Risk Factors and Mortality Impact of Acute Kidney Injury in Different ECMO Modalities: A Multicenter Retrospective Study

Risk Factors and Mortality Impact of Acute Kidney Injury in Different ECMO Modalities: A Multicenter Retrospective 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 Risk Factors and Mortality Impact of Acute Kidney Injury in Different ECMO Modalities: A Multicenter Retrospective Study Yueguo Wang, Xin Wang, Xiancong Wang, Jian Sun, Yulan Wang, Xiongfeng Zhu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7968769/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To identify independent risk factors for acute kidney injury (AKI) in critically ill patients undergoing extracorporeal membrane oxygenation (ECMO) and to evaluate the association between AKI severity and 30-day mortality. Methods A retrospective multicenter cohort study across three provincial ECMO medical centers was conducted between September 2019 and June 2024. Serum creatinine levels within the first 7 days following ECMO initiation were collected, and AKI was staged according to KDIGO criteria, with dynamic progression tracked over time. Multivariable logistic regression was used to identify predictors of moderate-to-severe AKI (AKI stages 2–3). Survival analysis was performed using Kaplan-Meier curves, and Cox proportional-hazards models were applied to assess the impact of AKI stage on 30-day mortality. Results Among 210 enrolled patients, 100 (47.6%) had AKI stages 0–1, while 110 (52.4%) developed AKI stages 2–3 within 7 days after ECMO initiation. Serial creatinine monitoring indicated a gradual increase in AKI stage 2, whereas the incidence of AKI stage 3 plateaued. Cox regression analysis demonstrated that moderate-to-severe AKI was independently associated with 30-day mortality, both before and after adjustment for APACHE II score (adjusted HR = 1.29, 95% CI 1.13–1.86, P < 0.05). In the overall cohort, VA-ECMO modality, norepinephrine use, and low fibrinogen level were significant risk factors for AKI stages 2–3, while pre-existing cardiac disease was protective (AUC 0.78). Subgroup analysis showed that for VV-ECMO patients, elevated LAC, HCO₃⁻, CRP, PCT, and BUN, as well as decreased fibrinogen, TBIL, and WBC count, were associated with AKI risk (AUC = 0.89). Conclusions AKI is an independent risk factor for 30-day mortality in ECMO patients. VA-ECMO modality, vasopressor use, and low fibrinogen levels increase the risk of moderate-to-severe AKI, with risk profiles varying by ECMO modality. Early identification of high-risk phenotypes and mode-specific management strategies are essential to improving outcomes. extracorporeal membrane oxygenation acute kidney injury risk factors APACHE II score Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acute kidney injury (AKI) is one of the most prevalent and severe complications observed during ECMO therapy [ 1 , 2 ]. The hemodynamic alterations, inflammatory response, and anticoagulation protocols inherent to ECMO treatment can all contribute to renal damage. Previous studies have suggested that the incidence rates of AKI during ECMO therapy range from 50% to 70% [ 3 , 4 ], with approximately 30% of affected patients requiring renal replacement therapy. This significantly heightens in-hospital mortality rates, increases resource utilization, and poses a long-term risk for chronic kidney disease (CKD) [ 5 ], thereby creating substantial socio-economic burdens on both the society and families [ 6 ]. Despite extensive research on ECMO-related AKI, the findings remain inconsistent, and the influence of different AKI stages on patient outcomes is yet to be fully elucidated. In a single-center study by Kallur et al .[ 7 ] sought to address this, demonstrating a trend where higher KDIGO-AKI stages were associated with increased odds of 30-day mortality, although these associations did not reach statistical significance in their cohort. Similarly, Chen et al .[ 8 ] found that among acute myocardial infarction complicated by cardiogenic shock patients supported by ECMO, Severe AKI was associated with markedly higher 1-year mortality (63.67% vs . 34.25%, all P < 0.001) and increased the risk of 1-year death approximately ten-fold (HR 10.82, 95% CI 3.12–37.51, P < 0.001). Additionally, Bravi et al . [ 9 ] corroborated these findings, showing that AKI stage 3 significantly increased mortality risk in elderly patients with COVID-19 (OR = 2.02, 95% CI 1.04–3.9, P = 0.038). However, existing literature predominantly focuses on non-domestic populations and is limited in its analysis of different ECMO modalities, including venoarterial ECMO (VA-ECMO) and venovenous ECMO (VV-ECMO). Additionally, the dynamic progression of AKI and its association with short-term mortality require further investigation. This retrospective study, involving multiple ECMO therapy centers, aims to explore the dynamic characteristics of AKI development, assess the impact of various AKI stages on 30-day mortality, and identify independent risk factors for moderate-to- severe AKI across different ECMO modalities. The findings are intended to facilitate early detection, risk stratification, and targeted management, ultimately enhancing the prognosis of ECMO patients. Materials and Methods Study Design and Participants This investigation is a multi-center, retrospective cohort study utilizing the Chinese Emergency Specialty Medical Association (CETAT), version 2.0., a multicenter emergency triage database developed by the Emergency Medical Specialist Alliance in China [ 10 ]. The study encompassed patients who underwent ECMO therapy in the intensive care units (ICUs) of the First Affiliated Hospital of the University of Science and Technology of China, the Third Affiliated Hospital of Anhui Medical University (Hefei First People's Hospital), and Hefei Third People's Hospital, between September 2019 and June 2024. Inclusion criteria were as follows:①Patients aged 18 years or older; ②Patients who received ECMO therapy during the study period;③Availability of complete clinical data at the time of admission and prior to ECMO initiation. Exclusion criteria were as follows:①Patients who did not complete physician-prescribed treatments;②Incomplete or missing clinical data; ③Patients with survival durations of less than 48 hours following ECMO initiation; ④History of long-term hemodialysis or chronic renal failure; ⑤Patients with advanced-stage cancer, pregnancy, or breastfeeding status;⑥Absence of essential laboratory or follow-up data. Definition and Staging of AKI The occurrence and staging of AKI were determined based on the dynamic changes in serum creatinine (Scr) levels within 7 days following ECMO initiation, as per the 2012 KDIGO guidelines [ 11 ]. The specific staging criteria are detailed in Table 1 . Table 1 KDIGO classification of renal function Stage Scr Criteria Stage I Increase in Scr to 1.5 ~ 1.9 times baseline or by ≥ 26.4 µmol/L within 48 hours Stage II Increase in Scr to 2.0 ~ 2.9 times baseline Stage III Increase in Scr to 3.0 times baseline, or ≥ 352 µmol/L, or initiation of renal replacement therapy (RRT) KDIGO, Kidney Disease: Improving Global Outcomes; RRT, renal replacement therapy; Scr, serum creatinine Observational Variables and Groupings Baseline clinical data were extracted from the electronic medical record system, including demographic variables (gender, age, height, and weight), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and history of chronic conditions [hypertension, diabetes, coronary artery disease, and chronic obstructive pulmonary disease (COPD), etc.]. Additional data included vital signs at admission, laboratory test results (initial blood work, coagulation profile, biochemical markers, and blood gas analysis), indications for ECMO initiation [acute respiratory distress syndrome (ARDS), cardiac arrest, cardiogenic shock (non-cardiac arrest-related)], the use of vasopressors prior to ECMO initiation, and clinical outcomes. According to the KDIGO criteria, patients were categorized into three groups based on the highest stage of AKI observed during ECMO: stages 0–1, 2, and 3. Furthermore, AKI stages 2–3 were classified as moderate-to-severe AKI to facilitate the analysis of associated risk factors. Study Endpoints The primary endpoint was the 30-day all-cause mortality rate. The second endpoint included the incidence of AKI across different stages and its correlation with mortality risk. Subgroup analyses will be conducted according to ECMO modality (VV-ECMO and VA-ECMO). Statistical Methods All statistical analyses were performed using Stata IC 16.0 and GraphPad Prism 10.0 software. The distribution of continuous variables was assessed using the Kolmogorov-Smirnov test. For skewed data, results are presented as median (interquartile range, IQR), with inter-group comparisons made using the Kruskal-Wallis H test. Categorical data were expressed as counts (n) and percentages (%), with comparisons between groups conducted using the χ² test or Fisher’s exact test. A Cox proportional hazards model was employed to adjust for confounders and examine the association between AKI stages and mortality risk, with hazard ratios (HR) and 95% confidence intervals (CI) reported. Kaplan-Meier survival curves and Log-rank tests were used to compare 30-day mortality rates across different AKI stages. Multivariate logistic regression analysis was performed to identify independent risk factors for progression to AKI stages 2–3, both in the overall cohort and within subgroups based on ECMO modality. