \u003cb\u003eVIS-\u003c/b\u003e\u003cem\u003eVasoactive-Inotropic Score\u003c/em\u003e, \u003cb\u003eAKI-\u003c/b\u003e\u003cem\u003eacute kidney injury\u003c/em\u003e, \u003cb\u003eeGFR-\u003c/b\u003e\u003cem\u003eestimated glomerular filtration rate, S\u003c/em\u003e\u003cb\u003eCr\u003c/b\u003e \u003cem\u003eserum creatinine\u003c/em\u003e, \u003cb\u003eBUN-\u003c/b\u003e\u003cem\u003eblood urea nitrogen\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe predictors of AKI in univariate binary logistic regression were PRISM and PELOD scores, SCr levels on admission and LogDKK3/Cr (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). By multivariable logistic regression model, only LogDKK3/Cr (AOR 3.619; 95% CI 1.478\u0026ndash;8.876) was independently associated with AKI (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of risk factors for AKI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndependent Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate logistic regression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.992\u0026ndash;1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.552\u0026ndash;2.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.868\u0026ndash;4.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of MV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.988\u0026ndash;1.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.799\u0026ndash;1.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRISM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.019\u0026ndash;1.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.984\u0026ndash;1.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePELOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.049\u0026ndash;1.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.972\u0026ndash;1.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000-4.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCr admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u0026ndash;0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.160\u0026ndash;5.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrine log DKK3/Cr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.186\u0026ndash;11.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.478\u0026ndash;8.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePRISM\u003c/b\u003e \u003cem\u003ePediatric Risk of Mortality\u003c/em\u003e, \u003cb\u003ePELOD\u003c/b\u003e \u003cem\u003ePediatric Logistic Organ Dysfunction\u003c/em\u003e, \u003cb\u003eMV\u003c/b\u003e \u003cem\u003eMechanic ventilation\u003c/em\u003e, \u003cb\u003eGCS\u003c/b\u003e \u003cem\u003eGlasgow Coma Scale\u003c/em\u003e, \u003cb\u003eVIS\u003c/b\u003e \u003cem\u003eVasoactive-Inotropic Score\u003c/em\u003e, \u003cb\u003eAKI\u003c/b\u003e \u003cem\u003eacute kidney injury\u003c/em\u003e, \u003cb\u003eAOR\u003c/b\u003e \u003cem\u003eadjusted odds ratio\u003c/em\u003e, \u003cb\u003eDKK3\u003c/b\u003e \u003cem\u003eDickkopf Related Protein 3\u003c/em\u003e, \u003cb\u003eSCr\u003c/b\u003e \u003cem\u003eserum\u003c/em\u003e c\u003cem\u003ereatinine\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe predictors of PICU mortality in univariate binary logistic regression were having comorbidity, duration of MV, GCS, PRISM and PELOD scores, SCr levels on admission and LogDKK3/Cr (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). By multivariable logistic regression model, PELOD (AOR 1.115; 95% CI 1.026\u0026ndash;1.212) and LogDKK3/Cr (AOR 3.914; 95% CI 1.397\u0026ndash;10.961) were independently associated with mortality (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of risk factors for mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndependent Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate logistic regression\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.992\u0026ndash;1.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.567\u0026ndash;2.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.466\u0026ndash;9.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.746\u0026ndash;6.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of MV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.114\u0026ndash;1.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.958\u0026ndash;1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.743\u0026ndash;0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.906\u0026ndash;1.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRISM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.043\u0026ndash;1.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.926\u0026ndash;1.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePELOD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.056\u0026ndash;1.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.026\u0026ndash;1.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIS day 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.998\u0026ndash;1.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCr admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u0026ndash;1.