Non-linear Relationship between Uric Acid to Albumin Ratio and Mortality in Pediatric Intensive Care Unit Patients: A Large-Scale Observational Study

Non-linear Relationship between Uric Acid to Albumin Ratio and Mortality in Pediatric Intensive Care Unit Patients: A Large-Scale Observational Study | 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 Non-linear Relationship between Uric Acid to Albumin Ratio and Mortality in Pediatric Intensive Care Unit Patients: A Large-Scale Observational Study Zhitao Zhong, Qiong Long This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7328002/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Purpose The prognostic value of the uric acid to albumin ratio (UAR) in critically ill children is unknown. We aimed to investigate the association between admission UAR and mortality in the pediatric intensive care unit (PICU) and to characterize the nature of this relationship. Patients and methods: This retrospective cohort study enrolled 6,686 critically ill children from the Pediatric Intensive Care (PIC) database. The primary outcome was 28-day ICU mortality. The relationship between UAR and mortality was explored using multivariable logistic regression. Restricted cubic splines (RCS) and a two-piecewise linear regression model were performed to assess for non-linearity and threshold effects. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and mediation analysis were also conducted. Results In the fully adjusted model, UAR was independently associated with an increased risk of 28-day ICU mortality (OR = 1.25, 95% CI: 1.13–1.37, P < 0.001). Patients in the highest UAR quartile (Q4) had a significantly higher mortality risk compared to the lowest quartile (Q1) (OR = 1.94, 95% CI: 1.34–2.82, P < 0.001). Kaplan-Meier analysis confirmed a significantly lower survival probability in the Q4 group ( P < 0.001). RCS analysis revealed a non-linear relationship ( P for non-linearity < 0.05), identifying a significant inflection point at UAR = 2.815. Below this threshold, the mortality risk increased more steeply (OR = 1.95, 95% CI: 1.49–2.53). The predictive ability of UAR for 28-day ICU mortality (AUC = 0.700) was superior to its individual components. Lactate was found to partially mediate the association, accounting for 35.18% of the total effect. Conclusion Our study identifies admission UAR as a novel, independent predictor of mortality in a large cohort of critically ill children. As a simple and universally available biomarker, UAR holds significant promise for improving early risk stratification in the PICU. uric acid to albumin ratio critically ill children mortality risk pediatric intensive care database Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Accurate and early risk stratification is a cornerstone of modern pediatric intensive care, fundamentally guiding clinical interventions and resource allocation to improve survival rates for critically ill children. This population is uniquely vulnerable, often presenting with complex and rapidly evolving pathophysiological states. While established scoring systems are integral to clinical practice, they rely on a multitude of variables that can be cumbersome to collect and may not fully encapsulate the underlying biological turmoil. [ 1 – 3 ] In the search for such markers, uric acid (UA), the end-product of purine metabolism, is now understood to be more than a simple metabolic waste product. Its elevation often signals accelerated cellular turnover and ATP degradation under conditions of tissue hypoxia and ischemia, positioning it as a key indicator of systemic oxidative stress and endothelial dysfunction. [ 4 , 5 ] Concurrently, serum albumin, a negative acute-phase reactant, is a well-established marker of the body's inflammatory response, nutritional status, and overall physiological reserve. Consequently, hypoalbuminemia has been robustly identified as an independent predictor of mortality in various critically ill cohorts, including pediatric patients. [ 6 , 7 ] Given the distinct yet interconnected pathways these two markers represent, the uric acid to albumin ratio (UAR) has recently been proposed as a novel, integrated biomarker. This composite index has already demonstrated considerable prognostic utility in adult critical care. For instance, an elevated UAR has been independently associated with increased all-cause mortality in adults with coronary artery disease, [ 8 ] and acute kidney injury. [ 9 ] Despite this compelling evidence in adult medicine, the clinical significance and prognostic value of UAR in the pediatric intensive care unit (PICU) remain largely uninvestigated. However, children exhibit distinct metabolic profiles and physiological responses to severe illness, which precludes the direct extrapolation of findings from adult populations. [ 10 ] Therefore, this large-scale observational study aimed to investigate the association between the admission UAR and mortality in a broad cohort of PICU patients. Methods Study Design and Data Source This retrospective cohort study was based on data from the Pediatric Intensive Care (PIC) database, a large, single-center electronic medical record database developed by the Children’s Hospital, Zhejiang University School of Medicine (ZUCH). [ 11 ] The PIC database contains comprehensive, anonymized clinical data from 12,881 pediatric patients admitted to various intensive care units (ICUs) at ZUCH between 2010 and 2018. The study protocol was approved by the Ethics Committee of ZUCH, and the requirement for individual informed consent was waived due to the retrospective nature of the analysis and the de-identification of all patient data. Study Population The study cohort was derived from the PIC database. For individuals with multiple ICU admissions, only data from the initial admission were incorporated into the analysis. The exclusion criteria were as follows: (1) age < 28 days (neonates), and (2) absence of baseline measurements for either UA or Alb. Data Collection and Definitions We extracted a comprehensive set of data for each patient within the first 24 hours of ICU admission, categorized as follows: Baseline Demographics: age and gender. Comorbidities: presence of congenital malformation of the heart, pneumonia, sepsis, and history of preterm birth. Laboratory Parameters: White blood cell (WBC) count, neutrophil count, lymphocyte count, monocyte count, red blood cell (RBC) count, platelet (PLT) count, hemoglobin, red cell distribution width (RDW), and hematocrit (HCT). Renal and Metabolic Panel: Uric acid (UA), sodium, potassium, total calcium, chloride, calculated bicarbonate, lactate, glucose, creatinine, urea, and cystatin C. Liver Function and Protein Panel: Albumin (Alb), globulin, direct bilirubin (DBIL), indirect bilirubin (IBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH). Coagulation Profile: Prothrombin time (PT), partial thromboplastin time (PTT), and international normalized ratio (INR). Lipid Panel: Triglycerides (TG) and total cholesterol. The primary exposure variable, the Uric Acid to Albumin Ratio (UAR), was calculated using the formula: UAR = UA (mg/dL) / Alb (g/dL). The primary outcome for this study was 28-day ICU mortality. Secondary outcomes included in-ICU mortality and in-hospital mortality. Statistical Analysis Continuous variables were presented as median and interquartile range (IQR) given their non-normal distribution, while categorical variables were reported as numbers and percentages (n, %). Patients were stratified into four groups based on quartiles of their baseline UAR. The Kruskal-Wallis test and the chi-square test were used to compare differences in continuous and categorical variables across UAR quartiles, respectively. Variables with more than 20% missing data were excluded from the analysis. [ 12 ] To robustly handle the remaining missing values, we employed a multiple imputation technique. Potential confounders were initially screened using univariate logistic regression. Variables with a P-value 5 were excluded. [ 14 ] Multivariable logistic regression was then performed to assess the independent association between UAR (as both a continuous and a categorical variable) and mortality outcomes. Three models were constructed: a non-adjusted model; Model I, adjusted for gender and pneumonia; and Model II (the fully-adjusted model), which further adjusted for covariates in Model I plus monocyte count, sodium, potassium, calcium, lactate, DBIL, and glucose. Results were presented as odds ratios (OR) with 95% confidence intervals (CI). To explore the potential non-linear relationship between UAR and mortality, we utilized restricted cubic splines (RCS). If non-linearity was detected, a two-piecewise linear regression model was applied to identify any threshold effects. The predictive capacity of UAR for mortality was assessed using the area under the receiver operating characteristic curve (AUC) and compared with that of UA and Alb alone. Kaplan-Meier curves were plotted to visualize survival differences among UAR quartiles, with the log-rank test used for comparison. To ensure the robustness of our findings, subgroup analyses were conducted across strata of age, gender, pneumonia, preterm infants, congenital malformation of heart, and sepsis. Finally, a mediation analysis was performed to investigate whether lactate mediated the relationship between UAR and mortality outcomes. All statistical analyses were conducted using R software (version 4.4.1), and P-value < 0.05 was considered statistically significant. Results Baseline Characteristics of the Study Population This study ultimately included 6,686 critically ill pediatric patients, with the selection process detailed in Fig. 1 . The cohort had a median age of 1.0 years, with 50.10% being infants (≤ 1 year old) and 55.49% being male. The overall 28-day ICU mortality rate was 4.68%. Baseline characteristics stratified by UAR quartiles are presented in Table 1 . Patients in the highest UAR quartile (Q4) were characterized by a younger age distribution and a higher prevalence of comorbidities, including congenital malformation of the heart ( P < 0.001) and sepsis ( P < 0.001). Furthermore, the Q4 group exhibited a profile indicative of greater inflammation and metabolic derangement, with significantly elevated levels of WBC, monocyte count, RDW, lactate, PT, PTT, INR, and urea, alongside lower levels of platelets and bicarbonate (all P < 0.001). Correspondingly, patients in the Q4 group experienced significantly higher rates of 28-day ICU, overall ICU, and in-hospital mortality, as well as a longer ICU stay (all P < 0.001). Table 1 Baseline characteristics of the study cohort stratified by UAR quartiles. Variables Total (n = 6686) Q1 ( 1.537) (n = 1672) P Baseline characteristics Age(years) 0.001 ≤1 3350 (50.10%) 709 (42.40%) 790 (47.28%) 921 (55.12%) 930 (55.62%) >1 3336 (49.90%) 963 (57.60%) 881 (52.72%) 750 (44.88%) 742 (44.38%) Gender 0.001 Male 3710 (55.49%) 893 (53.41%) 883 (52.84%) 953 (57.03%) 981 (58.67%) Female 2976 (44.51%) 779 (46.59%) 788 (47.16%) 718 (42.97%) 691 (41.33%) Comorbidities Congenital malformation of heart 0.012 No 6396 (95.66%) 1620 (96.89%) 1602 (95.87%) 1591 (95.21%) 1583 (94.68%) Yes 290 (4.34%) 52 (3.11%) 69 (4.13%) 80 (4.79%) 89 (5.32%) Pneumonia < 0.001 No 6225 (93.10%) 1516 (90.67%) 1580 (94.55%) 1577 (94.37%) 1552 (92.82%) Yes 461 (6.90%) 156 (9.33%) 91 (5.45%) 94 (5.63%) 120 (7.18%) Sepsis < 0.001 No 6565 (98.19%) 1653 (98.86%) 1654 (98.98%) 1657 (99.16%) 1601 (95.75%) Yes 121 (1.81%) 19 (1.14%) 17 (1.02%) 14 (0.84%) 71 (4.25%) Preterm infants < 0.001 No 6585 (98.49%) 1598 (95.57%) 1652 (98.86%) 1666 (99.70%) 1669 (99.82%) Yes 101 (1.51%) 74 (4.43%) 19 (1.14%) 5 (0.30%) 3 (0.18%) Laboratory tests UA (mg/dL) 4.44 (3.39, 5.75) 2.76 (2.20,3.24) 4.00 (3.58,4.38) 5.02 (4.54,5.56) 7.11 (6.08,9.12) < 0.001 Alb(g/dL) 3.79 (3.40, 4.14) 3.89 (3.50,4.23) 3.88 (3.53,4.20) 3.79 (3.45,4.12) 3.56 (3.11,3.96) < 0.001 UAR 1.17 (0.89, 1.54) 0.73 (0.60,0.82) 1.04 (0.97,1.11) 1.32 (1.25,1.42) 1.95 (1.69,2.61) < 0.001 WBC (10^9/L) 10.67 (7.78, 