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves. All statistical tests were two-tailed, with P < 0.05 considered statistically significant. Results Patient Characteristics A total of 210 patients receiving ECMO therapy were included in the study. Among them, 100 patients (47.6%) were classified into the AKI stages 0–1 group, while 110 patients (52.4%) were classified into the AKI stages 2–3 group. A comparison of baseline characteristics and clinical outcomes is provided in Table 2 . Compared to patients in the AKI stages 0–1 and stage 2 groups, those in the AKI stage 3 group were younger, had higher body weight, elevated APACHE II scores, and a greater prevalence of cardiac arrest and cardiogenic shock. Additionally, the use of VA-ECMO modality and vasopressors was more frequent in this group, and levels of procalcitonin (PCT) and D-dimer were significantly elevated, with a marked reduction in platelet (PLT) count ( P < 0.05). Hospital length of stay varied across the three groups, with patients in the AKI stage 3 group having a significantly shorter hospital stay ( P 0.05). Dynamic monitoring of Scr levels over 7 days following ECMO initiation revealed a daily decrease in the proportion of patients in AKI stages 0–1, a gradual increase in those in stage 2, and a stable proportion of patients in stage 3 (Fig. 1 ). Kaplan-Meier analysis demonstrated that the 30-day cumulative survival rate was significantly lower in the AKI stage 3 group compared to the AKI stages 0–1 and stage 2 groups ( P < 0.05), while no significant difference was observed between the AKI stages 0–1 and stage 2 groups (Fig. 2 ). Table 2 Comparison of baseline characteristics and clinical outcomes Clinical Variables AKI stages 0–1(N = 100) AKI stage 2 (N = 21) AKI stage 3 (N = 89) P -value Demographics Male, n (%) 68 (68.0%) 18 (85.7%) 58 (65.2%) 0.19 Age, years 54 (39, 61) 53 (49, 61) 49 (33, 56) 0.02 Height, cm 168.0 (165.5, 170.0) 170.0 (168.0, 172.0) 168.0 (165.0, 172.0) 0.17 Weight, Kg 62.0 (60.0, 65.0) 58.0 (48.0, 64.0) 63.0 (62.0, 71.0) 0.01 Medical history Hypertension, n (%) 31 (31.0%) 9 (42.9%) 29 (32.6%) 0.57 Diabetes Mellitus, n (%) 17 (17.0%) 4 (19.0%) 13 (14.6%) 0.84 ACS, n (%) 17 (17.0%) 2 (9.5%) 9 (10.1%) 0.33 COPD, n (%) 6 (6.0%) 0 (0.0%) 4 (4.5%) 0.50 Vital signs at admission Temperature, ℃ 37.0 (36.0, 37.0) 37.0 (36.0, 37.0) 37.0 (36.0, 37.0) 0.05 Heart rate, bpm 99 (87, 112) 105 (99, 116) 108 (85, 122) 0.34 SBP, mmHg 114.0 (104.0, 127.5) 113.0 (107.0, 128.0) 113.0 (95.0, 129.0) 0.26 DBP, mmHg 75.0 (66.5, 84.5) 77.0 (67.0, 81.0) 67.5 (59.0, 78.0) 0.07 Disease severity APACHE II score 20.5 (17.0, 26.5) 20.5 (17.0, 20.5) 25.0 (20.5, 31.0) < 0.01 Indications for ECMO initiation Acute Respiratory Failure, n (%) 15 (15.0%) 1 (4.8%) 11 (12.4%) 0.42 Cardiac Arrest, n (%) 8 (8.0%) 0 (0.0%) 16 (18.0%) 0.02 Cardiogenic Shock, n (%) 14 (14.0%) 4 (19.0%) 35 (39.3%) < 0.01 ECMO modality VA-ECMO, n (%) 42 (42.0%) 10 (47.6%) 70 (78.7%) < 0.01 Vasoactive drugs Norepinephrine, n (%) 74 (74.0%) 19 (90.5%) 87 (97.8%) < 0.01 Epinephrine, n (%) 72 (72.0%) 19 (90.5%) 85 (95.5%) < 0.01 Dopamine, n (%) 21 (21.0%) 5 (23.8%) 44 (49.4%) < 0.01 Laboratory test results WBC, ×10⁹·L − ¹ 10.8 (7.7, 15.8) 9.5 (6.1, 15.4) 11.0 (6.9, 17.0) 0.61 Neu, ×10⁹·L − ¹ 8.7 (6.0, 13.0) 7.6 (4.5, 13.4) 9.2 (4.9, 15.2) 0.69 RBC, ×10¹²·L − ¹ 4.0 (3.6, 4.6) 4.4 (3.8, 4.8) 4.0 (3.4, 4.6) 0.22 Hb, g·L − ¹ 121.5 (109.0, 136.5) 131.0 (110.0, 139.0) 123.0 (102.0, 141.0) 0.56 PLT, ×10⁹·L − ¹ 175.5 (144.5, 236.0) 227.0 (160.0, 311.0) 145.0 (70.0, 206.0) < 0.01 CRP, mg·L − ¹ 34.4 (11.2, 95.5) 14.9 (5.6, 80.1) 58.7 (15.0, 121.4) 0.35 PCT, ng·mL − ¹ 0.3 (0.1, 1.1) 0.2 (0.1, 0.4) 1.1 (0.3, 2.9) < 0.01 Scr, µmol·L − ¹ 73.8 (52.4, 110.0) 55.8 (44.8, 91.7) 140.6 (74.5, 234.0) < 0.01 BUN, mmol·L − ¹ 7.2 (5.1, 9.6) 6.0 (4.6, 11.1) 9.2 (6.6, 13.4) < 0.01 TBIL, µmol·L − ¹ 14.7 (9.0, 22.3) 11.6 (6.1, 16.8) 17.0 (11.2, 30.3) < 0.01 DBIL, µmol·L − ¹ 6.5 (3.9, 8.3) 6.5 (3.9, 7.9) 7.8 (5.2, 14.7) 0.01 ALB, g·L − ¹ 32.9 (27.1, 36.8) 33.4 (25.6, 39.0) 28.9 (24.6, 34.9) 0.05 LAC, mmol·L − ¹ 2.9 (2.2, 5.2) 2.9 (1.9, 5.5) 5.5 (2.9, 6.8) < 0.01 APTT, s 30.4 (26.7, 38.2) 37.3 (28.5, 55.0) 42.7 (31.9, 62.1) < 0.01 PT, s 13.4 (12.5, 15.4) 14.4 (12.7, 15.9) 16.6 (14.0, 21.1) < 0.01 TT, s 17.5 (16.2, 19.6) 17.6 (16.7, 30.2) 20.4 (17.7, 37.6) < 0.01 D-dimer, mg·L − ¹ 4.5 (1.1, 9.4) 4.6 (2.5, 6.8) 11.1 (4.1, 25.6) < 0.01 Fig, g·L − ¹ 4.0 (2.2, 5.8) 2.3 (2.0, 4.5) 2.9 (1.9, 5.2) 0.05 Arterial blood gas analysis PH 7.4 (7.3, 7.5) 7.4 (7.3, 7.4) 7.3 (7.2, 7.4) < 0.01 PCO 2 , mmHg 33.3 (29.8, 38.8) 34.0 (24.5, 53.0) 34.4 (31.1, 41.8) 0.64 PO 2 , mmHg 73.9 (54.3, 116.7) 73.9 (59.2, 214.0) 71.0 (48.0, 84.4) 0.17 HCO 3 − , mmHg 20.4 (19.9, 23.0) 19.9 (17.7, 24.0) 19.9 (16.8, 20.8) < 0.01 Clinical outcome Hospital length of stay, days 21 (11, 32) 28 (15, 46) 8.0 (3, 23) < 0.01 Death, n (%) 25 (25.0%) 5 (23.8%) 34 (38.2%) 0.11 Data are presented as n (%) or median (interquartile range) as appropriate. P < 0.05 was considered statistically significant. APACHE II, Acute Physiology and Chronic Health Evaluation II; APTT, Activated Partial Thromboplastin Time; ALB, Albumin; BUN, Blood Urea Nitrogen; COPD, Chronic Obstructive Pulmonary Disease; CRP, C-Reactive Protein; DBIL, Direct bilirubin; ECMO, Extracorporeal Membrane Oxygenation; Fig, Fibrinogen; Hb, Hemoglobin; HCO₃⁻, Bicarbonate; LAC, Lactate; Neu, neutrophil; pH, Potential of Hydrogen; PLT, Platelet; PCT, Procalcitonin; PCO₂, Arterial partial pressure of carbon dioxide; PO₂, Arterial partial pressure of oxygen; PT, Prothrombin Time; RBC, Red Blood Cell; Scr, Serum creatinine; TBIL, Total bilirubin; TT, Thrombin Time; VA-ECMO, Venoarterial Extracorporeal Membrane Oxygenation; WBC, White Blood Cell. ECMO initiation * P < 0.05, ns, no significant difference. Effect of AKI severity on 30-day mortality in ECMO patients To explore the prognostic value of AKI staging for 30-day mortality in ECMO patients. Cox regression analysis revealed that AKI stage 3 significantly increased the 30-day mortality risk, irrespective of APACHE II score adjustments. Unadjusted HR = 2.01 (95% CI 1.19–3.40, P = 0.01); adjusted HR = 1.29 (95% CI 1.13–1.86, P = 0.036), making it an independent risk factor for 30-day mortality. Subgroup analysis demonstrated that in the VV-ECMO subgroup, AKI stage 3 significantly increased the mortality risk (unadjusted HR = 3.17, 95% CI 1.27–7.93, P = 0.013; adjusted HR = 2.09, 95% CI 1.29–5.50, P = 0.038). In contrast, no significant association between AKI stage 3 and 30-day mortality risk was found in the VA-ECMO subgroup, regardless of APACHE II score adjustments (unadjusted P = 0.51; adjusted P = 0.444). Furthermore, each 1-point increase in APACHE II score was associated with a 10%-12% increase in mortality risk (HR = 1.10–1.12, P < 0.05) (Table 3 ). Kaplan- Meier survival curves demonstrated that the 30-day cumulative survival rate was significantly lower in patients with moderate-to-severe AKI (stages 2–3) compared to those in AKI stages 0–1 ( P = 0.04) (Fig. 3 ). Table 3 COX regression analysis of the association between AKI grade and 30-day mortality risk in ECMO patients All ECMO VA-ECMO VV-ECMO Unadjusted APACHE II score HR 95% CI P -value HR 95% CI P -value HR 95% CI P -value AKI stages 0–1 reference AKI stage 2 0.80 0.31 ~ 2.10 0.656 0.82 0.23 ~ 2.89 0.758 0.66 0.15 ~ 2.96 0.585 AKI stage 3 2.01 1.19 ~ 3.40 0.01 1.25 0.64 ~ 2.46 0.512 3.17 1.27 ~ 7.93 0.013 AKI stages 2–3 1.67 1.01 ~ 2.77 0.04 1.19 1.03 ~ 2.23 0.031 1.78 1.20 ~ 4.14 0.037 Adjusted APACHE II score HR 95% CI P -value HR 95% CI P -value HR 95% CI P -value AKI stages 0–1 reference AKI stage 2 0.82 0.32 ~ 2.12 0.687 0.96 0.27 ~ 3.41 0.944 0.75 0.17 ~ 3.42 0.713 AKI stage 3 1.29 1.13 ~ 1.86 0.036 0.75 0.36 ~ 1.56 0.444 2.09 1.29 ~ 5.50 0.038 AKI stages 2–3 1.31 1.28 ~ 2.48 0.041 1.15 1.24 ~ 2.71 0.034 1.48 1.02 ~ 3.48 0.046 APACHE II score 1.10 1.07 ~ 1.13 < 0.001 1.12 1.07 ~ 1.16 < 0.001 1.10 1.03 ~ 1.18 0.004 P < 0.05 was considered statistically significant. APACHE II, Acute Physiology and Chronic Health Evaluation II; AKI, Acute kidney injury; ECMO, Extracorporeal Membrane Oxygenation; VA-ECMO, Venoarterial Extracorporeal Membrane Oxygenation; VV-ECMO, Venovenous Extracorporeal Membrane Oxygenation. * P < 0.05. Modality-specific risk factors for moderate-to-severe AKI in ECMO patients To further demonstrated the influence of ECMO modality on the risk of moderate-to-severe AKI. Multivariate logistic regression in the overall cohort identified the following independent risk factors for moderate-to-severe AKI in ECMO patients: VA-ECMO modality (OR = 3.28, 95% CI : 1.83–5.89, P < 0.001), norepinephrine (NE) use (OR = 2.40, 95% CI : 1.24–4.64, P = 0.009), and low fibrinogen levels (OR = 0.75, 95% CI : 0.64–0.89, P = 0.001). But a history of cardiovascular disease was identified as a protective factor (OR = 0.38, 95% CI : 0.17–0.87, P = 0.021). The model's combined predictive AUC was 0.78. Further analysis of risk factors for moderate-to-severe AKI by ECMO modality revealed that in the VV-ECMO subgroup, elevated levels of lactate (LAC) (OR = 1.39, 95% CI : 1.11–1.77), bicarbonate (HCO₃⁻) (OR = 1.11, 95% CI : 1.00-1.22), C-reactive protein (CRP) (OR = 1.01, 95% CI : 1.00-1.02), procalcitonin (PCT) (OR = 1.36, 95% CI : 1.04–1.78), blood urea nitrogen (BUN) (OR = 1.16, 95% CI : 1.02–1.31), and a reduction in fibrinogen (OR = 0.58, 95% CI : 0.40–0.83), total bilirubin (TBIL) (OR = 0.85, 95% CI : 0.76–0.96), and white blood cell (WBC) count (OR = 0.89, 95% CI : 0.80–0.99) were all independent risk factors ( P < 0.05), with an AUC of 0.89. However, in the VA-ECMO subgroup, NE use (OR = 2.47, 95% CI : 1.10–5.53, P = 0.028) was the only independent risk factor identified, while a history of cardiovascular disease (OR = 0.35, 95% CI : 0.13–0.95, P = 0.039) acted as a protective factor. The predictive AUC for this subgroup was 0.76. Although pre-ECMO cardiogenic shock and ARDS showed relatively high odds ratios, these differences did not reach statistical significance ( P > 0.05), likely due to the limited sample size (Fig. 4 ). in ECMO patients ARDS, acute respiratory distress syndrome; BUN, Blood Urea Nitrogen; CRP, C-Reactive Protein; DBIL, Direct