Vancomycin Therapeutic Drug Monitoring Reduces Toxicity in ICU Patients: A MIMIC-IV Retrospective Study

Vancomycin Therapeutic Drug Monitoring Reduces Toxicity in ICU Patients: A MIMIC-IV 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 Article Vancomycin Therapeutic Drug Monitoring Reduces Toxicity in ICU Patients: A MIMIC-IV Retrospective Study Jia Wang, Chuzhu Huang, Yan Chen, Yilin Huang, Zhuomin Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7437818/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 14 You are reading this latest preprint version Abstract Background : Vancomycin is a first-line treatment for methicillin-resistant Staphylococcus aureus (MRSA)infections but is associated with risks of nephrotoxicity (5–43%), hepatotoxicity, and hematotoxicity. Therapeutic drug monitoring (TDM) is recommended to optimize dosing, yet its impact on multi-organ toxicity and mortality in intensive care unit (ICU) patients remains controversial because ofconflicting evidence and methodological limitations in prior studies. Methods : Data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v3.1) database for a retrospective cohort analysis of 28,451 ICU patients receiving intravenous vancomycin. The primary outcomes were vancomycin-associated nephrotoxicity (AKI according to the KDIGO criteria), hepatotoxicity (ALT/AST ≥120 U/L or bilirubin ≥2.5 mg/dL), and hematotoxicity (thrombocytopenia, anemia, or leukopenia); secondary outcomes included ICU / hospital mortality. Propensity score matching (PSM, 1:1 nearest neighbor with caliper=0.1) balanced 32 baseline covariates,including demographics. The associations between TDM and outcomes were evaluated via multivariable logistic regression and Cox proportional hazards models, with the results validated through subgroup analyses (stratified by comorbidities and concomitant medications) and sensitivity analyses. Results : Data from 28,451 ICU patients receiving intravenous vancomycin were extracted from the MIMIC-IV database, with 10,758 (37.8%) receiving TDM and 17,693 (62.2%) not receiving TDM. Before PSM, the TDM group presented higher baseline illness severity scores (e.g., SOFA, APS III) and more comorbidities. Unadjusted analyses revealed increased risks of adverse outcomes in the TDM group (AKI: OR = 2.98, 95% CI: 2.83–3.15; hematotoxicity: OR = 1.97, 95% CI: 1.88–2.07; hepatotoxicity: OR = 2.34, 95% CI: 2.19–2.50; all P < 0.001). However, with progressive adjustment for confounders, these associations attenuated significantly (Model 3: AKI OR = 1.93, hematotoxicity OR = 1.55, hepatotoxicity OR = 1.25; all P < 0.001). After PSM, the TDM group demonstrated significantly reduced risks of AKI (OR = 0.580, 95% CI: 0.540–0.610, P = 0.001), hematotoxicity (OR = 0.760, 95% CI: 0.710–0.800, P = 0.001), and hepatotoxicity (OR = 0.800, 95% CI: 0.750–0.860, P = 0.001). Secondary outcomes also favored TDM, with lower in-hospital mortality (OR = 0.672, 95% CI: 0.570–0.790, P = 0.001) and ICU mortality (OR = 0.691, 95% CI: 0.580–0.820, P = 0.001). Kaplan-Meier analysis further confirmed the survival benefits of TDM in both ICU and hospital settings (log-rank P < 0.001). Subgroup analyses revealed that hypertension, type 2 diabetes mellitus (T2DM), cancer, cerebral bleeding (CB), and concomitant use of aspirin or antibiotics weresignificant risk factors for nephrotoxicity, hematotoxicity and hepatotoxicity. Conclusion : This study demonstrated that vancomycin TDM significantly reduces toxicity risks (nephrotoxicity, hepatotoxicity, hematotoxicity) and mortality in intensive care unit (ICU) patients, supporting its routine use in critically ill populations. Health sciences/Diseases Health sciences/Medical research Health sciences/Nephrology Health sciences/Risk factors Vancomycin therapeutic drug monitoring ICU nephrotoxicity hepatotoxicity hematotoxicity MIMIC-IV Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Vancomycin is the first-line antibiotic for treating methicillin-resistant Staphylococcus aureus (MRSA) infections and is also employed in the management of other severe gram-positive bacterial infections[ 1 ]. As one of the most widely used antibiotics in the United States, vancomycin has been in clinical use for nearly 50 years [ 2 ]. Nonetheless, its application has long been complicated by a narrow therapeutic window and the risk of toxicity. Research has indicated that S. aureus infections, particularly MRSA infections, significantly increase patient morbidity, mortality, and healthcare burdens [ 3 ][ 4 ][ 5 ][ 6 ][ 7 ]. Moreover, vancomycin therapy can cause various adverse reactions, including red man syndrome [ 8 ], nephrotoxicity [ 8 ][ 9 ][ 10 ], and ototoxicity [ 11 ][ 12 ]. The incidence