14.01) 10.93 (7.91,14.28) 10.67 (8.02,13.86) 10.30 (7.76,13.34) 10.84 (7.57,14.66) 0.010 Neutrophil count (10⁹/L) 7.47 (4.73, 10.43) 7.67 (4.41,10.87) 7.64 (4.99,10.39) 7.21 (4.85,9.92) 7.46 (4.67,10.52) 0.162 Lymphocyte count (10^9/L) 2.12 (1.43, 3.03) 2.12 (1.43,3.09) 2.09 (1.41,2.92) 2.11 (1.44,2.93) 2.18 (1.44,3.17) 0.071 Monocyte count (10^9/L) 0.59 (0.41, 0.80) 0.61 (0.43,0.84) 0.59 (0.41,0.79) 0.57 (0.39,0.77) 0.60 (0.38,0.81) < 0.001 RBC (10^12/L) 3.83 (3.41, 4.27) 3.83 (3.41,4.24) 3.85 (3.46,4.28) 3.88 (3.46,4.29) 3.80 (3.27,4.29) 0.006 PLT (10^9/L) 260.00 (180.50, 347.00) 276.75 (199.38,362.00) 266.50 (197.00,356.75) 258.50 (186.00,349.25) 226.25 (141.92,317.50) < 0.001 Hemoglobin (g/L) 106.00 (94.67, 117.00) 106.04 (96.50,118.00) 106.04 (96.00,117.00) 106.00 (96.00,117.00) 104.00 (91.00,116.00) < 0.001 RDW (%) 13.70 (12.83, 14.92) 13.50 (12.70,14.80) 13.53 (12.75,14.60) 13.65 (12.85,14.85) 14.09 (13.15,15.40) < 0.001 HCT (%) 32.20 (28.85, 35.50) 32.30 (29.30,35.60) 32.21 (29.23,35.35) 32.21 (29.00,35.40) 31.60 (27.80,35.50) < 0.001 Sodium (mmol/L) 137.20 (135.30, 139.00) 137.00 (135.00,138.70) 137.00 (135.50,138.75) 137.29 (135.67,139.00) 137.50 (135.00,140.10) < 0.001 Potassium (mmol/L) 3.70 (3.49, 3.97) 3.70 (3.48,3.99) 3.70 (3.49,3.93) 3.70 (3.50,3.94) 3.70 (3.47,4.04) 0.201 Calcium (mmol/L) 1.20 (1.15, 1.25) 1.20 (1.15,1.25) 1.21 (1.17,1.26) 1.21 (1.16,1.26) 1.18 (1.09,1.24) < 0.001 Chloride (mmol/L) 109.00 (106.00, 111.60) 108.33 (105.19,110.71) 109.00 (106.50,111.43) 109.71 (106.80,112.00) 109.00 (105.50,112.17) < 0.001 Bicarbonate (mmol/L) 21.91 (20.36, 23.45) 22.50 (21.07,24.10) 21.96 (20.65,23.30) 21.85 (20.45,23.32) 21.17 (19.06,22.99) < 0.001 Lactate (mmol/L) 1.62 (1.20, 2.20) 1.60 (1.20,2.13) 1.59 (1.20,2.10) 1.55 (1.18,2.00) 1.81 (1.29,2.85) < 0.001 PT (sec) 11.80 (11.70, 11.95) 11.80 (11.70,11.95) 11.80 (11.70,11.95) 11.80 (11.70,11.97) 11.80 (11.66,12.00) 0.247 PTT (sec) 33.80 (28.36, 38.74) 33.10 (27.80,36.70) 32.50 (27.98,37.30) 33.60 (28.60,39.05) 36.40 (29.49,44.80) < 0.001 INR 1.12 (1.01, 1.20) 1.07 (0.99,1.17) 1.09 (1.00,1.17) 1.11 (1.02,1.19) 1.17 (1.05,1.33) < 0.001 TG (mmol/L) 0.77 (0.55, 1.12) 0.78 (0.54,1.12) 0.74 (0.54,1.07) 0.71 (0.52,1.06) 0.87 (0.59,1.36) < 0.001 Cholesterol total (mmol/L) 3.05 (2.36, 3.75) 3.25 (2.56,3.98) 3.13 (2.52,3.77) 3.01 (2.38,3.68) 2.72 (2.04,3.49) < 0.001 DBIL (µmol/L) 2.60 (1.60, 4.80) 2.60 (1.55,4.80) 2.40 (1.60,4.20) 2.60 (1.70,4.40) 3.00 (1.70,6.00) < 0.001 IBIL (µmol/L) 7.20 (4.50, 12.30) 7.40 (4.50,12.77) 7.30 (4.90,12.25) 7.40 (4.60,11.90) 6.70 (3.90,12.20) < 0.001 ALT (U/L) 19.00 (13.00, 32.00) 18.00 (12.00,29.00) 18.00 (12.00,28.00) 18.00 (13.00,28.00) 24.00 (14.46,55.12) < 0.001 AST (U/L) 47.00 (30.00, 87.00) 39.00 (27.00,64.00) 44.00 (29.25,77.00) 47.00 (32.00,82.50) 69.00 (37.00,146.00) < 0.001 Globulin (g/L) 19.23 (15.70, 23.50) 20.50 (16.38,24.60) 19.60 (15.90,23.50) 18.80 (15.70,22.80) 18.40 (15.10,22.56) < 0.001 Glucose (mmol/L) 7.43 (6.28, 8.79) 7.15 (6.10,8.43) 7.48 (6.39,8.70) 7.48 (6.37,8.80) 7.58 (6.27,9.39) < 0.001 LDH (U/L) 372.25 (276.00, 538.00) 327.00 (256.00,441.50) 348.00 (267.00,481.00) 375.00 (285.00,531.00) 489.00 (327.75,750.00) < 0.001 Creatinine (µmol/L) 41.00 (35.00, 49.00) 39.50 (33.50,46.00) 39.00 (33.69,46.00) 40.00 (35.00,47.00) 47.00 (38.00,65.75) < 0.001 Urea (mmol/L) 3.30 (2.40, 4.43) 2.83 (2.07,3.67) 3.09 (2.29,3.86) 3.25 (2.42,4.21) 4.54 (3.27,6.64) < 0.001 Cystatin C (mg/L) 0.79 (0.64, 1.03) 0.71 (0.58,0.96) 0.74 (0.62,0.92) 0.79 (0.65,0.99) 0.93 (0.73,1.28) < 0.001 Length of ICU 1.97 (0.92, 5.88) 2.65 (0.93,7.87) 1.65 (0.90,4.00) 1.79 (0.91,4.73) 2.95 (0.99,6.98) < 0.001 In-hospital mortality < 0.001 No 6332 (94.71) 1610 (96.29) 1630 (97.55) 1612 (96.47) 1480 (88.52) Yes 354 (5.29) 62 (3.71) 41 (2.45) 59 (3.53) 192 (11.48) In-ICU mortality < 0.001 No 6343 (94.87) 1614 (96.53) 1632 (97.67) 1614 (96.59) 1483 (88.70) Yes 343 (5.13) 58 (3.47) 39 (2.33) 57 (3.41) 189 (11.30) 28-day ICU mortality < 0.001 No 6373 (95.32) 1624 (97.13) 1637 (97.97) 1621 (97.01) 1491 (89.17) Yes 313 (4.68) 48 (2.87) 34 (2.03) 50 (2.99) 181 (10.83) Notes : Data were presented as median (IQR), or n (%); UA conversion: 1mg/dL = 59.48 µmol/L, Alb conversion: 1 g/dL = 10 g/L. Association Between UAR and Mortality In the univariate logistic regression analysis, UAR demonstrated a significant association with an increased risk of in-hospital mortality (OR = 1.76, 95% CI: 1.63–1.90, P < 0.001) ( Table S2 ). Other significant predictors included gender, pneumonia, and various laboratory parameters such as monocyte count, sodium, potassium, and calcium ( Table S3 ). This positive association between UAR and mortality persisted after multivariable adjustment (Table 2 ). In the fully adjusted model (Model II), UAR remained an independent predictor of 28-day ICU mortality (OR = 1.25, 95% CI: 1.13–1.37, P < 0.001). When analyzed by quartiles, patients in the highest UAR quartile (Q4) had a markedly higher risk of 28-day ICU mortality compared to those in the lowest quartile (Q1) (OR = 1.94, 95% CI: 1.34–2.82, P < 0.001). Similar significant associations were consistently observed for the secondary outcomes of in-ICU and in-hospital mortality ( P for trend < 0.001). Table 2 Relationship between UAR and mortality in critically ill pediatric patients. Exposure Non-adjusted Model Ⅰ Model Ⅱ OR (95% CI) P OR (95% CI) P OR (95% CI) P 28-day ICU mortality UAR 1.757(1.629,1.898) <0.001 1.761(1.633,1.902) <0.001 1.249(1.133,1.372) <0.001 Q1 Ref Ref Ref Q2 0.703(0.447,1.092) 0.120 0.743(0.472,1.157) 0.193 0.761(0.479,1.195) 0.239 Q3 1.044(0.698,1.563) 0.835 1.092(0.729,1.638) 0.669 1.042(0.688,1.582) 0.845 Q4 4.107(2.991,5.747) <0.001 4.236(3.078,5.939) <0.001 1.935(1.343,2.822) <0.001 P for trend <0.001 <0.001 <0.001 in-ICU mortality UAR 1.702(1.581,1.835) <0.001 1.706(1.584,1.839) <0.001 1.203(1.091,1.321) <0.001 Q1 Ref Ref Ref Q2 0.665(0.438,1) 0.052 0.703(0.462,1.059) 0.095 0.727(0.474,1.106) 0.140 Q3 0.983(0.677,1.427) 0.927 1.03(0.708,1.498) 0.878 1.002(0.68,1.474) 0.994 Q4 3.546(2.638,4.837) <0.001 3.662(2.719,5.006) <0.001 1.73(1.227,2.461) 0.002 P for trend <0.001 <0.001 <0.001 in-hospital mortality UAR 1.758(1.63,1.899) <0.001 1.761(1.633,1.903) <0.001 0.742(0.472,1.155) <0.001 Q1 Ref Ref Ref Q2 0.703(0.447,1.092) 0.120 0.742(0.472,1.155) 0.190 1.09(0.728,1.635) 0.238 Q3 1.044(0.698,1.563) 0.835 1.09(0.728,1.635) 0.675 4.176(3.033,5.857) 0.844 Q4 4.056(2.953,5.678) <0.001 4.176(3.033,5.857) <0.001 0.742(0.472,1.155) 0.001 P for trend <0.001 <0.001 <0.001 Notes : Non-adjusted models: None; Model Ⅰ adjusted for: gender、pneumonia(yes/no); Model Ⅱ adjusted for: confounders in the minimally adjusted (Model Ⅰ) + monocyte count, sodium, potassium, calcium, lactate, DBIL, and glucose. Non-linear Relationship and Threshold Effect Analysis After adjusting for covariates, restricted cubic spline analysis revealed a non-linear, positive dose-response relationship between UAR and the risk of 28-day ICU mortality, in-ICU mortality, and in-hospital mortality (all P for non-linearity < 0.05) (Fig. 2 ). A two-piecewise linear regression model further identified a significant inflection point for UAR at 2.815 in relation to 28-day ICU mortality (Table 3 ). Below this threshold, the association between UAR and mortality was more pronounced, with a steeper increase in risk (OR = 1.95, 95% CI: 1.49–2.53, P < 0.001). Above the threshold, the association remained significant but was attenuated (OR = 1.19, 95% CI: 1.04–1.37, P = 0.011). Similar threshold effects were consistently identified for in-ICU and in-hospital mortality ( P for likelihood test < 0.05). Table 3 Threshold effect analysis of UAR on mortality using a two-piecewise linear regression model. OR (95% CI) P 28-day ICU mortality Inflection point 2.815 <2.815 1.945 (1.493–2.533) < 0.001 ≥2.815 1.193 (1.042–1.366) 0.011 P for likelihood test < 0.001 in-ICU mortality Inflection point 2.815 <2.815 1.783 (1.387–2.294) < 0.001 ≥2.815 1.177 (1.027–1.350) 0.019 P for likelihood test 0.001 in-hospital mortality Inflection point 2.818 <2.818 1.706 (1.331–2.186) < 0.001 ≥2.818 1.173 (1.024–1.343) 0.021 P for likelihood test 0.002 Survival Analysis and Predictive Performance The Kaplan-Meier survival curves demonstrated a significant gradient in 28-day survival probability across the four UAR quartiles, with patients in the highest quartile (Q4) exhibiting the lowest survival rate throughout the follow-up period ( P < 0.001) (Fig. 3 ). The ROC curve analysis was performed to assess the predictive value of UAR for mortality (Fig. 4 ). The AUC for UAR in predicting 28-day ICU mortality was 0.700 (95% CI: 0.664–0.736), which outperformed its individual components, UA (AUC = 0.685, 95% CI: 0.649–0.721) and Alb (AUC = 0.605, 95% CI: 0.568–0.642). This superior predictive performance of UAR was also observed for the outcomes of in-ICU and in-hospital mortality. Subgroup and Mediation Analysis In subgroup analyses, the positive association between UAR and 28-day ICU mortality remained robust and consistent across various strata, including age, gender, presence of congenital heart malformation, pneumonia, and sepsis (Fig. 5 ). Interaction tests revealed no significant effect modification by these variables (all P for interaction > 0.05), underscoring the stability of the association. The mediation analysis explored the potential role of lactate in the pathway from UAR to mortality (Fig. 6 ). The results indicated that lactate partially mediated the effect of UAR on 28-day ICU mortality, accounting for 35.180% of the total effect. Similarly, lactate was found to mediate 38.509% and 39.458% of the total effect of UAR on in-ICU and in-hospital mortality, respectively. Discussion To our knowledge, this study is the first to establish the uric acid to albumin ratio (UAR) as an independent prognostic biomarker for mortality in a large, diverse cohort of critically ill pediatric patients. Our primary finding is that an elevated UAR upon ICU admission is significantly associated with an increased risk of 28-day ICU, overall ICU, and in-hospital mortality. This relationship was characterized by a non-linear, positive dose-response pattern. Furthermore, we identified that lactate partially mediates this association, providing a crucial insight into the underlying pathophysiological pathways. These results position UAR as a simple, universally accessible, and potent tool for early risk stratification in the pediatric intensive care unit (PICU). The prognostic utility of UAR is increasingly recognized, though research has predominantly focused on adult populations across a spectrum of diseases. For instance, in heart failure patients, a high UAR was associated with a greater likelihood of 28-day mortality or hospital readmission (HR = 1.594, 95% CI: 1.032–2.462, P = 0.036). [ 15 ] This predictive capacity extends to other conditions, with UAR being an independent risk factor for mortality in diabetic patients (HR = 1.238, 95% CI: 1.120–1.369, P < 0.001), [ 16 ] and for renal progression in IgA nephropathy (HR = 2.56, 95% CI: 1.07–6.16, P = 0.036). [ 17 ] Our study aligns with this body of evidence by confirming UAR's prognostic significance but extends it for the first time to a broad, undifferentiated cohort of critically ill children, a population with distinct physiological responses. A notable point of comparison is the nature of the dose-response relationship. While many studies in specific adult disease cohorts report a linear association, [ 15 , 18 ] our finding of a non-linear pattern is not without precedent. A large-scale study by Wang et al. using the NHANES database on the general adult population also identified a J-shaped non-linear association between UAR and both all-cause and cardiovascular mortality. [ 19 ] In that study, UAR values exceeding the inflection point were strongly associated with increased all-cause mortality (HR = 2.11, 95% CI: 1.74–2.55, P < 0.01). [ 19 ] This concordance suggests that the non-linear relationship may be a more universal phenomenon, observable in large, heterogeneous populations, whereas