bilirubin; ECMO, Extracorporeal Membrane Oxygenation; Fig, Fibrinogen; HCO₃⁻, Bicarbonate; Hb, Hemoglobin; LAC, Lactate; NE, norepinephrine; PCT, Procalcitonin; PO₂, Arterial partial pressure of oxygen; PLT, Platelet; Scr, Serum creatinine; TBIL, Total bilirubin; Temp, Temperature; TT, Thrombin Time; VA-ECMO, Venoarterial Extracorporeal Membrane Oxygenation; VV-ECMO, Venovenous Extracorporeal Membrane Oxygenation; WBC, White Blood Cell. Discussion This study retrospectively analyzed the dynamic changes in different stages of AKI and their prognostic differences in patients undergoing ECMO, and explored the associated risk factors for moderate-to-severe AKI under different ECMO modalities. The results showed that the incidence of moderate-to-severe AKI was approximately 52.4%. Among these patients, the proportion of those with AKI stage 2 gradually increased within the first 7 days after ECMO initiation, whereas AKI stage 3 was an independent risk factor for 30-day mortality. In addition, VA-ECMO modality, the use of NE, and low fibrinogen levels were found to increase the risk of moderate-to- severe AKI, while a history of cardiovascular disease appeared to have a protective effect. In VV-ECMO patients, metabolic disorders, inflammatory responses, and coagulation abnormalities were the primary risk factors, whereas in VA-ECMO patients, only NE use was independently associated with moderate-to-severe AKI. In this study, approximately 42.4% of AKI patients had AKI stage 3, which was lower than the 53.8% reported by Vinclair et al . [ 12 ]. This difference may be related to differences in the study population and diagnostic criteria: first, Vinclair et al . included only VA-ECMO patients, whereas in this study, about half of the cases were VA-ECMO, which aligns with the characteristics of emergency situations where a large number of patients with refractory circulatory failure require VA-ECMO support. VA-ECMO patients are more prone to severe AKI due to hemodynamic instability, frequent use of vasoactive drugs [ 13 , 14 ], whereas VV-ECMO patients tend to have more stable hemodynamics [ 15 ]. Secondly, Vinclair et al . used the highest KDIGO classification during ICU admission to determine AKI stage 3, whereas this study assessed KDIGO classification within 7 days after ECMO initiation. Consequently, some patients who progressed to AKI stage 3 after 7 days were not included, which likely led to a lower AKI incidence. Another studies also used Scr changes within 7 days as a criterion for diagnosing AKI, with nearly half of their patients progressed to AKI stage 3 [ 16 , 17 ], which is similar to the findings in this study. The focus on AKI occurrence within the first 7 days in this study is based on previous research showing that 90% of AKI cases occur within the first 7 days of hospitalization [ 18 , 19 ]. Another key finding of this study was that the proportion of AKI stage 3 patients did not change significantly within the first 7 days after ECMO initiation, while the number of AKI stage 2 patients increased significantly. This suggests that AKI stage 2 patients require closer monitoring within the first week of ECMO therapy. However, for patients who undergo prolonged ECMO support, the specific incidence and timing of AKI after 7 days require further investigation through larger-scale studies. This study also found that, whether or not APACHE II was adjusted, AKI stage 3 significantly increased the risk of 30-day mortality. This is consistent with the findings of Vinclair et al . [ 12 ] and other multicenter studies. In Vinclair's study, AKI stage 3 on the day of VA-ECMO initiation was independently associated with one-year mortality (OR = 10.20). Furthermore, this study showed that for every one-point increase in the APACHE II score, the risk of death increased by approximately 10%-12%, which is consistent with previous reports [ 3 , 20 ]. This indicates that the APACHE II score remains a reliable tool for prognostic assessment in ECMO patients, and it also suggests that clinical evaluations of these patients should consider the overall severity of their condition. Further analysis of AKI risk factors revealed that VA-ECMO modality, NE use, and low fibrinogen levels were independent risk factors for moderate-to-severe AKI across all ECMO patients. This is likely because VA-ECMO is commonly used in patients with severe circulatory failure, and its non-pulsatile perfusion, increased afterload, and other non-physiological hemodynamic characteristics interact with the shock-induced low perfusion state, increasing the risk of renal hypoperfusion and injury [ 21 , 22 ]. Moreover, the ECMO circuit in VA-ECMO involves mechanical shear stress and contact with non-physiological surfaces such as the oxygenator, which can cause hemolysis and microthrombus formation [ 23 , 24 ]. Additionally, the use of NE was associated with an increased risk of moderate-to-severe AKI in VA-ECMO patients (OR = 2.40–2.47). Similar conclusions were drawn by Huette et al . [ 25 ], with NE's activation of α-1 receptors increasing systemic vascular resistance and inducing vasoconstriction, which could contribute to AKI [ 26 ]. In contrast, this study found that a history of cardiovascular disease had a protective effect in both all ECMO and VA-ECMO subgroup patients (OR = 0.35–0.38), possibly because chronic heart disease patients tend to receive earlier and more rigorous volume management strategies or left ventricular unloading when ECMO is initiated [ 27 , 28 ]. Furthermore, metabolic disorders, inflammatory responses, and coagulation abnormalities were identified as risk factors for moderate-to-severe AKI in VV-ECMO patients. This may be related to the fact that VV-ECMO is commonly used in patients with severe ARDS [ 29 ] and other respiratory failure [ 30 ], and ongoing hypoxemia and lactate accumulation during the course of the disease can lead to renal cortical ischemia and acidotic tubular damage [ 31 ]. Limitations This study is one of the largest multi-center retrospective studies in China to date, but it does have limitations: ①The overall sample size of ECMO patients is still relatively small, and some results may be affected by statistical power, likely due to the high cost and technical complexity of ECMO treatment, which makes patient enrollment challenging. ②Although the APACHE II score was corrected in the multivariate model, it is impossible to completely control for confounding factors such as ECMO treatment parameters and anticoagulation protocols. ③The diagnosis of AKI did not include urine output criteria, meaning that patients with oliguria or anuria who did not meet the Scr threshold were omitted, which may lead to an underestimation of AKI incidence. Conclusion In the present study, the incidence of AKI in ECMO patients is high and significantly affects their prognosis. The risk of AKI varies significantly across different ECMO modalities, suggesting that clinical practice should include individualized risk stratification and early interventions based on ECMO modality and associated risk factors to improve patient outcomes. Declarations Ethics Approval and Consent to participate The study was approved by the Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China (Approval No. 2024-ky300) and conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective design and use of anonymized data. Consent for publication Not applicable. Competing Interests The authors declare that there are no conflicts of interest. Funding This study was supported by the Natural Science Foundation of Anhui Province (2208085MH235). Author Contribution YW, XW, and KJ contributed to the conception and design of the study. YW, XW, JS, YW, XZ, and HM contributed to data acquisition. YW and KJ drafted the manuscript. YW, XW, JS, and YW performed data analysis. YW, XW, YW, and KJ edited and critically revised the manuscript. YW and KJ approved the final version of the manuscript. Acknowledgements The authors would like to thank all the medical staff, patients and their families in the three ECMO medical centers for their support in this study. Data Availability The datasets generated and analyzed during the current study are not publicly available due to sensible personal clinical data, but are available from the corresponding author upon reasonable request. References Guru PK, Balasubramanian P, Ghimire M, et al. Acute kidney injury in patients before and after extracorporeal membrane oxygenation (ECMO) - Retrospective longitudinal analysis of the hospital outcomes[J]. J Crit Care. 2024;81:154528. https://doi:10.1016/j.jcrc.2024.154528 . Lumlertgul N, Wright R, Hutson G, et al. 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Incidence and outcomes of acute kidney injury in intensive care units: a Veterans Administration study[J]. Crit Care Med. 2009;37(9):2552–8. https://doi:10.1097/CCM.0b013e3181a5906f . Nisula S, Kaukonen KM, Vaara ST, et al. Incidence, risk factors and 90-day mortality of patients with acute kidney injury in Finnish intensive care units: the FINNAKI study[J]. Intensive Care Med. 2013;39(3):420–8. https://doi:10.1007/s00134-012-2796-5 . Maca J, Matousek V, Bursa F, et al. Extracorporeal membrane oxygenation survival: External validation of current predictive scoring systems focusing on influenza A etiology[J]. Artif Organs. 2021;45(8):881–92. https://doi:10.1111/aor.13932 . Bogerd M, Ten Berg S, Peters EJ, et al. Impella and venoarterial extracorporeal membrane oxygenation in cardiogenic shock complicating acute myocardial infarction[J]. Eur J Heart Fail. 2023;25(11):2021–31. https://doi:10.1002/ejhf.3025 . Idrovo A, Hollander SA, Neumayr TM, et al. Long-term kidney outcomes in pediatric continuous-flow ventricular assist device patients[J]. Pediatr Nephrol. 