of acute kidney injury (AKI) associated with vancomycin ranges from 5–43% [ 13 ], with a 2.45-fold higher risk of nephrotoxicity than that associated with non-glycopeptide antibiotics [ 14 ]. Importantly, this increased risk exists independently of other confounding factors. There is substantial evidence linking vancomycin to nephrotoxicity, demonstrating this association even when vancomycin is not explicitly classified as nephrotoxic in guidelines [ 15 ]. To optimize therapeutic efficacy while minimizing toxicity, therapeutic drug monitoring (TDM) of vancomycin is currently recommended by organizations such as the American Society of Health-System Pharmacists (ASHP), the Infectious Diseases Society of America (IDSA), and the Japanese Society of Chemotherapy [ 2 ][ 16 ]. However, the evidence supporting these recommendations remains contentious. On the one hand, the TDM criteria in these guidelines are primarily based on pharmacodynamic targets, such as the area under the concentration‒time curve to minimum inhibitory concentration ratio (AUC/MIC), which may not be fully applicable to patients in ICU, whose pathophysiological states can significantly vary. On the other hand, several studies have reported that TDM implementation has not markedly improved clinical outcomes or decreased the incidence of nephrotoxicity [ 2 ]. Moreover, some research indicates that the cost-effectiveness of TDM may be limited to specific high-risk populations, including ICU patients, those receiving concomitant nephrotoxic drugs, or oncology patients [ 17 ]. This ongoing debate highlights a critical issue: without high-quality evidence, the clinical value of vancomycin TDM remains to be conclusively established. Current research on vancomycin TDM has notable limitations. Most studies have focused primarily on nephrotoxicity and have often neglected other critical adverse effects, such as hepatotoxicity and hematologic toxicity. Additionally, there is a paucity of research specifically targeting ICU populations, with existing studies confounded by factors such as concomitant nephrotoxic drugs, hemodynamic fluctuations, and underlying diseases. To address these gaps, the present study utilized the MIMIC-IV database—a comprehensive, real-world dataset—to systematically evaluate the impact of vancomycin TDM on multiorgan toxicity, including nephrotoxicity, hepatotoxicity, and hematotoxicity. Employing a rigorous methodological approach—including a large sample size (n = 28,451), propensity score matching (PSM), and multiple sensitivity analyses—this study aims to provide a more reliable and high-quality evidence base to inform clinical practice. Ultimately, we hope these findings will facilitate more precise individualized dosing strategies for vancomycin therapy in ICU patients. 2 Materials and methods 2.1 Sources of Data This retrospective study utilized health-related data obtained from the MIMIC-IV (version 3.1) database, a comprehensive and extensive resource developed and managed by the MIT Computational Physiology Laboratory. This database comprises high-quality medical MIMIC-IV contains de-identified clinical data corresponding to all medical record numbers of patients admitted to the ICU or emergency department between 2008 and 2022 records of patients admitted to the intensive care units of the Beth Israel Deaconess Medical Center. MIMIC-IV contains de-identified clinical data corresponding to all medical record numbers of patients admitted to the ICU or emergency department between 2008 and 2022 [18]. Jia Wang, one of the authors, collected clinical data from the MIMIC database (certification number: 42257067), including patient demographic information, laboratory findings, and medication usage. This project adhered to the principles of the Helsinki Declaration, and approval from the ethics committee was not required because of participant anonymity and data standardization within the database. 2.2 Study population All adult patients (≥18 years) admitted to the ICU recorded in the MIMIC-IV database were screened for this study. We included patients who were administered vancomycin intravenously after ICU admission. Vancomycin TDM was defined as at least one measurement of the blood vancomycin concentration in laboratory indices at MIMIC-IV during ICU hospitalization. We categorized patients who were or were not treated with vancomycin TDM into a vancomycin group (TDM group) and a control group (non-TDM group). For patients with multiple ICU admissions, only data from their first ICU stay were analyzed. The patient enrollment process for this study is depicted in Figure 1. 