linear trends might appear in more narrowly defined, high-risk subgroups. The prognostic power of UAR lies in its integration of two distinct but interconnected pathological processes. The numerator, UA, is widely regarded as a marker of oxidative stress and endothelial dysfunction. [ 20 – 22 ] Its production is intrinsically linked to the generation of reactive oxygen species during states of cellular injury and hypoxia. [ 23 ] Hypoalbuminemia is itself a robust predictor of mortality in critical illness. [ 24 , 25 ] Mechanistically, severe hypoalbuminemia precipitates tissue malperfusion by lowering plasma oncotic pressure, which promotes an interstitial fluid shift; this edematous state subsequently impairs microcirculatory oxygen delivery, triggering a cascade of anaerobic metabolism that drives lactate production. [ 26 – 28 ] This cascade provides an explanation for our finding that lactate partially mediates the relationship between UAR and mortality. A high UAR reflects a state of high oxidative stress and a pro-inflammatory milieu that compromises microcirculation, predisposing the patient to tissue hypoperfusion and a switch to anaerobic glycolysis. Therefore, UAR can be viewed as an upstream indicator of this vulnerability, while lactate is its direct downstream biochemical consequence. From a clinical standpoint, our findings are highly relevant. UAR is an inexpensive and universally available biomarker derived from standard laboratory tests. Its ability to predict 28-day ICU mortality (AUC = 0.700) offers a practical advantage for early risk assessment, surpassing the performance of either UA or albumin alone. The identification of a non-linear relationship with a specific inflection point (UAR ≈ 2.8) provides a data-driven threshold that could assist clinicians in categorizing patient risk more precisely. Patients presenting with a UAR above this threshold warrant heightened clinical vigilance and may benefit from more aggressive monitoring and therapeutic strategies. While its predictive accuracy is more modest than that of complex, multi-variable machine learning algorithms, the simplicity and cost-effectiveness of UAR make it an exceptionally attractive screening tool for routine clinical practice worldwide. This study possesses several strengths, including its large sample size derived from a high-quality clinical database and the application of robust statistical methods, such as non-linear modeling and mediation analysis. Nevertheless, certain limitations must be acknowledged. The retrospective, single-center nature of the study may limit the generalizability of our findings and leaves it susceptible to unmeasured confounding factors. We analyzed UAR only at a single time point upon admission, thus the prognostic significance of its dynamic changes over the course of the ICU stay remains unexplored. As an observational study, we can only establish a strong association, not a causal link, between UAR and mortality. Future prospective, multi-center studies are essential to validate these findings and to explore the potential of UAR-guided interventions. Conclusion In conclusion, our study identifies the Uric Acid to Albumin Ratio (UAR) as a novel, independent, and robust predictor of mortality in the critically ill pediatric population. This association is non-linear and is significantly mediated by lactate, reflecting a confluence of oxidative stress, inflammation, and profound metabolic failure. Given its simplicity and accessibility, UAR holds considerable promise as a valuable biomarker to enhance the early identification and management of high-risk children in the ICU. Abbreviations Alb Albumin ALT alanine aminotransferase AST aspartate aminotransferase DBIL direct bilirubin HCT hematocrit IBIL indirect bilirubin ICU intensive care unit INR international normalized ratio LDH lactate dehydrogenase PIC Pediatric Intensive Care PICU pediatric intensive care unit PLT platelet PT Prothrombin time PTT partial thromboplastin time RBC Red blood cell RDW red cell distribution width TG Triglycerides UA uric acid UAR uric acid to albumin ratio WBC White blood cell Declarations Availability of data and materials The data were available on the Pediatric Intensive Care database website at http://pic.nbscn.org. Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of the Children’s Hospital, Zhejiang University School of Medicine (Hangzhou, China). The committee waived the requirement for written informed consent from participants, as the study involved a retrospective analysis of fully de-identified data. Competing interests The authors declare that they have no competing interests in this section. Author Contributions Conceptualization, Z.Z.; Data analysis, Z.Z. and Q.L.; Writing – Original Draft, Z.Z. and Q.L.; Writing – Review & Editing, Z.Z. and Q.L. All authors have read and agreed to the published version of the manuscript. Acknowledgment We acknowledge the contributions of all staff who participated in the construction and maintenance of the PIC database. Clinical trial not applicable. Consent to Publish declaration not applicable. Funding This study was funded by Research project of Zigong City Science & Technology and Intellectual Property Right Bureau (2023-YGY-3-04). References Pollack MM, Patel KM, Ruttimann UE. PRISM III: an updated Pediatric Risk of Mortality score. Crit Care Med. 1996;24(5):743–52. Slater A, Shann F, Pearson G. PIM2: a revised version of the Paediatric Index of Mortality. Intensive Care Med. 2003;29(2):278–85. Thukral A, Lodha R, Irshad M, Arora NK. Performance of Pediatric Risk of Mortality (PRISM), Pediatric Index of Mortality (PIM), and PIM2 in a pediatric intensive care unit in a developing country. Pediatr Crit care medicine: J Soc Crit Care Med World Federation Pediatr Intensive Crit Care Soc. 2006;7(4):356–61. Borghi C, Fogacci F, Cicero AF. Crystal clear - part I: The role of uric acid in cardiorenal disease. Eur J Intern Med 2025. Pinz MP, Medeiros I, Carvalho L, Meotti FC. Is uric acid a true antioxidant? 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Intensive Care Med. 2016;42(12):2077–9. Additional Declarations No competing interests reported. Supplementary Files Additionalfile.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 25 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers invited by journal 12 Sep, 2025 Editor assigned by journal 10 Sep, 2025 Editor invited by journal 19 Aug, 2025 Submission checks completed at journal 18 Aug, 2025 First submitted to journal 18 Aug, 2025 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. 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1","display":"","copyAsset":false,"role":"figure","size":168539,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram of the patient selection process.\u003c/strong\u003e\u003cbr\u003e\n \u003cstrong\u003eAbbreviations:\u003c/strong\u003e ICU, intensive care unit; Q, quartile.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/b7a07fc894f5d890270b4f36.jpg"},{"id":91935055,"identity":"1cb3cf0c-710b-42f7-8b14-f1c89f0a2351","added_by":"auto","created_at":"2025-09-23 02:42:19","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":141109,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDose-response relationship between UAR and mortality.\u003c/strong\u003e\u003cbr\u003e\n \u003cstrong\u003e(A)\u003c/strong\u003e Restricted cubic spline for 28-day ICU mortality. \u003cstrong\u003e(B)\u003c/strong\u003e Restricted cubic spline for in-ICU mortality. \u003cstrong\u003e(C)\u003c/strong\u003e Restricted cubic spline for in-hospital mortality.\u003cbr\u003e\n \u003cstrong\u003eAbbreviations:\u003c/strong\u003e UAR, uric acid to albumin ratio; OR, odds ratio; CI, confidence interval.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/d89af5c518be053abff01215.jpg"},{"id":91936520,"identity":"aed92b6c-e1f9-4976-bada-1cef3d229df6","added_by":"auto","created_at":"2025-09-23 02:50:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":181565,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier survival curves for patients stratified by UAR quartiles.\u003c/strong\u003e\u003cbr\u003e\nThe plot shows the 28-day ICU survival probability. \u003cbr\u003e\n \u003cstrong\u003eAbbreviations:\u003c/strong\u003e UAR, uric acid to albumin ratio; Q, quartile.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/5e61561cf5b97a8fe2d09ee5.jpg"},{"id":91935062,"identity":"ff0956a5-1642-47bc-a484-eee2a8fba112","added_by":"auto","created_at":"2025-09-23 02:42:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":300266,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic (ROC) curves for predicting 28-day ICU mortality.\u003c/strong\u003e\u003cbr\u003e\n \u003cstrong\u003e(A)\u003c/strong\u003e ROC curve for UAR. \u003cstrong\u003e(B)\u003c/strong\u003e ROC curve for UA. \u003cstrong\u003e(C)\u003c/strong\u003e ROC curve for Alb.\u003cbr\u003e\n \u003cstrong\u003eAbbreviations:\u003c/strong\u003e ROC, receiver operating characteristic; ICU, intensive care unit; UAR, uric acid to albumin ratio; UA, uric acid; Alb, albumin.\u003c/p\u003e","description":"","filename":"14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/c9efccf6e48c2506b2db001d.jpg"},{"id":91935059,"identity":"c19c3163-ef84-4471-a6cf-cfb42b62c6ef","added_by":"auto","created_at":"2025-09-23 02:42:19","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":348417,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubgroup analyses of the association between UAR and mortality.\u003c/strong\u003e\u003cbr\u003e\n \u003cstrong\u003e(A)\u003c/strong\u003e Forest plot for 28-day ICU mortality. \u003cstrong\u003e(B)\u003c/strong\u003e Forest plot for in-ICU mortality. \u003cstrong\u003e(C)\u003c/strong\u003e Forest plot for in-hospital mortality.\u003cbr\u003e\n \u003cstrong\u003eAbbreviations:\u003c/strong\u003e OR, odds ratio; CI, confidence interval; UAR, uric acid to albumin ratio; ICU, intensive care unit.\u003c/p\u003e","description":"","filename":"15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/9ffed311f16d9a8b517ba0ac.jpg"},{"id":91937535,"identity":"3679603f-03ec-4ff4-a574-4aeb1ca2532b","added_by":"auto","created_at":"2025-09-23 02:58:19","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":250678,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMediation analysis of lactate in the association between UAR and mortality outcomes.\u003c/strong\u003e\u003cbr\u003e\n \u003cstrong\u003eNote:\u003c/strong\u003e * indicates \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003cbr\u003e\n \u003cstrong\u003eAbbreviations:\u003c/strong\u003e UAR, uric acid to albumin ratio; ICU, intensive care unit.\u003c/p\u003e","description":"","filename":"16.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/704bb7adfda3baf17f94629b.jpg"},{"id":91939510,"identity":"aace335b-cefe-47a3-abdd-314fdd27b4e4","added_by":"auto","created_at":"2025-09-23 03:14:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3061160,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/2de77e23-7f12-4e87-badd-f63de1057239.pdf"},{"id":91936519,"identity":"0c001981-ad56-47d0-8bdb-83fd80e8784f","added_by":"auto","created_at":"2025-09-23 02:50:19","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":37610,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7328002/v1/925c7fb2d065b531e8f69fff.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Non-linear Relationship between Uric Acid to Albumin Ratio and Mortality in Pediatric Intensive Care Unit Patients: A Large-Scale Observational Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Accurate and early risk stratification is a cornerstone of modern pediatric intensive care, fundamentally guiding clinical interventions and resource allocation to improve survival rates for critically ill children. This population is uniquely vulnerable, often presenting with complex and rapidly evolving pathophysiological states. While established scoring systems are integral to clinical practice, they rely on a multitude of variables that can be cumbersome to collect and may not fully encapsulate the underlying biological turmoil.