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrine log DKK3/Cr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.283\u0026ndash;16.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.397\u0026ndash;10.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePRISM\u003c/b\u003e \u003cem\u003ePediatric Risk of Mortality\u003c/em\u003e, \u003cb\u003ePELOD\u003c/b\u003e \u003cem\u003ePediatric Logistic Organ Dysfunction\u003c/em\u003e, \u003cb\u003eMV\u003c/b\u003e \u003cem\u003eMechanic ventilation\u003c/em\u003e, \u003cb\u003eGCS\u003c/b\u003e \u003cem\u003eGlasgow Coma Scale\u003c/em\u003e, \u003cb\u003eVIS\u003c/b\u003e \u003cem\u003eVasoactive-Inotropic Score\u003c/em\u003e, \u003cb\u003eAOR\u003c/b\u003e \u003cem\u003eadjusted odds ratio\u003c/em\u003e, \u003cb\u003eDKK3\u003c/b\u003e\u003cem\u003eDickkopf Related Protein 3\u003c/em\u003e, \u003cb\u003eCr\u003c/b\u003e \u003cem\u003eCreatinine\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe association of the cut-off value of urine DKK3 creatinine ratio with AKI and mortality:\u003c/h3\u003e\n\u003cp\u003eUrine DKK3/Cr more than 63311 pg/ml increases the risk of AKI 5.547 times (OR 5.547; 95% CI 1.618\u0026ndash;19.022, p\u0026thinsp;=\u0026thinsp;0.006). Urine DKK3/Cr more than 86963 pg/ml increases the risk of mortality 5.569 times (OR 5.569; 95% CI 1.329\u0026ndash;22.499, p\u0026thinsp;=\u0026thinsp;0.019).\u003c/p\u003e \u003cp\u003eOn PICU admission, urine DKK3/creatinine predicted AKI with AUC 0.73 (95% CI 0.638\u0026ndash;0.827) (p\u0026thinsp;=\u0026thinsp;0.048) (Fig.\u0026nbsp;1a). Sensitivity and specificity at the cutoff 63311 pg/mg were 26.2% and 94.7%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). On PICU admission, urine DKK3/Cr predicted mortality with AUC 0.75 (95% CI 0.642\u0026ndash;0.852) (p\u0026thinsp;=\u0026thinsp;0.05) (Fig.\u0026nbsp;1b). Sensitivity and specificity at the 86963 pg/mg were 28.6% and 94.8%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe sensitivity and specificity of a cut-off value of urine DKK3/Creatinine for predicting for AKI and mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDKK3/Creatinine\u003c/p\u003e \u003cp\u003e(63311) pg/mg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAKI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDKK3/Creatinine\u003c/p\u003e \u003cp\u003e(86983) pg/mg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAbsent\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh, n(%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eLow, n(%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (23.8)\u003c/p\u003e \u003cp\u003e32 (76.2)\u003c/p\u003e \u003cp\u003e42(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (5.3)\u003c/p\u003e \u003cp\u003e71 (94.7)\u003c/p\u003e \u003cp\u003e75 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (12)\u003c/p\u003e \u003cp\u003e103(88)\u003c/p\u003e \u003cp\u003e117(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHigh, n(%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eLow, n(%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (17.9)\u003c/p\u003e \u003cp\u003e32 (82.1)\u003c/p\u003e \u003cp\u003e39 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (3.8)\u003c/p\u003e \u003cp\u003e75 (96.2)\u003c/p\u003e \u003cp\u003e78 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10 (8.5)\u003c/p\u003e \u003cp\u003e107 (91.5)\u003c/p\u003e \u003cp\u003e117(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSensitivity of DKK3/Creatinin for AKI: 23.8%; Specificity of DKK3/Creatinin for AKI: 94.7\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eSensitivity of DKK3/Creatinin for mortality: 17.9%; Specificity of DKK3/Creatinin for mortality: 96.2%\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePositive predictive value of DKK3/Creatinin for AKI: 71.4%\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePositive predictive value of DKK3/Creatinin for AKI: 70.0%\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eNegative predictive value of DKK3/Creatinin for mortality: 68.9%\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eNegative predictive value of DKK3/Creatinin for mortality: 70.1%\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study presents the first largest study investigating the possible role of urine DKK3 excretion to predict AKI in PICU and demonstrates that the children with AKI have had more nephrotic range proteinuria, mortality and multiorgan dysfunction scores and urine DKK3 to creatinine ratio than those without AKI. This study also shows that AKI and mortality is common among the PICU patients and urine DKK3 on PICU admission is a predictor of both AKI development and mortality. Finally, baseline urinary DKK3 excretion above the threshold has high specificity and low sensitivity for predicting both AKI and mortality. Frequency and severity of AKI in PICU varies between studies. AKI and AKI stage 1 have been reported in 12.6\u0026ndash;26.9% and 50.3\u0026ndash;56.9% of patients in PICU, respectively [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In our cohort, we found that 35.8% of patients in PICU developed AKI during the follow-up and the percentage of patients at different stages of AKI was similar (stage 1, 38%, stage 2 and 3, 30.9%). This discrepancy may be due to the number of patients with co-morbid disease, which is 64.1% and inclusion criterion of present study. El Halal et al investigated the effect of source of patient admission on mortality [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. They found that 55.2% of the cases had co-morbidity and that mortality was statistically higher among children with co-morbidity than those without co-morbidity (13.9% vs. 6.4%).