2.3 Data collection and definitions Structured Query Language (SQL) was employed to extract data via Navicat Premium software (version 15) on the basis of unique patient identifiers (e.g., stay_id). We collected demographic information, including age, sex, BMI, and race. Disease severity and laboratory indices were assessed via the SOFA score, APS III score, SAPS II score, OASIS score, GCS score, Charlson comorbidity index, and APACHE II score within the first 24 hours of ICU admission. The SIRS criteria were also evaluated. Comorbidities were identified using ICD-9/10 codes, including hypertension, liver cirrhosis, hepatitis, CVA, CKD, cancer, T1DM and T2DM, obesity, sepsis, CB, HF, MI, and IHD, were identified via ICD-9/10 codes. The use of medications, including aspirin and antibiotics, was documented. The laboratory variables collected included RDW, red blood cell count, creatinine, BUN, calcium, chloride, and glucose. The primary outcomes included AKI, hematotoxicity, and hepatotoxicity. The secondary outcomes included Hosp Day and Icu Day. In this study, nephrotoxicity was defined according to the AKI criteria [19], with patients considered positive if they exhibited either an absolute serum creatinine (Cr) increase ≥0.3 mg/dL or a ≥50% Cr elevation from baseline (highest value within 3 days prevancomycin) during treatment [13][20], confirmed by two consecutive measurements. Hematotoxicity was identified by laboratory abnormalities: thrombocytopenia (platelet count <100×10^9/L), leukopenia (white blood cell count <4×10^9/L), neutropenia (absolute neutrophil count <1.5×10^9/L), or anemia (hemoglobin <10 g/dL). Hepatotoxicity required elevations in alanine aminotransferase (ALT ≥120 U/L), aspartate aminotransferase (AST ≥120 U/L), or total bilirubin (≥2.5 mg/dL). All laboratory values were assessed via baseline measurements taken within 24 hours of ICU admission or pretreatment. Patients meeting ≥1 criterion for any toxicity were classified as affected, ensuring standardized and clinically meaningful assessment. 2.4 Outcomes This study aimed to investigate the impact of TDM on medication safety during vancomycin administration in ICU patients. The primary safety endpoints studied include nephrotoxicity, hematotoxicity, and hepatotoxicity. Secondary outcomes focus on the associations between TDM and in-hospital mortality and ICU mortality. In addition, the study will assess the impact of different comorbidities (e.g., hypertension, liver cirrhosis, hepatitis, etc.). on the effect of TDM through subgroup analyses, with a special focus on whether concomitant use of nephrotoxic medications (e.g., aspirin, antibiotics) affects the safety profile of vancomycin. 2.5 Statistical analysis In this study, continuous variables did not follow a normal distribution and are therefore presented as medians with interquartile ranges (IQRs). Categorical variables are expressed as frequencies and percentages. The baseline characteristics of statin-treated and untreated patients were compared via the Mann‒Whitney test for continuous variables and the chi‒square test for categorical variables. Variables with less than 20% missing data were retained. All missing values were addressed via multiple imputation methods in SPSS version 27. Multivariable logistic regression models were constructed to adjust for potential confounders in assessing the associations between TDM use and outcomes. Cox proportional hazards models were employed to estimate the associations of TDM use with survival rates in both hospital and ICU settings. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for all the models. Model 1 (Crude): Unadjusted analysis. Model 2: Adjusted for race, hypertension, liver cirrhosis, CVA, CKD, cancer, T2DM, T1DM, obesity, sepsis, CB, HF, MI, IHD, aspirin, and antibiotics. Model 3 (Fully Adjusted): Further adjusted for hepatitis, SIRS, age, BMI, SOFA score, APS III, SAPS II, OASIS, GCS, Charlson comorbidity index, APACHE II score, RDW, red blood cell count, creatinine, BUN, calcium, chloride, and glucose. For survival outcomes (in-hospital and in-ICU mortality), HRs and 95% CIs were derived from Cox models via the same adjustment hierarchy. To control for potential confounders, PSM was performed in this study via a 1:1 nearest-neighbor matching method with a caliper value set at 0.1. The matched variables included all the baseline variables except the outcome indicators (AKI, hematotoxicity, and hepatotoxicity). The balance of covariates after matching was assessed by the standardized mean difference (SMD). In the matched cohort, the associations of TDM with the primary safety outcomes (AKI, hematotoxicity, and hepatotoxicity) were assessed via logistic regression analysis. Moreover, the Cox proportional risk model was used to analyze the association of TDM with secondary outcomes (hospital mortality and ICU mortality). Subgroup analyses were performed to assess potential effect modifications by clinically relevant factors, including comorbidities (e.g., hypertension, liver cirrhosis, hepatitis, CVA, CKD, cancer, T1DM and T2DM, obesity, sepsis, CB, HF, MI, and IHD), and concomitant medications (e.g., aspirin, antibiotics). All the statistical analyses were performed via R version 4.4.1 and SPSS version 27. A two-sided P value of less than 0.05 was considered statistically significant. 