\u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn the search for such markers, uric acid (UA), the end-product of purine metabolism, is now understood to be more than a simple metabolic waste product. Its elevation often signals accelerated cellular turnover and ATP degradation under conditions of tissue hypoxia and ischemia, positioning it as a key indicator of systemic oxidative stress and endothelial dysfunction.\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e Concurrently, serum albumin, a negative acute-phase reactant, is a well-established marker of the body's inflammatory response, nutritional status, and overall physiological reserve. Consequently, hypoalbuminemia has been robustly identified as an independent predictor of mortality in various critically ill cohorts, including pediatric patients.\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eGiven the distinct yet interconnected pathways these two markers represent, the uric acid to albumin ratio (UAR) has recently been proposed as a novel, integrated biomarker. This composite index has already demonstrated considerable prognostic utility in adult critical care. For instance, an elevated UAR has been independently associated with increased all-cause mortality in adults with coronary artery disease,\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e and acute kidney injury.\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eDespite this compelling evidence in adult medicine, the clinical significance and prognostic value of UAR in the pediatric intensive care unit (PICU) remain largely uninvestigated. However, children exhibit distinct metabolic profiles and physiological responses to severe illness, which precludes the direct extrapolation of findings from adult populations. \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e Therefore, this large-scale observational study aimed to investigate the association between the admission UAR and mortality in a broad cohort of PICU patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Data Source\u003c/h2\u003e\u003cp\u003eThis retrospective cohort study was based on data from the Pediatric Intensive Care (PIC) database, a large, single-center electronic medical record database developed by the Children\u0026rsquo;s Hospital, Zhejiang University School of Medicine (ZUCH).\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e The PIC database contains comprehensive, anonymized clinical data from 12,881 pediatric patients admitted to various intensive care units (ICUs) at ZUCH between 2010 and 2018. The study protocol was approved by the Ethics Committee of ZUCH, and the requirement for individual informed consent was waived due to the retrospective nature of the analysis and the de-identification of all patient data.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThe study cohort was derived from the PIC database. For individuals with multiple ICU admissions, only data from the initial admission were incorporated into the analysis. The exclusion criteria were as follows: (1) age\u0026thinsp;\u0026lt;\u0026thinsp;28 days (neonates), and (2) absence of baseline measurements for either UA or Alb.\u003c/p\u003e\n\u003ch3\u003eData Collection and Definitions\u003c/h3\u003e\n\u003cp\u003eWe extracted a comprehensive set of data for each patient within the first 24 hours of ICU admission, categorized as follows: Baseline Demographics: age and gender. Comorbidities: presence of congenital malformation of the heart, pneumonia, sepsis, and history of preterm birth. Laboratory Parameters: White blood cell (WBC) count, neutrophil count, lymphocyte count, monocyte count, red blood cell (RBC) count, platelet (PLT) count, hemoglobin, red cell distribution width (RDW), and hematocrit (HCT). Renal and Metabolic Panel: Uric acid (UA), sodium, potassium, total calcium, chloride, calculated bicarbonate, lactate, glucose, creatinine, urea, and cystatin C. Liver Function and Protein Panel: Albumin (Alb), globulin, direct bilirubin (DBIL), indirect bilirubin (IBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH). Coagulation Profile: Prothrombin time (PT), partial thromboplastin time (PTT), and international normalized ratio (INR). Lipid Panel: Triglycerides (TG) and total cholesterol. The primary exposure variable, the Uric Acid to Albumin Ratio (UAR), was calculated using the formula: UAR\u0026thinsp;=\u0026thinsp;UA (mg/dL) / Alb (g/dL). The primary outcome for this study was 28-day ICU mortality. Secondary outcomes included in-ICU mortality and in-hospital mortality.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were presented as median and interquartile range (IQR) given their non-normal distribution, while categorical variables were reported as numbers and percentages (n, %). Patients were stratified into four groups based on quartiles of their baseline UAR. The Kruskal-Wallis test and the chi-square test were used to compare differences in continuous and categorical variables across UAR quartiles, respectively. Variables with more than 20% missing data were excluded from the analysis.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e To robustly handle the remaining missing values, we employed a multiple imputation technique. Potential confounders were initially screened using univariate logistic regression. Variables with a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were selected for inclusion in the multivariable models.\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e To mitigate multicollinearity, the variance inflation factor (VIF) was calculated, and variables with a VIF\u0026thinsp;\u0026gt;\u0026thinsp;5 were excluded.\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e Multivariable logistic regression was then performed to assess the independent association between UAR (as both a continuous and a categorical variable) and mortality outcomes. Three models were constructed: a non-adjusted model; Model I, adjusted for gender and pneumonia; and Model II (the fully-adjusted model), which further adjusted for covariates in Model I plus monocyte count, sodium, potassium, calcium, lactate, DBIL, and glucose. Results were presented as odds ratios (OR) with 95% confidence intervals (CI). To explore the potential non-linear relationship between UAR and mortality, we utilized restricted cubic splines (RCS). If non-linearity was detected, a two-piecewise linear regression model was applied to identify any threshold effects. The predictive capacity of UAR for mortality was assessed using the area under the receiver operating characteristic curve (AUC) and compared with that of UA and Alb alone. Kaplan-Meier curves were plotted to visualize survival differences among UAR quartiles, with the log-rank test used for comparison. To ensure the robustness of our findings, subgroup analyses were conducted across strata of age, gender, pneumonia, preterm infants, congenital malformation of heart, and sepsis. Finally, a mediation analysis was performed to investigate whether lactate mediated the relationship between UAR and mortality outcomes. All statistical analyses were conducted using R software (version 4.4.1), and P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eBaseline Characteristics of the Study Population\u003c/h2\u003e\u003cp\u003eThis study ultimately included 6,686 critically ill pediatric patients, with the selection process detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The cohort had a median age of 1.0 years, with 50.10% being infants (\u0026le;\u0026thinsp;1 year old) and 55.49% being male. The overall 28-day ICU mortality rate was 4.68%. Baseline characteristics stratified by UAR quartiles are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Patients in the highest UAR quartile (Q4) were characterized by a younger age distribution and a higher prevalence of comorbidities, including congenital malformation of the heart (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and sepsis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, the Q4 group exhibited a profile indicative of greater inflammation and metabolic derangement, with significantly elevated levels of WBC, monocyte count, RDW, lactate, PT, PTT, INR, and urea, alongside lower levels of platelets and bicarbonate (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Correspondingly, patients in the Q4 group experienced significantly higher rates of 28-day ICU, overall ICU, and in-hospital mortality, as well as a longer ICU stay (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\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\u003eBaseline characteristics of the study cohort stratified by UAR quartiles.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6686)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQ1 (\u0026lt;\u0026thinsp;0.865)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1672)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQ2 (0.895\u0026ndash;1.174)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1671)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eQ3 (1.174\u0026ndash;1.537)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1671)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eQ4 (\u0026gt;\u0026thinsp;1.537)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1672)\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\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eBaseline characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\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\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\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3350 (50.10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e709 (42.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e790 (47.28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e921 (55.12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e930 (55.62%)\u003c/p\u003e\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\u003e\u0026gt;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3336 (49.90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e963 (57.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e881 (52.72%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e750 (44.88%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e742 (44.38%)\u003c/p\u003e\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\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3710 (55.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e893 (53.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e883 (52.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e953 (57.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e981 (58.67%)\u003c/p\u003e\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\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2976 (44.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e779 (46.59%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e788 (47.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e718 (42.97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e691 (41.33%)\u003c/p\u003e\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\u003e\u003cb\u003eComorbidities\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\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCongenital malformation of heart\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6396 (95.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1620 (96.89%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1602 (95.87%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1591 (95.21%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1583 (94.68%)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e290 (4.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52 (3.11%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69 (4.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e80 (4.