2024;39(4):1289–300. https://doi:10.1007/s00467-023-06190-8 . Bemtgen X, Rilinger J, Holst M, et al. Carboxyhemoglobin (CO-Hb) Correlates with Hemolysis and Hospital Mortality in Extracorporeal Membrane Oxygenation: A Retrospective Registry[J]. Diagnostics (Basel). 2022;12(7):1642. https://doi:10.3390/diagnostics12071642 . Saeed O, Jakobleff WA, Forest SJ, et al. Hemolysis and Nonhemorrhagic Stroke During Venoarterial Extracorporeal Membrane Oxygenation[J]. Ann Thorac Surg. 2019;108(3):756–63. https://doi:10.1016/j.athoracsur.2019.03.030 . Huette P, Moussa MD, Beyls C, et al. Association between acute kidney injury and norepinephrine use following cardiac surgery: a retrospective propensity score-weighted analysis[J]. Ann Intensive Care. 2022;12:61. https://doi:10.1186/s13613-022-01037-1 . Zhang D, Li L, Huang W, et al. Vasoactive-Inotropic Score as a Promising Predictor of Acute Kidney Injury in Adult Patients Requiring Extracorporeal Membrane Oxygenation.[J]. ASAIO J. 2024;70(7):586–93. https://doi:10.1097/MAT.0000000000002158 . Chiu LC, Chuang LP, Lin SW, et al. Cumulative Fluid Balance during Extracorporeal Membrane Oxygenation and Mortality in Patients with Acute Respiratory Distress Syndrome[J]. Membr (Basel). 2021;11(8):567. https://doi:10.3390/membranes11080567 . Schrage B, Becher PM, Bernhardt A, et al. Left Ventricular Unloading Is Associated With Lower Mortality in Patients With Cardiogenic Shock Treated With Venoarterial Extracorporeal Membrane Oxygenation: Results From an International, Multicenter Cohort Study[J]. Circulation. 2020;142(22):2095–106. https://doi:10.1161/CIRCULATIONAHA.120.048792 . Combes A, Supady A, Abrams D, et al. Extracorporeal life support for adult patients with ARDS[J]. Intensive Care Med. 2025;51(9):1674–86. https://doi:10.1007/s00134-025-08070-1 . Tongyoo S, Chanthawatthanarak S, Permpikul C, et al. Extracorporeal membrane oxygenation (ECMO) support for acute hypoxemic respiratory failure patients: outcomes and predictive factors[J]. J Thorac Dis. 2022;14(2):371–80. https://doi:10.21037/jtd-21-1460 . Saugel B, Sander M, Katzer C, et al. Association of intraoperative hypotension and cumulative norepinephrine dose with postoperative acute kidney injury in patients having noncardiac surgery: a retrospective cohort analysis[J]. Br J Anaesth. 2025;134(1):54–62. https://doi:10.1016/j.bja.2024.11.005 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":243990,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDynamic evolution of AKI grading within 7 days following\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eECMO initiation\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7968769/v1/2fa4fb08c826e23ce6b2e549.png"},{"id":96330358,"identity":"e68907a7-77f3-4612-ad63-3fa1d1d2a429","added_by":"auto","created_at":"2025-11-20 00:48:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98863,"visible":true,"origin":"","legend":"\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e\u003cem\u003e P\u003c/em\u003e \u0026lt;0.05，ns, no significant difference\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e30-day survival curves by individual AKI Stage\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7968769/v1/1c2ab6801b81fc8ddb0e714c.png"},{"id":96330355,"identity":"6476e46a-056c-4a99-8faf-9c095abb230d","added_by":"auto","created_at":"2025-11-20 00:48:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65408,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e30-day survival curves by AKI grade\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e* P \u0026lt;0.05.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7968769/v1/2064a412e45baad2af6885e3.png"},{"id":96330363,"identity":"d9818437-c7d2-43c3-8b96-20b92ef7626d","added_by":"auto","created_at":"2025-11-20 00:48:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":769346,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultivariate logistic analysis of risk factors for moderate to severe AKI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ein ECMO patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7968769/v1/854b05046cfa72de149daf37.png"},{"id":99310172,"identity":"cfbdfd14-41f2-4045-a3cd-a610bf69a180","added_by":"auto","created_at":"2025-12-31 16:12:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2388501,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7968769/v1/f16e8902-34ed-4f6e-b532-ef295b0ec29a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk Factors and Mortality Impact of Acute Kidney Injury in Different ECMO Modalities: A Multicenter Retrospective Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute kidney injury (AKI) is one of the most prevalent and severe complications observed during ECMO therapy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The hemodynamic alterations, inflammatory response, and anticoagulation protocols inherent to ECMO treatment can all contribute to renal damage. Previous studies have suggested that the incidence rates of AKI during ECMO therapy range from 50% to 70% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], with approximately 30% of affected patients requiring renal replacement therapy. This significantly heightens in-hospital mortality rates, increases resource utilization, and poses a long-term risk for chronic kidney disease (CKD) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], thereby creating substantial socio-economic burdens on both the society and families [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite extensive research on ECMO-related AKI, the findings remain inconsistent, and the influence of different AKI stages on patient outcomes is yet to be fully elucidated. In a single-center study by Kallur \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] sought to address this, demonstrating a trend where higher KDIGO-AKI stages were associated with increased odds of 30-day mortality, although these associations did not reach statistical significance in their cohort. Similarly, Chen \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] found that among acute myocardial infarction complicated by cardiogenic shock patients supported by ECMO, Severe AKI was associated with markedly higher 1-year mortality (63.67% \u003cem\u003evs\u003c/em\u003e. 34.25%, all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and increased the risk of 1-year death approximately ten-fold (HR 10.82, 95%\u003cem\u003eCI\u003c/em\u003e 3.12\u0026ndash;37.51, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, Bravi \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] corroborated these findings, showing that AKI stage 3 significantly increased mortality risk in elderly patients with COVID-19 (OR\u0026thinsp;=\u0026thinsp;2.02, 95%\u003cem\u003eCI\u003c/em\u003e 1.04\u0026ndash;3.9, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038). However, existing literature predominantly focuses on non-domestic populations and is limited in its analysis of different ECMO modalities, including venoarterial ECMO (VA-ECMO) and venovenous ECMO (VV-ECMO). Additionally, the dynamic progression of AKI and its association with short-term mortality require further investigation.\u003c/p\u003e\u003cp\u003eThis retrospective study, involving multiple ECMO therapy centers, aims to explore the dynamic characteristics of AKI development, assess the impact of various AKI stages on 30-day mortality, and identify independent risk factors for moderate-to- severe AKI across different ECMO modalities. The findings are intended to facilitate early detection, risk stratification, and targeted management, ultimately enhancing the prognosis of ECMO patients.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participants\u003c/h2\u003e\u003cp\u003eThis investigation is a multi-center, retrospective cohort study utilizing the Chinese Emergency Specialty Medical Association (CETAT), version 2.0., a multicenter emergency triage database developed by the Emergency Medical Specialist Alliance in China [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The study encompassed patients who underwent ECMO therapy in the intensive care units (ICUs) of the First Affiliated Hospital of the University of Science and Technology of China, the Third Affiliated Hospital of Anhui Medical University (Hefei First People's Hospital), and Hefei Third People's Hospital, between September 2019 and June 2024.\u003c/p\u003e\u003cp\u003eInclusion criteria were as follows:①Patients aged 18 years or older; ②Patients who received ECMO therapy during the study period;③Availability of complete clinical data at the time of admission and prior to ECMO initiation. Exclusion criteria were as follows:①Patients who did not complete physician-prescribed treatments;②Incomplete or missing clinical data; ③Patients with survival durations of less than 48 hours following ECMO initiation; ④History of long-term hemodialysis or chronic renal failure; ⑤Patients with advanced-stage cancer, pregnancy, or breastfeeding status;⑥Absence of essential laboratory or follow-up data.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDefinition and Staging of AKI\u003c/h3\u003e\n\u003cp\u003eThe occurrence and staging of AKI were determined based on the dynamic changes in serum creatinine (Scr) levels within 7 days following ECMO initiation, as per the 2012 KDIGO guidelines [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The specific staging criteria are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKDIGO classification of renal function\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScr Criteria\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage I\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncrease in Scr to 1.5\u0026thinsp;~\u0026thinsp;1.9 times baseline or by \u0026ge;\u0026thinsp;26.4 \u0026micro;mol/L within 48 hours\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncrease in Scr to 2.0\u0026thinsp;~\u0026thinsp;2.9 times baseline\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage III\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncrease in Scr to 3.0 times baseline, or \u0026ge;\u0026thinsp;352 \u0026micro;mol/L, or initiation of renal replacement therapy (RRT)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eKDIGO, Kidney Disease: Improving Global Outcomes; RRT, renal replacement therapy;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eScr, serum creatinine\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eObservational Variables and Groupings\u003c/h3\u003e\n\u003cp\u003eBaseline clinical data were extracted from the electronic medical record system, including demographic variables (gender, age, height, and weight), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and history of chronic conditions [hypertension, diabetes, coronary artery disease, and chronic obstructive pulmonary disease (COPD), etc.]