3 Results 3.1 Patient characteristics A total of 28,451 ICU patients receiving intravenous vancomycin were included in this study from the MIMIC-IV database ( Table 1 ), with 10,758 (37.8%) undergoing TDM and 17,693 (62.2%) not receiving TDM. Before PSM, the TDM group was significantly older (median age 68 vs. 66 years, p < 0.001) and had higher illness severity scores (SOFA score: 3 vs. 3, p < 0.001; APS III score: 38 vs. 36, p < 0.001). Comorbidities such as hypertension (97.74% vs. 94.83%, p < 0.001), liver cirrhosis (0.12% vs. 0.24%, p = 0.003), and sepsis (1.05% vs. 0.75%, p < 0.001) were more prevalent in the TDM group. After PSM (9,785 patients per group), all baseline characteristics were well balanced (SMD < 0.10) ( Figure 2 ). The TDM group had a lower incidence of AKI (23.21% vs. 34.95%, p < 0.001), with reduced AKI severity (stage 3: 43.20% vs. 27.57%, p < 0.001). Hematotoxicity was less common in the TDM group (45.03% vs. 52.36%, p < 0.001), whereas hepatotoxicity was more common (23.33% vs. 18.48%, p < 0.001). The hospital length of stay was longer in the TDM group (median 9.73 vs. 8.88 days, p < 0.001), as was the ICU stay (1.76 vs. 1.62 days, p < 0.001). Table 1 . Baseline characteristics of patients before and after propensity score matching Variables Before PSM After PSM Total (n = 28451) Non TDM (n = 17693) TDM (n = 10758) P Total (n = 19570) Non TDM (n = 9785) TDM (n = 9785) P Patient characteristics Age, M (Q₁, Q₃) 68.00 (57.00, 79.00) 69.00 (59.00, 79.00) 66.00 (55.00, 77.00) <.001 67.00 (56.00, 78.00) 68.00 (57.00, 79.00) 67.00 (55.00, 78.00) <.001 BMI, M (Q₁, Q₃) 27.76 (24.06, 32.32) 27.68 (24.06, 32.01) 27.96 (24.02, 32.91) <.001 27.73 (23.95, 32.43) 27.65 (23.92, 32.20) 27.85 (23.98, 32.72) 0.002 Gender, n(%) 0.243 0.235 F 11597 (40.76) 7165 (40.50) 4432 (41.20) 8198 (41.89) 4140 (42.31) 4058 (41.47) M 16854 (59.24) 10528 (59.50) 6326 (58.80) 11372 (58.11) 5645 (57.69) 5727 (58.53) Race, n(%) <.001 0.029 OTHER 11970 (42.07) 7926 (44.80) 4044 (37.59) 7213 (36.86) 3533 (36.11) 3680 (37.61) WHITE 16481 (57.93) 9767 (55.20) 6714 (62.41) 12357 (63.14) 6252 (63.89) 6105 (62.39) Laboratory Index SOFA, M (Q₁, Q₃) 3.00 (1.00, 5.00) 3.00 (1.00, 5.00) 3.00 (1.00, 5.00) 0.574 3.00 (1.00, 5.00) 3.00 (1.00, 5.00) 3.00 (1.00, 5.00) 0.407 APS III, M (Q₁, Q₃) 37.00 (28.00, 46.00) 36.00 (28.00, 45.00) 38.00 (29.00, 47.00) <.001 38.00 (29.00, 46.00) 37.00 (29.00, 46.00) 38.00 (29.00, 47.00) 0.082 SAPS II, M (Q₁, Q₃) 32.00 (25.00, 40.00) 32.00 (25.00, 40.00) 32.00 (24.00, 40.00) 0.001 32.00 (24.00, 40.00) 32.00 (24.00, 40.00) 32.00 (24.00, 40.00) 0.057 OASIS, M (Q₁, Q₃) 28.00 (23.00, 33.00) 28.00 (23.00, 33.00) 28.00 (23.00, 33.00) 0.357 28.00 (23.00, 33.00) 28.00 (23.00, 33.00) 28.00 (23.00, 33.00) 0.169 GCS, M (Q₁, Q₃) 15.00 (14.00, 15.00) 15.00 (14.00, 15.00) 15.00 (14.00, 15.00) <.001 15.00 (14.00, 15.00) 15.00 (14.00, 15.00) 15.00 (14.00, 15.00) 0.007 Charlson, M (Q₁, Q₃) 5.00 (3.00, 7.00) 5.00 (3.00, 7.00) 5.00 (3.00, 8.00) 0.003 5.00 (3.00, 8.00) 5.00 (3.00, 8.00) 5.00 (3.00, 8.00) 0.067 APACHE II, M (Q₁, Q₃) 15.00 (11.00, 19.00) 15.00 (11.00, 19.00) 15.00 (11.00, 20.00) 0.391 15.00 (11.00, 19.00) 15.00 (11.00, 19.00) 15.00 (11.00, 19.00) 0.597 SIRS, n(%) <.001 0.122 0 205 (0.72) 147 (0.83) 58 (0.54) 114 (0.58) 60 (0.61) 54 (0.55) 1 3115 (10.95) 1955 (11.05) 1160 (10.78) 2176 (11.12) 1104 (11.28) 1072 (10.96) 2 9693 (34.07) 6158 (34.80) 3535 (32.86) 6642 (33.94) 3385 (34.59) 3257 (33.29) 3 12358 (43.44) 7631 (43.13) 4727 (43.94) 8458 (43.22) 4188 (42.80) 4270 (43.64) 4 3080 (10.83) 1802 (10.18) 1278 (11.88) 2180 (11.14) 1048 (10.71) 1132 (11.57) Comorbidities Hypertension,n(%) 1157 (4.07) 914 (5.17) 243 (2.26) <.001 523 (2.67) 283 (2.89) 240 (2.45) 0.057 Liver cirrhosis, n(%) 55 (0.19) 42 (0.24) 13 (0.12) 0.030 32 (0.16) 19 (0.19) 13 (0.13) 0.288 Hepatitis, n(%) 87 (0.31) 51 (0.29) 36 (0.33) 0.492 65 (0.33) 33 (0.34) 32 (0.33) 0.901 CVA, n(%) 181 (0.64) 144 (0.81) 37 (0.34) <.001 78 (0.40) 42 (0.43) 36 (0.37) 0.496 CKD, n(%) 269 (0.95) 211 (1.19) 58 (0.54) <.001 119 (0.61) 65 (0.66) 54 (0.55) 0.312 Cancer, n(%) 478 (1.68) 373 (2.11) 105 (0.98) <.001 221 (1.13) 117 (1.20) 104 (1.06) 0.379 T2DM, n(%) 580 (2.04) 