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e89 (5.32%)\u003c/p\u003e\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\u003ePneumonia\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\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\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\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6225 (93.10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1516 (90.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1580 (94.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1577 (94.37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1552 (92.82%)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e461 (6.90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e156 (9.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e91 (5.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e94 (5.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e120 (7.18%)\u003c/p\u003e\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\u003eSepsis\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\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\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\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6565 (98.19%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1653 (98.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1654 (98.98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1657 (99.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1601 (95.75%)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e121 (1.81%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (1.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17 (1.02%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14 (0.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e71 (4.25%)\u003c/p\u003e\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\u003ePreterm infants\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\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\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\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6585 (98.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1598 (95.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1652 (98.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1666 (99.70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1669 (99.82%)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101 (1.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74 (4.43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19 (1.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5 (0.30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3 (0.18%)\u003c/p\u003e\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\u003e\u003cb\u003eLaboratory tests\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\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\u003eUA (mg/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.44 (3.39, 5.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.76 (2.20,3.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.00 (3.58,4.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.02 (4.54,5.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.11 (6.08,9.12)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlb(g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.79 (3.40, 4.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.89 (3.50,4.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.88 (3.53,4.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.79 (3.45,4.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.56 (3.11,3.96)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.17 (0.89, 1.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73 (0.60,0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.04 (0.97,1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.32 (1.25,1.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.95 (1.69,2.61)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC (10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.67 (7.78, 14.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.93 (7.91,14.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.67 (8.02,13.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.30 (7.76,13.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.84 (7.57,14.66)\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\u003eNeutrophil count (10⁹/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.47 (4.73, 10.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.67 (4.41,10.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.64 (4.99,10.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.21 (4.85,9.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.46 (4.67,10.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphocyte count (10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.12 (1.43, 3.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.12 (1.43,3.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.09 (1.41,2.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.11 (1.44,2.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.18 (1.44,3.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonocyte count (10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.59 (0.41, 0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.61 (0.43,0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.59 (0.41,0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.57 (0.39,0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.60 (0.38,0.81)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBC (10^12/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.83 (3.41, 4.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.83 (3.41,4.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.85 (3.46,4.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.88 (3.46,4.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.80 (3.27,4.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT (10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e260.00 (180.50, 347.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e276.75 (199.38,362.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e266.50 (197.00,356.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e258.50 (186.00,349.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e226.25 (141.92,317.50)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e106.00 (94.67, 117.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e106.04 (96.50,118.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e106.04 (96.00,117.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e106.00 (96.00,117.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e104.00 (91.00,116.00)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRDW (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13.70 (12.83, 14.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.50 (12.70,14.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.53 (12.75,14.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13.65 (12.85,14.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.09 (13.15,15.40)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCT (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.20 (28.85, 35.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32.30 (29.30,35.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.21 (29.23,35.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32.21 (29.00,35.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e31.60 (27.80,35.50)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSodium (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e137.20 (135.30, 139.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e137.00 (135.00,138.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e137.00 (135.50,138.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e137.29 (135.67,139.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e137.50 (135.00,140.10)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePotassium (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.70 (3.49, 3.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.70 (3.48,3.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.70 (3.49,3.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.70 (3.50,3.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.70 (3.47,4.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.201\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalcium (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.20 (1.15, 1.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.20 (1.15,1.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.21 (1.17,1.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.21 (1.16,1.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.18 (1.09,1.24)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChloride (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e109.00 (106.00, 111.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e108.33 (105.19,110.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e109.00 (106.50,111.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e109.71 (106.80,112.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e109.00 (105.50,112.17)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBicarbonate (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.91 (20.36, 23.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22.50 (21.07,24.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.96 (20.65,23.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.85 (20.45,23.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e21.17 (19.06,22.99)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLactate (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.62 (1.20, 2.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.60 (1.20,2.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.59 (1.20,2.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.55 (1.18,2.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.81 (1.29,2.85)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePT (sec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.80 (11.70, 11.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.80 (11.70,11.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.80 (11.70,11.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.80 (11.70,11.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11.80 (11.66,12.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.247\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePTT (sec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33.80 (28.36, 38.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33.10 (27.80,36.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.50 (27.98,37.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e33.60 (28.60,39.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e36.40 (29.49,44.80)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.12 (1.01, 1.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.07 (0.99,1.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.09 (1.00,1.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.11 (1.02,1.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.17 (1.05,1.33)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTG (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.77 (0.55, 1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.78 (0.54,1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.74 (0.54,1.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.71 (0.52,1.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.87 (0.59,1.36)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCholesterol total (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.05 (2.36, 3.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.25 (2.56,3.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.13 (2.52,3.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.01 (2.38,3.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.72 (2.04,3.49)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBIL (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.60 (1.60, 4.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.60 (1.55,4.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.40 (1.60,4.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.60 (1.70,4.