. Additional data included vital signs at admission, laboratory test results (initial blood work, coagulation profile, biochemical markers, and blood gas analysis), indications for ECMO initiation [acute respiratory distress syndrome (ARDS), cardiac arrest, cardiogenic shock (non-cardiac arrest-related)], the use of vasopressors prior to ECMO initiation, and clinical outcomes. According to the KDIGO criteria, patients were categorized into three groups based on the highest stage of AKI observed during ECMO: stages 0\u0026ndash;1, 2, and 3. Furthermore, AKI stages 2\u0026ndash;3 were classified as moderate-to-severe AKI to facilitate the analysis of associated risk factors.\u003c/p\u003e\n\u003ch3\u003eStudy Endpoints\u003c/h3\u003e\n\u003cp\u003eThe primary endpoint was the 30-day all-cause mortality rate. The second endpoint included the incidence of AKI across different stages and its correlation with mortality risk. Subgroup analyses will be conducted according to ECMO modality (VV-ECMO and VA-ECMO).\u003c/p\u003e\n\u003ch3\u003eStatistical Methods\u003c/h3\u003e\n\u003cp\u003eAll statistical analyses were performed using Stata IC 16.0 and GraphPad Prism 10.0 software. The distribution of continuous variables was assessed using the Kolmogorov-Smirnov test. For skewed data, results are presented as median (interquartile range, IQR), with inter-group comparisons made using the Kruskal-Wallis H test. Categorical data were expressed as counts (n) and percentages (%), with comparisons between groups conducted using the χ\u0026sup2; test or Fisher\u0026rsquo;s exact test. A Cox proportional hazards model was employed to adjust for confounders and examine the association between AKI stages and mortality risk, with hazard ratios (HR) and 95% confidence intervals (CI) reported. Kaplan-Meier survival curves and Log-rank tests were used to compare 30-day mortality rates across different AKI stages. Multivariate logistic regression analysis was performed to identify independent risk factors for progression to AKI stages 2\u0026ndash;3, both in the overall cohort and within subgroups based on ECMO modality. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves. All statistical tests were two-tailed, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003ePatient Characteristics\u003c/h2\u003e\u003cp\u003eA total of 210 patients receiving ECMO therapy were included in the study. Among them, 100 patients (47.6%) were classified into the AKI stages 0\u0026ndash;1 group, while 110 patients (52.4%) were classified into the AKI stages 2\u0026ndash;3 group. A comparison of baseline characteristics and clinical outcomes is provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Compared to patients in the AKI stages 0\u0026ndash;1 and stage 2 groups, those in the AKI stage 3 group were younger, had higher body weight, elevated APACHE II scores, and a greater prevalence of cardiac arrest and cardiogenic shock. Additionally, the use of VA-ECMO modality and vasopressors was more frequent in this group, and levels of procalcitonin (PCT) and D-dimer were significantly elevated, with a marked reduction in platelet (PLT) count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Hospital length of stay varied across the three groups, with patients in the AKI stage 3 group having a significantly shorter hospital stay (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, the 30-day mortality rate did not differ significantly between the groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Dynamic monitoring of Scr levels over 7 days following ECMO initiation revealed a daily decrease in the proportion of patients in AKI stages 0\u0026ndash;1, a gradual increase in those in stage 2, and a stable proportion of patients in stage 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Kaplan-Meier analysis demonstrated that the 30-day cumulative survival rate was significantly lower in the AKI stage 3 group compared to the AKI stages 0\u0026ndash;1 and stage 2 groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while no significant difference was observed between the AKI stages 0\u0026ndash;1 and stage 2 groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of baseline characteristics and clinical outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical Variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAKI stages 0\u0026ndash;1(N\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAKI stage 2\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAKI stage 3\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;89)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eDemographics\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68 (68.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (85.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58 (65.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54 (39, 61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53 (49, 61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49 (33, 56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight, cm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e168.0 (165.5, 170.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e170.0 (168.0, 172.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168.0 (165.0, 172.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight, Kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.0 (60.0, 65.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.0 (48.0, 64.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63.0 (62.0, 71.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedical history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31 (31.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (42.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (32.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes Mellitus, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (17.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (19.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (14.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACS, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (17.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (9.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (10.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCOPD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (6.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVital signs at admission\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature, ℃\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37.0 (36.0, 37.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.0 (36.0, 37.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.0 (36.0, 37.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart rate, bpm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99 (87, 112)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e105 (99, 116)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e108 (85, 122)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSBP, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e114.0 (104.0, 127.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e113.0 (107.0, 128.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e113.0 (95.0, 129.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBP, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75.0 (66.5, 84.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.0 (67.0, 81.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.5 (59.0, 78.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDisease severity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAPACHE II score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.5 (17.0, 26.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.5 (17.0, 20.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.0 (20.5, 31.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIndications for ECMO initiation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcute Respiratory Failure, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (15.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (12.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiac Arrest, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (8.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (18.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiogenic Shock, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (14.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (19.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (39.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eECMO modality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVA-ECMO, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (42.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (47.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70 (78.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVasoactive drugs\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorepinephrine, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74 (74.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (90.