463 (2.62) 117 (1.09) <.001 236 (1.21) 120 (1.23) 116 (1.19) 0.793 T1DM, n(%) 34 (0.12) 27 (0.15) 7 (0.07) 0.038 15 (0.08) 8 (0.08) 7 (0.07) 0.796 Obesity, n(%) 94 (0.33) 68 (0.38) 26 (0.24) 0.042 54 (0.28) 30 (0.31) 24 (0.25) 0.414 Sepsis, n(%) 246 (0.86) 133 (0.75) 113 (1.05) 0.008 201 (1.03) 101 (1.03) 100 (1.02) 0.943 CB, n(%) 211 (0.74) 154 (0.87) 57 (0.53) <.001 130 (0.66) 73 (0.75) 57 (0.58) 0.159 HF, n(%) 447 (1.57) 356 (2.01) 91 (0.85) <.001 192 (0.98) 104 (1.06) 88 (0.90) 0.246 MI, n(%) 165 (0.58) 149 (0.84) 16 (0.15) <.001 40 (0.20) 24 (0.25) 16 (0.16) 0.205 IHD, n(%) 882 (3.10) 786 (4.44) 96 (0.89) <.001 203 (1.04) 107 (1.09) 96 (0.98) 0.438 Medications Aspirin, n(%) <.001 0.074 0 20332 (71.46) 11866 (67.07) 8466 (78.69) 14984 (76.57) 7439 (76.02) 7545 (77.11) 1 8119 (28.54) 5827 (32.93) 2292 (21.31) 4586 (23.43) 2346 (23.98) 2240 (22.89) Antibiotics, n(%) <.001 0.397 0 5530 (19.44) 5134 (29.02) 396 (3.68) 769 (3.93) 373 (3.81) 396 (4.05) 1 22921 (80.56) 12559 (70.98) 10362 (96.32) 18801 (96.07) 9412 (96.19) 9389 (95.95) Lab variables RDW, M (Q₁, Q₃) 14.50 (13.40, 16.10) 14.30 (13.30, 15.80) 14.80 (13.60, 16.60) <.001 14.70 (13.50, 16.40) 14.60 (13.50, 16.30) 14.70 (13.60, 16.50) <.001 Red blood, M (Q₁, Q₃) 3.43 (2.93, 4.00) 3.41 (2.91, 3.95) 3.47 (2.95, 4.06) <.001 3.48 (2.96, 4.05) 3.48 (2.97, 4.04) 3.47 (2.95, 4.05) 0.451 Creatinine, M (Q₁, Q₃) 1.00 (0.70, 1.50) 1.00 (0.70, 1.40) 1.10 (0.80, 1.80) <.001 1.00 (0.80, 1.60) 1.00 (0.80, 1.50) 1.10 (0.80, 1.80) <.001 BUN, M (Q₁, Q₃) 20.00 (14.00, 33.00) 19.00 (13.00, 30.00) 22.00 (14.00, 38.00) <.001 21.00 (14.00, 35.00) 20.00 (14.00, 34.00) 22.00 (14.00, 37.00) <.001 Calcium, M (Q₁, Q₃) 8.20 (7.70, 8.70) 8.30 (7.80, 8.70) 8.20 (7.70, 8.70) <.001 8.20 (7.70, 8.70) 8.20 (7.70, 8.70) 8.20 (7.70, 8.70) <.001 Chloride, M (Q₁, Q₃) 105.00 (100.00, 108.00) 105.00 (101.00, 109.00) 104.00 (99.00, 108.00) <.001 104.00 (100.00, 108.00) 104.00 (100.00, 108.00) 104.00 (100.00, 108.00) <.001 Glucose, M (Q₁, Q₃) 127.00 (105.00, 162.00) 124.00 (104.00, 156.00) 131.00 (106.00, 172.00) <.001 129.00 (106.00, 168.00) 127.00 (105.00, 164.00) 131.00 (106.00, 171.00) <.001 Primary Outcomes AKI, n(%) <.001 <.001 0 10888 (38.27) 8391 (47.43) 2497 (23.21) 5732 (29.29) 3420 (34.95) 2312 (23.63) 1 17563 (61.73) 9302 (52.57) 8261 (76.79) 13838 (70.71) 6365 (65.05) 7473 (76.37) Aki Stage, n(%) <.001 <.001 1 4180 (23.80) 2770 (29.78) 1410 (17.07) 2948 (21.30) 1663 (26.13) 1285 (17.20) 2 7725 (43.98) 4443 (47.76) 3282 (39.73) 6002 (43.37) 2947 (46.30) 3055 (40.88) 3 5658 (32.22) 2089 (22.46) 3569 (43.20) 4888 (35.32) 1755 (27.57) 3133 (41.92) Hematotoxicity, n(%) <.001 <.001 0 15775 (55.45) 10931 (61.78) 4844 (45.03) 9563 (48.87) 5123 (52.36) 4440 (45.38) 1 12676 (44.55) 6762 (38.22) 5914 (54.97) 10007 (51.13) 4662 (47.64) 5345 (54.62) Hepatotoxicity, n(%) <.001 <.001 0 23905 (84.02) 15657 (88.49) 8248 (76.67) 15602 (79.72) 7977 (81.52) 7625 (77.93) 1 4546 (15.98) 2036 (11.51) 2510 (23.33) 3968 (20.28) 1808 (18.48) 2160 (22.07) Secondary outcomes Hosp Day, M (Q₁, Q₃) 8.78 (5.63, 16.65) 8.15 (5.38, 14.95) 9.73 (6.01, 20.14) <.001 9.11 (5.80, 17.94) 8.88 (5.63, 16.82) 9.67 (6.00, 19.17) <.001 Icu Day, M (Q₁, Q₃) 1.55 (1.00, 3.18) 1.46 (0.99, 2.88) 1.76 (1.04, 4.06) <.001 1.66 (1.01, 3.53) 1.62 (1.00, 3.23) 1.71 (1.02, 3.83) <.001 Z: Mann‒Whitney test, χ²: Chi‒square test M: Median, Q₁: 1st quartile, Q₃: 3rd quartile Body mass index (BMI), Sequential Organ Failure Assessment (SOFA), Acute Physiology Score III (APS III), Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), Glasgow Coma Scale (GCS), Acute Physiology and Chronic Health Evaluation II (APACHE II), Systemic Inflammatory Response Syndrome (SIRS), cerebrovascular accident (CVA), chronic kidney disease (CKD), type 1 and type 2 diabetes mellitus (T1DM, T2DM), cerebral bleeding (CB), heart failure (HF), myocardial infarction (MI), ischemiaemic heart disease (IHD), red cell distribution width (RDW), blood urea nitrogen (BUN), acute kidney injury (AKI), hospital length of stay (Hosp Day), and ICU length of stay (Icu Day) 3.2 Multivariable logistic and Cox regression analyses For the primary outcome, TDM of vancomycin demonstrated significant safety benefits after comprehensive adjustment for confounding factors (Table 2). While initial unadjusted analyses revealed greater risks of adverse events in the TDM group (AKI: OR=2.98, 95% CI=2.83--3.15; hematotoxicity: OR=1.97, 95% CI=1.88--2.07; hepatotoxicity: OR=2.34, 95% CI=2.19--2.50; all p<0.001), these associations substantially attenuated with progressive adjustment (Model 3: AKI OR=1.93, hematotoxicity: OR=1.55, hepatotoxicity: OR=1.25; all p<0.001). For the secondary outcome, the TDM group had a lower risk of in-hospital