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.00 (1.70,6.00)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBIL (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.20 (4.50, 12.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.40 (4.50,12.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.30 (4.90,12.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.40 (4.60,11.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.70 (3.90,12.20)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALT (U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.00 (13.00, 32.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.00 (12.00,29.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.00 (12.00,28.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.00 (13.00,28.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e24.00 (14.46,55.12)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAST (U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47.00 (30.00, 87.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.00 (27.00,64.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44.00 (29.25,77.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e47.00 (32.00,82.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e69.00 (37.00,146.00)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlobulin (g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.23 (15.70, 23.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.50 (16.38,24.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.60 (15.90,23.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.80 (15.70,22.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e18.40 (15.10,22.56)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlucose (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.43 (6.28, 8.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.15 (6.10,8.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.48 (6.39,8.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.48 (6.37,8.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.58 (6.27,9.39)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDH (U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e372.25 (276.00, 538.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e327.00 (256.00,441.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e348.00 (267.00,481.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e375.00 (285.00,531.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e489.00 (327.75,750.00)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41.00 (35.00, 49.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.50 (33.50,46.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e39.00 (33.69,46.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00 (35.00,47.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e47.00 (38.00,65.75)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrea (mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.30 (2.40, 4.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.83 (2.07,3.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.09 (2.29,3.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.25 (2.42,4.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.54 (3.27,6.64)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCystatin C (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.79 (0.64, 1.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.71 (0.58,0.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.74 (0.62,0.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.79 (0.65,0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.93 (0.73,1.28)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLength of ICU\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.97 (0.92, 5.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.65 (0.93,7.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.65 (0.90,4.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.79 (0.91,4.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.95 (0.99,6.98)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIn-hospital mortality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c7\"\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\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6332 (94.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1610 (96.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1630 (97.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1612 (96.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1480 (88.52)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e354 (5.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62 (3.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41 (2.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e59 (3.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e192 (11.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIn-ICU mortality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c7\"\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\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6343 (94.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1614 (96.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1632 (97.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1614 (96.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1483 (88.70)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e343 (5.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58 (3.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e39 (2.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57 (3.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e189 (11.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e28-day ICU mortality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c7\"\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\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6373 (95.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1624 (97.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1637 (97.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1621 (97.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1491 (89.17)\u003c/p\u003e\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\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e313 (4.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e48 (2.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34 (2.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e50 (2.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e181 (10.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Data were presented as median (IQR), or n (%); UA conversion: 1mg/dL\u0026thinsp;=\u0026thinsp;59.48 \u0026micro;mol/L, Alb conversion: 1 g/dL\u0026thinsp;=\u0026thinsp;10 g/L.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssociation Between UAR and Mortality\u003c/h3\u003e\n\u003cp\u003eIn the univariate logistic regression analysis, UAR demonstrated a significant association with an increased risk of in-hospital mortality (OR\u0026thinsp;=\u0026thinsp;1.76, 95% CI: 1.63\u0026ndash;1.90, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eTable S2\u003c/b\u003e). Other significant predictors included gender, pneumonia, and various laboratory parameters such as monocyte count, sodium, potassium, and calcium (\u003cb\u003eTable S3\u003c/b\u003e). This positive association between UAR and mortality persisted after multivariable adjustment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the fully adjusted model (Model II), UAR remained an independent predictor of 28-day ICU mortality (OR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 1.13\u0026ndash;1.37, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When analyzed by quartiles, patients in the highest UAR quartile (Q4) had a markedly higher risk of 28-day ICU mortality compared to those in the lowest quartile (Q1) (OR\u0026thinsp;=\u0026thinsp;1.94, 95% CI: 1.34\u0026ndash;2.82, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similar significant associations were consistently observed for the secondary outcomes of in-ICU and in-hospital mortality (\u003cem\u003eP\u003c/em\u003e for trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eRelationship between UAR and mortality in critically ill pediatric patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eExposure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eNon-adjusted\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eModel Ⅰ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eModel Ⅱ\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e28-day ICU mortality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.757(1.629,1.898)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.761(1.633,1.902)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.249(1.133,1.372)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\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\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.703(0.447,1.092)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.743(0.472,1.157)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.761(0.479,1.195)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.239\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.044(0.698,1.563)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.092(0.729,1.638)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.042(0.688,1.582)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.845\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.107(2.991,5.747)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.236(3.078,5.939)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.935(1.343,2.822)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ein-ICU mortality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.702(1.581,1.835)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.706(1.584,1.839)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.203(1.091,1.321)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\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\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.665(0.438,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.703(0.462,1.059)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.727(0.474,1.106)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.140\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.983(0.677,1.427)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.03(0.708,1.498)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.002(0.68,1.474)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.546(2.638,4.837)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.662(2.719,5.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.73(1.227,2.461)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ein-hospital mortality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.758(1.63,1.899)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.761(1.633,1.903)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.742(0.472,1.155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\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\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.703(0.447,1.092)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.742(0.472,1.155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.09(0.728,1.635)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.238\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.044(0.698,1.563)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.09(0.728,1.635)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.176(3.033,5.857)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.844\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.056(2.953,5.678)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.176(3.033,5.857)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.742(0.472,1.155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Non-adjusted models: None; Model Ⅰ adjusted for: gender、pneumonia(yes/no);\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel Ⅱ adjusted for: confounders in the minimally adjusted (Model Ⅰ)\u0026thinsp;+\u0026thinsp;monocyte count, sodium, potassium, calcium, lactate, DBIL, and glucose.