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e87 (97.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEpinephrine, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72 (72.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (90.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85 (95.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDopamine, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (21.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (23.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44 (49.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLaboratory test results\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC, \u0026times;10⁹\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.8 (7.7, 15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.5 (6.1, 15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.0 (6.9, 17.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeu, \u0026times;10⁹\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.7 (6.0, 13.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.6 (4.5, 13.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.2 (4.9, 15.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBC, \u0026times;10\u0026sup1;\u0026sup2;\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0 (3.6, 4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.4 (3.8, 4.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.0 (3.4, 4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHb, g\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e121.5 (109.0, 136.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e131.0 (110.0, 139.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e123.0 (102.0, 141.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT, \u0026times;10⁹\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e175.5 (144.5, 236.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e227.0 (160.0, 311.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e145.0 (70.0, 206.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP, mg\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.4 (11.2, 95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.9 (5.6, 80.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.7 (15.0, 121.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCT, ng\u0026middot;mL\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3 (0.1, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2 (0.1, 0.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1 (0.3, 2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScr, \u0026micro;mol\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.8 (52.4, 110.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55.8 (44.8, 91.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e140.6 (74.5, 234.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBUN, mmol\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.2 (5.1, 9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0 (4.6, 11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.2 (6.6, 13.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBIL, \u0026micro;mol\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.7 (9.0, 22.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.6 (6.1, 16.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.0 (11.2, 30.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBIL, \u0026micro;mol\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.5 (3.9, 8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.5 (3.9, 7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.8 (5.2, 14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALB, g\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.9 (27.1, 36.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.4 (25.6, 39.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.9 (24.6, 34.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLAC, mmol\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.9 (2.2, 5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.9 (1.9, 5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.5 (2.9, 6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAPTT, s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.4 (26.7, 38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.3 (28.5, 55.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.7 (31.9, 62.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePT, s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.4 (12.5, 15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.4 (12.7, 15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.6 (14.0, 21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTT, s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.5 (16.2, 19.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.6 (16.7, 30.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.4 (17.7, 37.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD-dimer, mg\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.5 (1.1, 9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.6 (2.5, 6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.1 (4.1, 25.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFig, g\u0026middot;L\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0 (2.2, 5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.3 (2.0, 4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.9 (1.9, 5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eArterial blood gas analysis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.4 (7.3, 7.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.4 (7.3, 7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.3 (7.2, 7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCO\u003csub\u003e2\u003c/sub\u003e, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.3 (29.8, 38.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.0 (24.5, 53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.4 (31.1, 41.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO\u003csub\u003e2\u003c/sub\u003e, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.9 (54.3, 116.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.9 (59.2, 214.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.0 (48.0, 84.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.4 (19.9, 23.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.9 (17.7, 24.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.9 (16.8, 20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eClinical outcome\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospital length of stay, days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21 (11, 32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (15, 46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.0 (3, 23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeath, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (23.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (38.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eData are presented as n (%) or median (interquartile range) as appropriate. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. APACHE II, Acute Physiology and Chronic Health Evaluation II; APTT, Activated Partial Thromboplastin Time; ALB, Albumin; BUN, Blood Urea Nitrogen; COPD, Chronic Obstructive Pulmonary Disease; CRP, C-Reactive Protein; DBIL, Direct bilirubin; ECMO, Extracorporeal Membrane Oxygenation; Fig, Fibrinogen; Hb, Hemoglobin; HCO₃⁻, Bicarbonate; LAC, Lactate; Neu, neutrophil; pH, Potential of Hydrogen; PLT, Platelet; PCT, Procalcitonin; PCO₂, Arterial partial pressure of carbon dioxide; PO₂, Arterial partial pressure of oxygen; PT, Prothrombin Time; RBC, Red Blood Cell; Scr, Serum creatinine; TBIL, Total bilirubin; TT, Thrombin Time; VA-ECMO, Venoarterial Extracorporeal Membrane Oxygenation; WBC, White Blood Cell.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eECMO initiation\u003c/h3\u003e\n\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ns, no significant difference.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEffect of AKI severity on 30-day mortality in ECMO patients\u003c/h2\u003e\u003cp\u003eTo explore the prognostic value of AKI staging for 30-day mortality in ECMO patients. Cox regression analysis revealed that AKI stage 3 significantly increased the 30-day mortality risk, irrespective of APACHE II score adjustments. Unadjusted HR\u0026thinsp;=\u0026thinsp;2.01 (95%\u003cem\u003eCI\u003c/em\u003e 1.19\u0026ndash;3.40, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01); adjusted HR\u0026thinsp;=\u0026thinsp;1.29 (95%\u003cem\u003eCI\u003c/em\u003e 1.13\u0026ndash;1.86, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), making it an independent risk factor for 30-day mortality. Subgroup analysis demonstrated that in the VV-ECMO subgroup, AKI stage 3 significantly increased the mortality risk (unadjusted HR\u0026thinsp;=\u0026thinsp;3.17, 95%\u003cem\u003eCI\u003c/em\u003e 1.27\u0026ndash;7.93, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013; adjusted HR\u0026thinsp;=\u0026thinsp;2.09, 95%\u003cem\u003eCI\u003c/em\u003e 1.29\u0026ndash;5.50, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038). In contrast, no significant association between AKI stage 3 and 30-day mortality risk was found in the VA-ECMO subgroup, regardless of APACHE II score adjustments (unadjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.51; adjusted \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.444). Furthermore, each 1-point increase in APACHE II score was associated with a 10%-12% increase in mortality risk (HR\u0026thinsp;=\u0026thinsp;1.10\u0026ndash;1.12, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Kaplan- Meier survival curves demonstrated that the 30-day cumulative survival rate was significantly lower in patients with moderate-to-severe AKI (stages 2\u0026ndash;3) compared to those in AKI stages 0\u0026ndash;1 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCOX regression analysis of the association between AKI grade and 30-day mortality risk in ECMO patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eAll ECMO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eVA-ECMO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eVV-ECMO\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnadjusted APACHE II score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stages 0\u0026ndash;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u003cp\u003ereference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stage 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.31\u0026thinsp;~\u0026thinsp;2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.23\u0026thinsp;~\u0026thinsp;2.