mortality (OR: 0.63, 95% CI: 0.54–0.74, p < 0.001) after full adjustment (Model 3). Similarly, ICU mortality was reduced in the TDM group (adjusted OR: 0.72, 95% CI: 0.62–0.85, p < 0.001). Table 2 . Multivariate-Adjusted Associations between Vancomycin Use and Clinical Outcomes Variables TDM Model1 Model2 Model3 Non use Use OR (95%CI) P OR (95%CI) P OR (95%CI) P Primary Outcomes AKI 9302 (52.57) 8261 (76.79) 2.98 (2.83 ~ 3.15) <.001 1.99 (1.87 ~ 2.12) <.001 1.93 (1.81 ~ 2.06) <.001 Hematotoxicity 6762 (38.22) 5914 (54.97) 1.97 (1.88 ~ 2.07) <.001 1.39 (1.32 ~ 1.47) <.001 1.55 (1.46 ~ 1.65) <.001 Hepatotoxicity 2036 (11.51) 2510 (23.33) 2.34 (2.19 ~ 2.50) <.001 1.49 (1.39 ~ 1.59) <.001 1.25 (1.16 ~ 1.34) <.001 Secondary outcomes In-Hospital Mortality 8.15 (5.38, 14.95) 9.73 (6.01, 20.14) 0.49 (0.42 ~ 0.57) <.001 0.58 (0.49 ~ 0.67) <.001 0.63 (0.54 ~ 0.74) <.001 In-ICU Mortality 1.46 (0.99, 2.88) 1.76 (1.04, 4.06) 0.51 (0.44 ~ 0.59) <.001 0.64 (0.55 ~ 0.75) <.001 0.72 (0.62 ~ 0.85) <.001 OR: Odds Ratio, CI: Confidence Interval Model1: Crude Model2: Adjust: race, Hypertension, Liver_cirrhosis, CVA, CKD, Cancer, T2DM, T1DM, Obesity, Sepsis, CB, HF, MI, IHD, Aspirin, Antibiotics Model3: Adjust: race, Hypertension, Liver_cirrhosis, Hepatitis, CVA, CKD, Cancer, T2DM, T1DM, Obesity, Sepsis, CB, HF, MI, IHD, SIRS, Aspirin, Antibiotics, age, BMI, SOFA, APS III, SAPS II, OASIS, GCS, Charlson, APACHE II, RDW, Red_blood, Creatinine, BUN, Calcium, Chloride, Glucose 3.3 Sensitivity analysis Logistic regression analysis after PSM demonstrated significant associations between vancomycin TDM and clinical outcomes (Figure 3). For primary safety outcomes, TDM was associated with reduced risks of AKI (OR 0.580, 95% CI 0.540–0.610; P=0.001), hematotoxicity (OR 0.760, 95% CI 0.710–0.800; P=0.001), and hepatotoxicity (OR 0.800, 95% CI 0.750–0.860; P=0.001). With respect to secondary outcomes, TDM had protective effects on in-hospital mortality (OR 0.672, 95% CI 0.570–0.790; P=0.001) and ICU mortality (OR 0.691, 95% CI 0.580–0.820; P=0.001). All associations were statistically significant, with P values of 0.001 and odds ratios consistently below 1.0, indicating beneficial effects of TDM across all measured outcomes. The narrow confidence intervals for each outcome suggest precise effect estimates, supporting the robustness of these findings. The consistency in direction and significance across both primary and secondary outcomes reinforces the clinical benefits associated with vancomycin TDM in this patient population. 3.4 Subgroup analysis Subgroup analyses identified several significant risk factors for adverse outcomes (Figure 4). For AKI, hypertension (OR=2.14, 95% CI=1.25–3.67, P=0.006), cancer (OR=2.64, 95% CI=1.04–6.66, P=0.040), CB (OR=4.96, 95% CI=1.39–17.72, P=0.014), aspirin use (OR=1.34, 95% CI=1.15–1.57, P=0.001), and antibiotic use (OR=1.70, 95% CI=1.59–1.81, P=0.001) were significantly associated with increased risk. For hematotoxicity, significant associations were observed with hypertension (OR=1.62, 95% CI=1.10–2.40, P=0.015), hepatitis (OR=20.47, 95% CI=3.04–138.05, P=0.002), aspirin use (OR=1.36, 95% CI=1.20–1.54, P=0.001), and antibiotic use (OR=1.23, 95% CI=1.16–1.31, P=0.001). Notably, T2DM was significantly associated with hematotoxicity outcomes (OR=1.16, 95% CI=1.08--1.25, P=0.001), whereas aspirin (OR=1.82, 95% CI=1.52--2.18, P=0.001) and antibiotics (OR=1.14, 95% CI=1.05--1.22, P=0.001) remained significant across all analyses. Several variables, including liver cirrhosis, CVA, T1DM, and obesity, presented extreme OR values with wide confidence intervals, likely due to small sample sizes, resulting in nonsignificant P values. The consistency of antibiotic and aspirin associations across multiple outcomes suggests their important role in adverse event risk. 3.5 Kaplan‒Meier analysis The Kaplan‒Meier survival analyses after propensity score matching demonstrated significant survival benefits associated with vancomycin TDM (Figure 5). For ICU survival, the TDM group had significantly better outcomes than did the non-TDM group (HR 0.691, 95% CI 0.585--0.816, log-rank P < 0.001), with consistently greater numbers at risk throughout the follow-up period (TDM vs non-TDM: 9785 vs 9785 at baseline; 1738 vs 1423 at later time points). Similarly, for in-hospital survival, the TDM group exhibited a significantly reduced mortality risk (HR 0.672, 95% CI 0.569–0.794, log-rank P < 0.001), with maintained numerical advantages in patients at risk across all observed time intervals (TDM vs non-TDM: 9774 vs 9778 at baseline; 4673 vs 4246 at subsequent assessments). These robust findings, as evidenced by highly significant P values and hazard ratios below 1.0 with narrow confidence intervals, consistently support the survival benefit of vancomycin TDM in both ICU and hospital settings. The larger number of patients remaining at risk in the TDM groups at each follow-up point further reinforces these survival advantages. 