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eNon-linear Relationship and Threshold Effect Analysis\u003c/h3\u003e\n\u003cp\u003eAfter adjusting for covariates, restricted cubic spline analysis revealed a non-linear, positive dose-response relationship between UAR and the risk of 28-day ICU mortality, in-ICU mortality, and in-hospital mortality (all \u003cem\u003eP\u003c/em\u003e for non-linearity\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A two-piecewise linear regression model further identified a significant inflection point for UAR at 2.815 in relation to 28-day ICU mortality (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Below this threshold, the association between UAR and mortality was more pronounced, with a steeper increase in risk (OR\u0026thinsp;=\u0026thinsp;1.95, 95% CI: 1.49\u0026ndash;2.53, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Above the threshold, the association remained significant but was attenuated (OR\u0026thinsp;=\u0026thinsp;1.19, 95% CI: 1.04\u0026ndash;1.37, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011). Similar threshold effects were consistently identified for in-ICU and in-hospital mortality (\u003cem\u003eP\u003c/em\u003e for likelihood test\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\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\u003eThreshold effect analysis of UAR on mortality using a two-piecewise linear regression model.\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\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e28-day ICU mortality\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\"\u003e\u003cp\u003eInflection point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.815\u003c/p\u003e\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\"\u003e\u003cp\u003e\u0026lt;2.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.945 (1.493\u0026ndash;2.533)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;2.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.193 (1.042\u0026ndash;1.366)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for likelihood test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ein-ICU mortality\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\"\u003e\u003cp\u003eInflection point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.815\u003c/p\u003e\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\"\u003e\u003cp\u003e\u0026lt;2.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.783 (1.387\u0026ndash;2.294)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;2.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.177 (1.027\u0026ndash;1.350)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for likelihood test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ein-hospital mortality\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\"\u003e\u003cp\u003eInflection point\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.818\u003c/p\u003e\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\"\u003e\u003cp\u003e\u0026lt;2.818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.706 (1.331\u0026ndash;2.186)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;2.818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.173 (1.024\u0026ndash;1.343)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for likelihood test\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSurvival Analysis and Predictive Performance\u003c/h2\u003e\u003cp\u003eThe Kaplan-Meier survival curves demonstrated a significant gradient in 28-day survival probability across the four UAR quartiles, with patients in the highest quartile (Q4) exhibiting the lowest survival rate throughout the follow-up period (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The ROC curve analysis was performed to assess the predictive value of UAR for mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The AUC for UAR in predicting 28-day ICU mortality was 0.700 (95% CI: 0.664\u0026ndash;0.736), which outperformed its individual components, UA (AUC\u0026thinsp;=\u0026thinsp;0.685, 95% CI: 0.649\u0026ndash;0.721) and Alb (AUC\u0026thinsp;=\u0026thinsp;0.605, 95% CI: 0.568\u0026ndash;0.642). This superior predictive performance of UAR was also observed for the outcomes of in-ICU and in-hospital mortality.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup and Mediation Analysis\u003c/h2\u003e\u003cp\u003eIn subgroup analyses, the positive association between UAR and 28-day ICU mortality remained robust and consistent across various strata, including age, gender, presence of congenital heart malformation, pneumonia, and sepsis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Interaction tests revealed no significant effect modification by these variables (all \u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05), underscoring the stability of the association. The mediation analysis explored the potential role of lactate in the pathway from UAR to mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The results indicated that lactate partially mediated the effect of UAR on 28-day ICU mortality, accounting for 35.180% of the total effect. Similarly, lactate was found to mediate 38.509% and 39.458% of the total effect of UAR on in-ICU and in-hospital mortality, respectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this study is the first to establish the uric acid to albumin ratio (UAR) as an independent prognostic biomarker for mortality in a large, diverse cohort of critically ill pediatric patients. Our primary finding is that an elevated UAR upon ICU admission is significantly associated with an increased risk of 28-day ICU, overall ICU, and in-hospital mortality. This relationship was characterized by a non-linear, positive dose-response pattern. Furthermore, we identified that lactate partially mediates this association, providing a crucial insight into the underlying pathophysiological pathways. These results position UAR as a simple, universally accessible, and potent tool for early risk stratification in the pediatric intensive care unit (PICU).\u003c/p\u003e\u003cp\u003eThe prognostic utility of UAR is increasingly recognized, though research has predominantly focused on adult populations across a spectrum of diseases. For instance, in heart failure patients, a high UAR was associated with a greater likelihood of 28-day mortality or hospital readmission (HR\u0026thinsp;=\u0026thinsp;1.594, 95% CI: 1.032\u0026ndash;2.462, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036).\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e This predictive capacity extends to other conditions, with UAR being an independent risk factor for mortality in diabetic patients (HR\u0026thinsp;=\u0026thinsp;1.238, 95% CI: 1.120\u0026ndash;1.369, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001),\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e and for renal progression in IgA nephropathy (HR\u0026thinsp;=\u0026thinsp;2.56, 95% CI: 1.07\u0026ndash;6.16, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036).\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e Our study aligns with this body of evidence by confirming UAR's prognostic significance but extends it for the first time to a broad, undifferentiated cohort of critically ill children, a population with distinct physiological responses.\u003c/p\u003e\u003cp\u003eA notable point of comparison is the nature of the dose-response relationship. While many studies in specific adult disease cohorts report a linear association,\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e our finding of a non-linear pattern is not without precedent. A large-scale study by Wang et al. using the NHANES database on the general adult population also identified a J-shaped non-linear association between UAR and both all-cause and cardiovascular mortality.\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e In that study, UAR values exceeding the inflection point were strongly associated with increased all-cause mortality (HR\u0026thinsp;=\u0026thinsp;2.11, 95% CI: 1.74\u0026ndash;2.55, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e This concordance suggests that the non-linear relationship may be a more universal phenomenon, observable in large, heterogeneous populations, whereas linear trends might appear in more narrowly defined, high-risk subgroups.\u003c/p\u003e\u003cp\u003eThe prognostic power of UAR lies in its integration of two distinct but interconnected pathological processes. The numerator, UA, is widely regarded as a marker of oxidative stress and endothelial dysfunction. \u003csup\u003e[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e Its production is intrinsically linked to the generation of reactive oxygen species during states of cellular injury and hypoxia.\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e Hypoalbuminemia is itself a robust predictor of mortality in critical illness.\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e Mechanistically, severe hypoalbuminemia precipitates tissue malperfusion by lowering plasma oncotic pressure, which promotes an interstitial fluid shift; this edematous state subsequently impairs microcirculatory oxygen delivery, triggering a cascade of anaerobic metabolism that drives lactate production.\u003csup\u003e[\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e This cascade provides an explanation for our finding that lactate partially mediates the relationship between UAR and mortality. A high UAR reflects a state of high oxidative stress and a pro-inflammatory milieu that compromises microcirculation, predisposing the patient to tissue hypoperfusion and a switch to anaerobic glycolysis. Therefore, UAR can be viewed as an upstream indicator of this vulnerability, while lactate is its direct downstream biochemical consequence.\u003c/p\u003e\u003cp\u003eFrom a clinical standpoint, our findings are highly relevant. UAR is an inexpensive and universally available biomarker derived from standard laboratory tests. Its ability to predict 28-day ICU mortality (AUC\u0026thinsp;=\u0026thinsp;0.700) offers a practical advantage for early risk assessment, surpassing the performance of either UA or albumin alone. The identification of a non-linear relationship with a specific inflection point (UAR\u0026thinsp;\u0026asymp;\u0026thinsp;2.8) provides a data-driven threshold that could assist clinicians in categorizing patient risk more precisely. Patients presenting with a UAR above this threshold warrant heightened clinical vigilance and may benefit from more aggressive monitoring and therapeutic strategies. While its predictive accuracy is more modest than that of complex, multi-variable machine learning algorithms, the simplicity and cost-effectiveness of UAR make it an exceptionally attractive screening tool for routine clinical practice worldwide.\u003c/p\u003e\u003cp\u003eThis study possesses several strengths, including its large sample size derived from a high-quality clinical database and the application of robust statistical methods, such as non-linear modeling and mediation analysis. Nevertheless, certain limitations must be acknowledged. The retrospective, single-center nature of the study may limit the generalizability of our findings and leaves it susceptible to unmeasured confounding factors. We analyzed UAR only at a single time point upon admission, thus the prognostic significance of its dynamic changes over the course of the ICU stay remains unexplored. As an observational study, we can only establish a strong association, not a causal link, between UAR and mortality. Future prospective, multi-center studies are essential to validate these findings and to explore the potential of UAR-guided interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our study identifies the Uric Acid to Albumin Ratio (UAR) as a novel, independent, and robust predictor of mortality in the critically ill pediatric population. This association is non-linear and is significantly mediated by lactate, reflecting a confluence of oxidative stress, inflammation, and profound metabolic failure. Given its simplicity and accessibility, UAR holds considerable promise as a valuable biomarker to enhance the early identification and management of high-risk children in the ICU.