\u003c/p\u003e \u003cp\u003eArıkan et al. evaluated 150 intensive care patients in term of mortality rate and requirement of dialysis in PICU within 28 days and found as 14.6 and 8.9%, respectively. They also showed that risk of AKI and death increases as the length of stay in MV increases [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similar to the study of Arıkan et al., in our study, the risk of developing AKI and death were increased as the length of stay in MV increased. Our results in terms of dialysis treatment were found to be 3.4%, similar to the study of Louzada et al [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo date, a variety of biomarker studies have been conducted for the early detection of AKI [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. NGAL, IL-18, KIM-1 and LFABP are the most studied biomarkers. Studies evaluating the usefulness of NGAL for the early diagnosis of AKI demonstrated that sensitivity and specificity were 69-76.9% and 79\u0026ndash;90, respectively [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Sensitivity and specificity were 91% and 81% for KIM-1, 50.6\u0026ndash;64% and 86.2\u0026ndash;92% for IL-18 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], 64-66.8% and 67.5\u0026ndash;93% for L-FABP [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] respectively. In our study, the urine DKK3/Cr cut-off value (\u0026gt;\u0026thinsp;63311 pg/mg) showed 26.2% sensitivity and 94.7% specificity for the early detection of AKI. Early urine DKK3 measurement was moderately useful in demonstrating early prediction of AKI, with an average AUC of 0.73. Recently, Kuai et al. investigated the possible role of urine renin/Cr as a biomarker of early AKI in children and found a sensitivity of 0.805 for AKI stage 3 and 0.801 for mortality in the ROC analysis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In our study, we measured urine DKK3 in the first 24 hours of hospitalization and a sensitivity of 0.732 for the development of AKI and 0.747 for mortality was found. The low ROC analysis values in our study may be related to the higher number of patients who developed AKI compared to Kuai et al. study, in which only stage 3 AKI patients were included into the ROC analysis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, there is no study examining the possible role of urine DKK3 for the prediction of AKI in children hospitalized in the PICU. In children with chronic kidney disease (CKD), Federico G et al. evaluated 72 patients with nephronophthisis and glomerulopathy and demonstrated that urine DKK3/Cr was positively correlated with the percentage of interstitial fibrosis and tubular atrophy (IFTA), and DKK3/Cr is more reliable biomarker showing kidney damage than SCr [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In an adult study, Schunk S et al. investigated the capacity of baseline urine DKK3 for the prediction of AKI after cardiac surgery in 733 patients and detected that cut-off value of 471 pg/mg was associated with risk of AKI [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In our study, urinary DKK3/cut-off point value for the development of AKI according to KDIGO SCr was found to be 63311 pg/mg in a total of 117 patients hospitalized in PICU, and it was determined that this value could predict the development of AKI with a sensitivity of 73.2%. In addition, it was found that the cut-off value of 86963 pg/mg could predict the development of mortality with a sensitivity of 74.7%. In our study, AKI developed more frequently in patients with high baseline urine DKK3/Cr value in PICU. These data show that urine DKK3 may be used a reliable biomarker in terms of predicting the development of AKI and the risk of death in these patients without a known history of kidney damage. This approach can enable patients to anticipate at risk so that necessary measures such as effective fluid support can be taken. It can also prevent the prolongation of hospitalization of patients due to AKI and reduce the cost. The high urinary DKK3 level in AKI patients in our study may be associated with the WNT/β-catenin signaling pathway in the pathogenesis of AKI development [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. DKK3 is a protein that inhibits the WNT/β-catenin signaling pathway. Therefore, as we have shown in our study, since the WNT/β-catenin pathway is more active in advanced stages of AKI, DKK3, which inhibits WNT/β-catenin pathway, is released into the urine more [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. With this aspect, it may be a suitable biomarker for clinical use.