4 Discussion The results of this study suggest that although initial multimodel controlled logistic regression analyses revealed that the TDM group did not demonstrate a significant safety advantage (OR>1), this finding should be interpreted carefully in the context of baseline characteristics. Notably, baseline analyses revealed that patients in the TDM group had higher disease severity scores and worse clinical statuses. This group imbalance may have obscured the true effect of TDM. As more covariates were progressively controlled in the models, the ORs exhibited a decreasing trend, indicating that the initial negative results were likely driven by baseline disparities between the groups. This inference was further supported by PSM; after baseline characteristics were balanced, the TDM group showed significant improvement (OR<1) in all three safety outcomes — AKI, hematotoxicity, and hepatotoxicity. Together, these findings suggest that vancomycin TDM indeed enhances therapeutic safety, and the earlier unfavorable results likely reflect the clinical reality that TDM is preferentially used in patients with more severe conditions. Consequently, this study provides compelling evidence to support the routine implementation of vancomycin TDM in ICU patients, particularly critically ill individuals, where safety benefits are more pronounced. The findings also diverge somewhat from the existing literature. For example, Yang et al.[21] reported no statistically significant association between vancomycin TDM and a reduced incidence of nephrotoxicity, whereas our study revealed that TDM significantly decreases the risk of nephrotoxicity in ICU patients. This discrepancy may be attributed to several factors: although Yang’s study included 971 treatment sessions, the intervention group comprised only 207 cases, and the follow-up period was short (one year), potentially limiting statistical validity. Additionally, as a single-center retrospective study, it may have suffered from selection bias and inadequate control of ICU-specific confounders such as SOFA scores and vasoactive medication use. Notably, multiple studies support our findings; for example, a systematic review and meta-analysis [22] confirmed that TDM significantly reduces nephrotoxicity risk (HR=0.25, 95% CI=0.13–0.48; p<0.0001). Several researchers have also demonstrated that vancomycin therapeutic drug monitoring is associated with shorter treatment durations and lower total doses [2][23][24][25]. Regarding mortality outcomes, evidence from the MIMIC-IV database corroborates our finding that TDM is linked to reduced mortality, despite differences in database versions (3.1 vs. 2.1) [26]. The strengths of this study include the use of multicenter, large-sample ICU data from the MIMIC-IV, rigorous propensity score matching, multiple regression analyses, and sensitivity tests that validate the robustness of our results. These methodological strengths provide a greater level of evidence supporting the nephroprotective role of TDM in critically ill patients. In this study, we systematically analyzed the risk factors associated with vancomycin-related toxicity. We found that hypertension, malignancy, CB, aspirin use, and antibiotic coadministration were significantly linked to an increased risk of nephrotoxicity. Conversely, hypertension, hepatitis, aspirin, and antibiotic use were significantly associated with hematologic toxicity. Notably, type 2 diabetes was specifically associated with hepatotoxicity, and the combination of aspirin with antibiotics consistently demonstrated significant correlations across all toxicity analyses. Previous studies have identified key risk factors for vancomycin-associated nephrotoxicity, including the concurrent use of nephrotoxic drugs (e.g., aminoglycosides, amphotericin B) [27][28][29], prolongation of treatment duration [27][30], and the use of vasoactive medications [30]. Vancomycin exhibits considerable interindividual variability in pharmacokinetics among adults [31], a variation that is particularly pronounced in critically ill populations such as patients with severe sepsis, those undergoing continuous veno-venous hemodialysis, patients with malignancies, neonates, and severe burn victims [10][14][32][33][34][35][36][37][38]. Moreover, predicting blood levels in specific high-risk groups—such as patients with heart failure [39], obesity [40], or renal insufficiency[27][30][41]—is challenging, underscoring the