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAlb\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlbumin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eALT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ealanine aminotransferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAST\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003easpartate aminotransferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDBIL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003edirect bilirubin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHCT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehematocrit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIBIL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eindirect bilirubin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eintensive care unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eINR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003einternational normalized ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elactate dehydrogenase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePIC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePediatric Intensive Care\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epediatric intensive care unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eplatelet\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProthrombin time\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePTT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epartial thromboplastin time\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRed blood cell\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRDW\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ered cell distribution width\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTriglycerides\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003euric acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUAR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003euric acid to albumin ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWhite blood cell\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe data were available on the Pediatric Intensive Care database website at \u0026nbsp;http://pic.nbscn.org.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and was approved by the\u0026nbsp;Institutional Review Board of the Children\u0026rsquo;s Hospital, Zhejiang University School of Medicine (Hangzhou, China). The committee waived the requirement for written informed consent from participants, as the study involved a retrospective analysis of fully de-identified data.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests in this section.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eConceptualization, Z.Z.; Data analysis, Z.Z. and Q.L.; Writing \u0026ndash; Original Draft, Z.Z. and Q.L.; Writing \u0026ndash; Review \u0026amp; Editing, Z.Z. and Q.L. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgment\u003c/p\u003e\n\u003cp\u003eWe acknowledge the contributions of all staff who participated in the construction and maintenance of the PIC database.\u003c/p\u003e\n\u003cp\u003eClinical trial\u0026nbsp;\u003c/p\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003cp\u003eConsent to Publish declaration\u003c/p\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study was funded by Research project of Zigong City Science \u0026amp; Technology and Intellectual Property Right Bureau (2023-YGY-3-04).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePollack MM, Patel KM, Ruttimann UE. PRISM III: an updated Pediatric Risk of Mortality score. Crit Care Med. 1996;24(5):743\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSlater A, Shann F, Pearson G. PIM2: a revised version of the Paediatric Index of Mortality. Intensive Care Med. 2003;29(2):278\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThukral A, Lodha R, Irshad M, Arora NK. Performance of Pediatric Risk of Mortality (PRISM), Pediatric Index of Mortality (PIM), and PIM2 in a pediatric intensive care unit in a developing country. Pediatr Crit care medicine: J Soc Crit Care Med World Federation Pediatr Intensive Crit Care Soc. 2006;7(4):356\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBorghi C, Fogacci F, Cicero AF. Crystal clear - part I: The role of uric acid in cardiorenal disease. Eur J Intern Med 2025.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePinz MP, Medeiros I, Carvalho L, Meotti FC. Is uric acid a true antioxidant? Identification of uric acid oxidation products and their biological effects. 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Front Nutr. 2024;11:1481155.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen S, Zhang M, Hu S, Shao X, Liu L, Yang Z, Nan K. Uric acid to albumin ratio is a novel predictive marker for all-cause and cardiovascular death in diabetic patients: a prospective cohort study. Front Endocrinol. 2024;15:1388731.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQin A, Yang D, Wang S, Dong L, Tan J, Tang Y, Qin W. Uric acid-based ratios for predicting renal failure in Chinese IgA nephropathy patients. Int J Med Sci. 2023;20(12):1584\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiao Y, Li L, Li J, Zhao F, Zhang C. Uric Acid to Albumin Ratio: A Predictive Marker for Acute Kidney Injury in Isolated Tricuspid Valve Surgery. Rev Cardiovasc Med. 2025;26(2):26391.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang G, Li G, Wang P, Zang M, Pu J. The Uric Acid to Albumin Ratio Predicts All-cause and Cardiovascular Mortality Among U.S. Adults Results from the National Health and Nutrition Examination Survey in 2003\u0026ndash;2018. Int J Med Sci. 2025;22(10):2277\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaruhashi T, Hisatome I, Kihara Y, Higashi Y. Hyperuricemia and endothelial function: From molecular background to clinical perspectives. Atherosclerosis. 2018;278:226\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSautin YY, Nakagawa T, Zharikov S, Johnson RJ. Adverse effects of the classic antioxidant uric acid in adipocytes: NADPH oxidase-mediated oxidative/nitrosative stress. Am J Physiol Cell Physiol. 2007;293(2):C584\u0026ndash;596.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePuddu P, Puddu GM, Cravero E, Vizioli L, Muscari A. Relationships among hyperuricemia, endothelial dysfunction and cardiovascular disease: molecular mechanisms and clinical implications. J Cardiol. 2012;59(3):235\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuwabara M, Hisatome I, Ae R, Kosami K, Aoki Y, Andres-Hernando A, Kanbay M, Lanaspa MA. Hyperuricemia, A new cardiovascular risk. Nutr metabolism Cardiovasc diseases: NMCD. 2025;35(3):103796.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAguayo-Becerra OA, Torres-Garibay C, Mac\u0026iacute;as-Amezcua MD, Fuentes-Orozco C, Ch\u0026aacute;vez-Tostado Mde G, Andal\u0026oacute;n-Due\u0026ntilde;as E, Espinosa Partida A, Alvarez-Villase\u0026ntilde;or Adel S, Cort\u0026eacute;s-Flores AO, Gonz\u0026aacute;lez-Ojeda A. Serum albumin level as a risk factor for mortality in burn patients. Clin (Sao Paulo Brazil). 2013;68(7):940\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang L, Deng T, Zeng G, Chen X, Wu D. The association of serum albumin with 28 day mortality in critically ill patients undergoing dialysis: a secondary analysis based on the eICU collaborative research database. Eur J Med Res. 2024;29(1):530.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGremese E, Bruno D, Varriano V, Perniola S, Petricca L, Ferraccioli G. Serum Albumin Levels: A Biomarker to Be Repurposed in Different Disease Settings in Clinical Practice. J Clin Med 2023, 12(18).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFanali G, di Masi A, Trezza V, Marino M, Fasano M, Ascenzi P. Human serum albumin: from bench to bedside. Mol Aspects Med. 2012;33(3):209\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBloch A, Berger D, Takala J. Understanding circulatory failure in sepsis. Intensive Care Med. 2016;42(12):2077\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"uric acid to albumin ratio, critically ill children, mortality risk, pediatric intensive care database","lastPublishedDoi":"10.21203/rs.3.rs-7328002/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7328002/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eThe prognostic value of the uric acid to albumin ratio (UAR) in critically ill children is unknown. We aimed to investigate the association between admission UAR and mortality in the pediatric intensive care unit (PICU) and to characterize the nature of this relationship.\u003c/p\u003e\u003ch2\u003ePatients and methods:\u003c/h2\u003e\u003cp\u003eThis retrospective cohort study enrolled 6,686 critically ill children from the Pediatric Intensive Care (PIC) database. The primary outcome was 28-day ICU mortality. The relationship between UAR and mortality was explored using multivariable logistic regression. Restricted cubic splines (RCS) and a two-piecewise linear regression model were performed to assess for non-linearity and threshold effects. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and mediation analysis were also conducted.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eIn the fully adjusted model, UAR was independently associated with an increased risk of 28-day ICU mortality (OR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 1.13\u0026ndash;1.37, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients in the highest UAR quartile (Q4) had a significantly higher mortality risk compared to the lowest quartile (Q1) (OR\u0026thinsp;=\u0026thinsp;1.94, 95% CI: 1.34\u0026ndash;2.82, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Kaplan-Meier analysis confirmed a significantly lower survival probability in the Q4 group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). RCS analysis revealed a non-linear relationship (\u003cem\u003eP\u003c/em\u003e for non-linearity\u0026thinsp;\u0026lt;\u0026thinsp;0.05), identifying a significant inflection point at UAR\u0026thinsp;=\u0026thinsp;2.815. Below this threshold, the mortality risk increased more steeply (OR\u0026thinsp;=\u0026thinsp;1.95, 95% CI: 1.49\u0026ndash;2.53). The predictive ability of UAR for 28-day ICU mortality (AUC\u0026thinsp;=\u0026thinsp;0.700) was superior to its individual components. Lactate was found to partially mediate the association, accounting for 35.18% of the total effect.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur study identifies admission UAR as a novel, independent predictor of mortality in a large cohort of critically ill children. As a simple and universally available biomarker, UAR holds significant promise for improving early risk stratification in the PICU.\u003c/p\u003e","manuscriptTitle":"Non-linear Relationship between Uric Acid to Albumin Ratio and Mortality in Pediatric Intensive Care Unit Patients: A Large-Scale Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 02:42:14","doi":"10.21203/rs.3.rs-7328002/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-09-25T17:06:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323807900423942836353164214663665966718","date":"2025-09-15T18:42:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-12T22:15:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-10T05:51:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-19T18:06:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-19T02:14:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-08-19T02:10:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4f3fa4b9-1003-4c62-97f8-33232a0c8741","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-23T02:42:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 02:42:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7328002","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7328002","identity":"rs-7328002","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}