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.15\u0026thinsp;~\u0026thinsp;2.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.585\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stage 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.19\u0026thinsp;~\u0026thinsp;3.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.64\u0026thinsp;~\u0026thinsp;2.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.512\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.27\u0026thinsp;~\u0026thinsp;7.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stages 2\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01\u0026thinsp;~\u0026thinsp;2.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.03\u0026thinsp;~\u0026thinsp;2.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.20\u0026thinsp;~\u0026thinsp;4.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted APACHE II score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e95% \u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stages 0\u0026ndash;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c10\" namest=\"c2\"\u003e\u003cp\u003ereference\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stage 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.32\u0026thinsp;~\u0026thinsp;2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.27\u0026thinsp;~\u0026thinsp;3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.17\u0026thinsp;~\u0026thinsp;3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.713\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stage 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.13\u0026thinsp;~\u0026thinsp;1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.36\u0026thinsp;~\u0026thinsp;1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.29\u0026thinsp;~\u0026thinsp;5.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKI stages 2\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.28\u0026thinsp;~\u0026thinsp;2.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.24\u0026thinsp;~\u0026thinsp;2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.02\u0026thinsp;~\u0026thinsp;3.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAPACHE II score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.07\u0026thinsp;~\u0026thinsp;1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.07\u0026thinsp;~\u0026thinsp;1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.03\u0026thinsp;~\u0026thinsp;1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. APACHE II, Acute Physiology and Chronic Health Evaluation II; AKI, Acute kidney injury; ECMO, Extracorporeal Membrane Oxygenation; VA-ECMO, Venoarterial Extracorporeal Membrane Oxygenation; VV-ECMO, Venovenous Extracorporeal Membrane Oxygenation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e* P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eModality-specific risk factors for moderate-to-severe AKI in ECMO patients\u003c/h2\u003e\u003cp\u003eTo further demonstrated the influence of ECMO modality on the risk of moderate-to-severe AKI. Multivariate logistic regression in the overall cohort identified the following independent risk factors for moderate-to-severe AKI in ECMO patients: VA-ECMO modality (OR\u0026thinsp;=\u0026thinsp;3.28, 95%\u003cem\u003eCI\u003c/em\u003e: 1.83\u0026ndash;5.89, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), norepinephrine (NE) use (OR\u0026thinsp;=\u0026thinsp;2.40, 95%\u003cem\u003eCI\u003c/em\u003e: 1.24\u0026ndash;4.64, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), and low fibrinogen levels (OR\u0026thinsp;=\u0026thinsp;0.75, 95%\u003cem\u003eCI\u003c/em\u003e: 0.64\u0026ndash;0.89, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). But a history of cardiovascular disease was identified as a protective factor (OR\u0026thinsp;=\u0026thinsp;0.38, 95% \u003cem\u003eCI\u003c/em\u003e: 0.17\u0026ndash;0.87, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021). The model's combined predictive AUC was 0.78.\u003c/p\u003e\u003cp\u003eFurther analysis of risk factors for moderate-to-severe AKI by ECMO modality revealed that in the VV-ECMO subgroup, elevated levels of lactate (LAC) (OR\u0026thinsp;=\u0026thinsp;1.39, 95% \u003cem\u003eCI\u003c/em\u003e: 1.11\u0026ndash;1.77), bicarbonate (HCO₃⁻) (OR\u0026thinsp;=\u0026thinsp;1.11, 95% \u003cem\u003eCI\u003c/em\u003e: 1.00-1.22), C-reactive protein (CRP) (OR\u0026thinsp;=\u0026thinsp;1.01, 95% \u003cem\u003eCI\u003c/em\u003e: 1.00-1.02), procalcitonin (PCT) (OR\u0026thinsp;=\u0026thinsp;1.36, 95% \u003cem\u003eCI\u003c/em\u003e: 1.04\u0026ndash;1.78), blood urea nitrogen (BUN) (OR\u0026thinsp;=\u0026thinsp;1.16, 95%\u003cem\u003eCI\u003c/em\u003e: 1.02\u0026ndash;1.31), and a reduction in fibrinogen (OR\u0026thinsp;=\u0026thinsp;0.58, 95% \u003cem\u003eCI\u003c/em\u003e: 0.40\u0026ndash;0.83), total bilirubin (TBIL) (OR\u0026thinsp;=\u0026thinsp;0.85, 95% \u003cem\u003eCI\u003c/em\u003e: 0.76\u0026ndash;0.96), and white blood cell (WBC) count (OR\u0026thinsp;=\u0026thinsp;0.89, 95% \u003cem\u003eCI\u003c/em\u003e: 0.80\u0026ndash;0.99) were all independent risk factors (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with an AUC of 0.89. However, in the VA-ECMO subgroup, NE use (OR\u0026thinsp;=\u0026thinsp;2.47, 95% \u003cem\u003eCI\u003c/em\u003e: 1.10\u0026ndash;5.53, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028) was the only independent risk factor identified, while a history of cardiovascular disease (OR\u0026thinsp;=\u0026thinsp;0.35, 95% \u003cem\u003eCI\u003c/em\u003e: 0.13\u0026ndash;0.95, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039) acted as a protective factor. The predictive AUC for this subgroup was 0.76. Although pre-ECMO cardiogenic shock and ARDS showed relatively high odds ratios, these differences did not reach statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), likely due to the limited sample size (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ein ECMO patients\u003c/h2\u003e\u003cp\u003eARDS, acute respiratory distress syndrome; BUN, Blood Urea Nitrogen; CRP, C-Reactive Protein; DBIL, Direct bilirubin; ECMO, Extracorporeal Membrane Oxygenation; Fig, Fibrinogen; HCO₃⁻, Bicarbonate; Hb, Hemoglobin; LAC, Lactate; NE, norepinephrine; PCT, Procalcitonin; PO₂, Arterial partial pressure of oxygen; PLT, Platelet; Scr, Serum creatinine; TBIL, Total bilirubin; Temp, Temperature; TT, Thrombin Time; VA-ECMO, Venoarterial Extracorporeal Membrane Oxygenation; VV-ECMO, Venovenous Extracorporeal Membrane Oxygenation; WBC, White Blood Cell.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study retrospectively analyzed the dynamic changes in different stages of AKI and their prognostic differences in patients undergoing ECMO, and explored the associated risk factors for moderate-to-severe AKI under different ECMO modalities. The results showed that the incidence of moderate-to-severe AKI was approximately 52.4%. Among these patients, the proportion of those with AKI stage 2 gradually increased within the first 7 days after ECMO initiation, whereas AKI stage 3 was an independent risk factor for 30-day mortality. In addition, VA-ECMO modality, the use of NE, and low fibrinogen levels were found to increase the risk of moderate-to- severe AKI, while a history of cardiovascular disease appeared to have a protective effect. In VV-ECMO patients, metabolic disorders, inflammatory responses, and coagulation abnormalities were the primary risk factors, whereas in VA-ECMO patients, only NE use was independently associated with moderate-to-severe AKI.\u003c/p\u003e\u003cp\u003eIn this study, approximately 42.4% of AKI patients had AKI stage 3, which was lower than the 53.8% reported by Vinclair \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This difference may be related to differences in the study population and diagnostic criteria: first, Vinclair \u003cem\u003eet al\u003c/em\u003e. included only VA-ECMO patients, whereas in this study, about half of the cases were VA-ECMO, which aligns with the characteristics of emergency situations where a large number of patients with refractory circulatory failure require VA-ECMO support. VA-ECMO patients are more prone to severe AKI due to hemodynamic instability, frequent use of vasoactive drugs [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], whereas VV-ECMO patients tend to have more stable hemodynamics [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Secondly, Vinclair \u003cem\u003eet al\u003c/em\u003e. used the highest KDIGO classification during ICU admission to determine AKI stage 3, whereas this study assessed KDIGO classification within 7 days after ECMO initiation. Consequently, some patients who progressed to AKI stage 3 after 7 days were not included, which likely led to a lower AKI incidence. Another studies also used Scr changes within 7 days as a criterion for diagnosing AKI, with nearly half of their patients progressed to AKI stage 3 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which is similar to the findings in this study. The focus on AKI occurrence within the first 7 days in this study is based on previous research showing that 90% of AKI cases occur within the first 7 days of hospitalization [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Another key finding of this study was that the proportion of AKI stage 3 patients did not change significantly within the first 7 days after ECMO initiation, while the number of AKI stage 2 patients increased significantly. This suggests that AKI stage 2 patients require closer monitoring within the first week of ECMO therapy. However, for patients who undergo prolonged ECMO support, the specific incidence and timing of AKI after 7 days require further investigation through larger-scale studies.