\u003c/p\u003e \u003cp\u003eUnderstanding clinical and laboratory risk factors for development of AKI in PICU at the time of diagnosis may provide important advantages to clinicians to guide treatment and follow-up. However, predictors of AKI in PICU patients are different due to differences in study designs and reasons of AKI [\u003cspan additionalcitationids=\"CR30 CR31 CR32 CR33 CR34 CR35\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Proteinuria [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], age, multi-organ dysfunction [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], serum chloride [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], higher eGFR [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], higher PRISM score [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], required mechanical ventilation, documented infection and having SCr [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], at baseline and concomitant use of vancomycin and furosemide [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], have been reported to be independent predictors for AKI. In this study, in the multivariate logistic regression model, PRISM and LogDKK3/Cr at baseline are independently predicted AKI. Our study results are consistent with some previous studies that PICU patients with high PRISM score had a high risk of the development of AKI [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. To date, as previously mentioned, there is no pediatric study addressing urine DKK3 in AKI; therefore, we compared our results with adult studies showing that higher urinary DKK3 before the cardiac surgery or invasive cardiovascular procedures was significantly associated with increased risk of AKI [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Additionally, we demonstrate that urine DKK3/Cr more than cut-off value increases the risk of AKI 5.547 times and the risk of mortality 5.569 times.\u003c/p\u003e \u003cp\u003eInitially detected proteinuria in adults in intensive care unit is a risk factor for AKI [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In our study, urine DKK3/Cr value was found to be higher in patients with nephrotic range proteinuria at baseline and AKI was significantly more common in the same patients. Studies show that the Wnt/β-catenin signaling pathway is active in kidney diseases with podocyte damage, and proteinuria can be reduced with regulatory molecules [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Our study supports the literature because more intense proteinuria is observed in cases where this pathway is likely active.\u003c/p\u003e \u003cp\u003eThe strengths of this study include the following: 1) This is the first study showing baseline urine DKK3/Cr value as a significant risk factor for AKI in children stayed in PICU; 2) number of patients in our cohort, representing the largest pediatric series in this topic in the literature, 3) data were collected from patients with normal SCr and without history of kidney disease.\u003c/p\u003e \u003cp\u003eOur study also has limitations:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAll participants in our study were enrolled from only single center, it remains to be validated with further studies including patients with difference race\u003csup\u003e12\u003c/sup\u003e. Due to the low prevalence of AKI (9.5% of patients with AKI) requiring KRT, the relationship between urinary DKK3 to creatinine ratio and KRT for AKI could not be evaluated in this study.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe sample size of our cohort is small and the number of patients with AKI is also small. We could not test the strength of the urinary DKK3 cutoff value, which increases the risk of developing AKI, in the validation cohort.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is no long-term follow-up of the patients in this study. The answer to the question of how long in advance DKK3 can provide information about the development of long-term kidney damage can only be answered by larger studies with long-term follow-up.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eDespite all these limitations, we still think that this study gives valuable information about the possible role of urine DKK3 for the prediction of AKI in PICU.\u003c/p\u003e \u003cp\u003eIn conclusion, Urine DKK3 is a clinically useful biomarker in predicting the development of AKI according to KDIGO SCr in patients hospitalized in PICU. A high level of urine DKK3 is a risk factor for both AKI and mortality in children in PICU. Although the cost of urine DKK3 measurement seems high compared to serum creatinine, there has been hope that such biomarkers could reduce hospitalization costs by predicting early diagnosis of AKI in intensive care patients and providing insight into patient surveillance. Additionally, larger prospective studies are needed to validate our results.