\u003c/p\u003e\u003cp\u003eThis study also found that, whether or not APACHE II was adjusted, AKI stage 3 significantly increased the risk of 30-day mortality. This is consistent with the findings of Vinclair \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and other multicenter studies. In Vinclair's study, AKI stage 3 on the day of VA-ECMO initiation was independently associated with one-year mortality (OR\u0026thinsp;=\u0026thinsp;10.20). Furthermore, this study showed that for every one-point increase in the APACHE II score, the risk of death increased by approximately 10%-12%, which is consistent with previous reports [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This indicates that the APACHE II score remains a reliable tool for prognostic assessment in ECMO patients, and it also suggests that clinical evaluations of these patients should consider the overall severity of their condition. Further analysis of AKI risk factors revealed that VA-ECMO modality, NE use, and low fibrinogen levels were independent risk factors for moderate-to-severe AKI across all ECMO patients. This is likely because VA-ECMO is commonly used in patients with severe circulatory failure, and its non-pulsatile perfusion, increased afterload, and other non-physiological hemodynamic characteristics interact with the shock-induced low perfusion state, increasing the risk of renal hypoperfusion and injury [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, the ECMO circuit in VA-ECMO involves mechanical shear stress and contact with non-physiological surfaces such as the oxygenator, which can cause hemolysis and microthrombus formation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, the use of NE was associated with an increased risk of moderate-to-severe AKI in VA-ECMO patients (OR\u0026thinsp;=\u0026thinsp;2.40\u0026ndash;2.47). Similar conclusions were drawn by Huette \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], with NE's activation of α-1 receptors increasing systemic vascular resistance and inducing vasoconstriction, which could contribute to AKI [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In contrast, this study found that a history of cardiovascular disease had a protective effect in both all ECMO and VA-ECMO subgroup patients (OR\u0026thinsp;=\u0026thinsp;0.35\u0026ndash;0.38), possibly because chronic heart disease patients tend to receive earlier and more rigorous volume management strategies or left ventricular unloading when ECMO is initiated [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore, metabolic disorders, inflammatory responses, and coagulation abnormalities were identified as risk factors for moderate-to-severe AKI in VV-ECMO patients. This may be related to the fact that VV-ECMO is commonly used in patients with severe ARDS [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and other respiratory failure [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and ongoing hypoxemia and lactate accumulation during the course of the disease can lead to renal cortical ischemia and acidotic tubular damage [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study is one of the largest multi-center retrospective studies in China to date, but it does have limitations: ①The overall sample size of ECMO patients is still relatively small, and some results may be affected by statistical power, likely due to the high cost and technical complexity of ECMO treatment, which makes patient enrollment challenging. ②Although the APACHE II score was corrected in the multivariate model, it is impossible to completely control for confounding factors such as ECMO treatment parameters and anticoagulation protocols. ③The diagnosis of AKI did not include urine output criteria, meaning that patients with oliguria or anuria who did not meet the Scr threshold were omitted, which may lead to an underestimation of AKI incidence.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn the present study, the incidence of AKI in ECMO patients is high and significantly affects their prognosis. The risk of AKI varies significantly across different ECMO modalities, suggesting that clinical practice should include individualized risk stratification and early interventions based on ECMO modality and associated risk factors to improve patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to participate\u003c/strong\u003e\u003cp\u003e The study was approved by the Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China (Approval No. 2024-ky300) and conducted in accordance with the Declaration of Helsinki. Informed consent was waived due to the retrospective design and use of anonymized data.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors declare that there are no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study was supported by the Natural Science Foundation of Anhui Province (2208085MH235).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYW, XW, and KJ contributed to the conception and design of the study. YW, XW, JS, YW, XZ, and HM contributed to data acquisition. YW and KJ drafted the manuscript. YW, XW, JS, and YW performed data analysis. YW, XW, YW, and KJ edited and critically revised the manuscript. YW and KJ approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eThe authors would like to thank all the medical staff, patients and their families in the three ECMO medical centers for their support in this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to sensible personal clinical data, but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGuru PK, Balasubramanian P, Ghimire M, et al. Acute kidney injury in patients before and after extracorporeal membrane oxygenation (ECMO) - Retrospective longitudinal analysis of the hospital outcomes[J]. 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Br J Anaesth. 2025;134(1):54\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi:10.1016/j.bja.2024.11.005\u003c/span\u003e\u003cspan address=\"https://doi:10.1016/j.bja.2024.11.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"extracorporeal membrane oxygenation, acute kidney injury, risk factors, APACHE II score","lastPublishedDoi":"10.21203/rs.3.rs-7968769/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7968769/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo identify independent risk factors for acute kidney injury (AKI) in critically ill patients undergoing extracorporeal membrane oxygenation (ECMO) and to evaluate the association between AKI severity and 30-day mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective multicenter cohort study across three provincial ECMO medical centers was conducted between September 2019 and June 2024. Serum creatinine levels within the first 7 days following ECMO initiation were collected, and AKI was staged according to KDIGO criteria, with dynamic progression tracked over time. Multivariable logistic regression was used to identify predictors of moderate-to-severe AKI (AKI stages 2\u0026ndash;3). Survival analysis was performed using Kaplan-Meier curves, and Cox proportional-hazards models were applied to assess the impact of AKI stage on 30-day mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 210 enrolled patients, 100 (47.6%) had AKI stages 0\u0026ndash;1, while 110 (52.4%) developed AKI stages 2\u0026ndash;3 within 7 days after ECMO initiation. Serial creatinine monitoring indicated a gradual increase in AKI stage 2, whereas the incidence of AKI stage 3 plateaued. Cox regression analysis demonstrated that moderate-to-severe AKI was independently associated with 30-day mortality, both before and after adjustment for APACHE II score (adjusted HR\u0026thinsp;=\u0026thinsp;1.29, 95%\u003cem\u003eCI\u003c/em\u003e 1.13\u0026ndash;1.86, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the overall cohort, VA-ECMO modality, norepinephrine use, and low fibrinogen level were significant risk factors for AKI stages 2\u0026ndash;3, while pre-existing cardiac disease was protective (AUC 0.78). Subgroup analysis showed that for VV-ECMO patients, elevated LAC, HCO₃⁻, CRP, PCT, and BUN, as well as decreased fibrinogen, TBIL, and WBC count, were associated with AKI risk (AUC\u0026thinsp;=\u0026thinsp;0.89).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eAKI is an independent risk factor for 30-day mortality in ECMO patients. VA-ECMO modality, vasopressor use, and low fibrinogen levels increase the risk of moderate-to-severe AKI, with risk profiles varying by ECMO modality. Early identification of high-risk phenotypes and mode-specific management strategies are essential to improving outcomes.\u003c/p\u003e","manuscriptTitle":"Risk Factors and Mortality Impact of Acute Kidney Injury in Different ECMO Modalities: A Multicenter Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 00:48:45","doi":"10.21203/rs.3.rs-7968769/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc8d3cbd-2b2b-4865-a465-5f5cd324340f","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-24T06:09:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 00:48:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7968769","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7968769","identity":"rs-7968769","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}