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eContributions:\u003c/h2\u003e \u003cp\u003eResearch ideas and study design: SAG, ID, MHP; data acquisition: SAG, ID, MAD, BNA, NG; laboratory studies: IG, CY; data analysis/interpretation: ID, SY, NG; statistical analysis: ID, NG; supervision or mentorship: MHP, ID. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual\u0026rsquo;s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated and resolved, including with documentation in the literature if appropriate.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFinancial Disclosure:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no relevant financial interests.\u003c/p\u003e\u003ch2\u003eAcknowledgment:\u003c/h2\u003e \u003cp\u003e This study was supported by Erciyes University Research Foundation (TTU-2021-10826) and accepted as an oral presentation in 54th annual scientific meeting of the European Society for Pediatric Nephrology. 22\u0026ndash;25 June 2022, Ljubljana, Slovenia. We thank the pediatric intensive care team at Erciyes University, Children Hospital, for their administrative assistance.\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e \u003cp\u003eData for this study was obtained via e-mail from the corresponding author. e-mail: [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRoy JP, Devarajan P (2020) Acute kidney injury: diagnosis and management. Indian J Pediatr 87:600\u0026ndash;607\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDevarajan P (2020) The current state of the art in acute kidney injury. Front Pediatr 8:70\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBai Z, Fang F, Xu Z, Lu C, Wang X, Chen J, Pan J, Wang J, Li Y (2018) Serum and urine FGF23 and IGFBP-7 for the prediction of acute kidney injury in critically ill children. 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J Am Coll Cardiol 77:2667\u0026ndash;2676\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute Kidney Injury, Biomarker, Dickkopf-3, Pediatrics","lastPublishedDoi":"10.21203/rs.3.rs-5342903/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5342903/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEarly identification of AKI is crucial to lowering morbidity and mortality in pediatric intensive care units (PICU). Dickkopf-3(DKK3) is a glycoprotein produced by stressed tubular epithelium, plays role in Wnt/β-catenin pathway and demonstrates tubulointerstitial damage. The aim of this study to investigate the possible role of urinary DKK3 in detecting AKI before creatinine elevation in PICU and whether elevated urinary DKK3 is associated with worse outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e117 patients were included in the study. Urine DKK3 levels were measured on PICU admission. Patients who developed AKI and those who did not during the 10-days follow-up were compared in terms of urine DKK3 levels, clinical and laboratory variables. Univariate and multiple binary logistic regression analyses were performed to examine risk factors for the development of AKI and mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eForty-two (35.8%) patients experienced AKI and 39(33%) patients died. Median urine DKK3 level was statistically significantly higher in patients developing AKI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In multivariate logistic regression model, only LogDKK3/Cr (AOR:3.619; 95%CI:1.478\u0026ndash;8.876) was independently associated with AKI. The predictors of mortality by logistic regression model, PELOD (AOR:1.115; 95% CI:1.026\u0026ndash;1.212) and LogDKK3/Cr (AOR:3.914; 95%CI:1.397\u0026ndash;10.961) were independently associated with mortality. Urine DKK3/Cr more than 63311 pg/ml increases the risk of AKI 5.547 times (95% CI:1.618\u0026ndash;19.022, p\u0026thinsp;=\u0026thinsp;0.006) and more than 86963 pg/ml increases the risk of mortality 5.569 times (95% CI:1.329\u0026ndash;22.499, p\u0026thinsp;=\u0026thinsp;0.019).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eUrine DKK3 is a useful biomarker in predicting the development of AKI according to KDIGO SCr for patients in PICU and high levels are a risk factor for AKI and mortality.\u003c/p\u003e","manuscriptTitle":"The role of urinary Dickkopf-3/creatinine ratio in diagnosis of acute kidney injury before creatinine elevation in pediatric intensive care unit","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-20 10:44:09","doi":"10.21203/rs.3.rs-5342903/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d428930-8635-4b68-9a5f-5da9116653e1","owner":[],"postedDate":"November 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T18:01:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-20 10:44:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5342903","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5342903","identity":"rs-5342903","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}