importance of TDM in these populations. Some studies [42] have also suggested that TDM provides limited clinical benefit in patients with normal renal function. Our findings confirm known risk factors and, importantly, for the first time, systematically reveal a potential synergistic effect of aspirin across multiple forms of vancomycin toxicity. This novel insight may inform more rational and evidence-based clinical use of vancomycin. Although the present study was limited by the use of the MIMIC-IV database, which precluded the collection of data on ototoxicity and Red Man syndrome, the literature offers valuable insights into these adverse reactions. Research indicates that Red Man syndrome is primarily mediated by histamine release and manifests clinically as flushing and tingling sensations in the face, neck, and upper body [8]. Its occurrence is closely related to the infusion rate, with a significantly increased risk when doses exceeding 500 mg are infused rapidly over 30 minutes [11][17][43]. Consequently, clinical guidelines recommend controlling the infusion time for 1 g doses to at least 1 hour [44] and for higher doses (e.g., 2 g) to extend to 1.5–2 hours [45]. These standardized practices effectively prevent the syndrome. With respect to ototoxicity, available studies depict a more complex picture. Early reports by Bailie et al. [46], covering studies from 1956--1986, linked ototoxicity mainly to vancomycin preparations with high impurity levels. Notably, several studies have failed to establish a clear association between vancomycin blood levels and ototoxicity [2][44], and the incidence of ototoxicity when vancomycin is used alone appears to be very low [2]. Age has emerged as a significant risk factor [47], with a retrospective study demonstrating a higher incidence in patients aged ≥53 years than in younger patients (p=0.008) [48]. Additionally, coadministration of other ototoxic agents (e.g., aminoglycosides and certain diuretics) may result in synergistic toxicity. On the basis of current evidence, heightened vigilance remains necessary for high-risk groups, such as elderly individuals, individuals with pre-existing hearing loss, and those receiving multiple ototoxic medications [49]. These findings increase our understanding of the adverse effects of vancomycin. Although this study’s database limitations prevented direct analysis of these outcomes, existing evidence suggests that these drug-related risks can be effectively managed through infusion standardization and identification of at-risk populations. Although vancomycin dose and trough concentration data were not directly analyzed in this study, the available evidence indicates that these parameters are strongly associated with safety. The literature consistently demonstrates that elevated serum trough concentrations and prolonged vancomycin treatment duration increase the risk of nephrotoxicity [50]. Older age, longer treatment courses, and lower serum vancomycin concentrations (30–65 mg/L) are significant risk factors for vancomycin-induced nephrotoxicity [51]. Notably, treatment durations exceeding one week can increase nephrotoxicity risk from 6% to 30% [52], and concomitant use of nephrotoxic agents (e.g., aminoglycosides) can increase the incidence from 5–7% to as high as 22% with monotherapy [2][11][28]. The pharmacokinetic properties of vancomycin, which accounts for approximately 80–90% of vancomycin renally excreted [20], underscore the importance of precise dose adjustment in patients with renal impairment [53]. Multiple studies have shown that higher doses significantly increase nephrotoxicity risk, with rates reaching 12–42.7% [10][11][27][54][55]. While clinical guidelines for MRSA infection management [56] and the vancomycin TDM consensus [2] recommend maintaining trough levels between 15–20 μg/mL and Australian guidelines suggest 12–18 μg/mL [57] (to ensure an AUC/MIC ≥400 [2] ) , recent research indicates that these ranges may heighten the risk of acute kidney injury [58][59]. In high-risk populations, such as pediatric, renal failure, or critically ill patients [20][60][61][62], individualized dosing via TDM is essential because of significant pharmacokinetic variability [63]. With respect to administration mode, studies comparing continuous versus intermittent infusion have yielded mixed results. Although some reports suggest potential advantages of continuous infusion, there is no conclusive evidence that it is superior in terms of clinical outcomes [64][65][66]. Consequently, current guidelines continue to endorse intermittent infusion as the standard. These findings underscore the critical role of TDM in balancing efficacy and safety, particularly in high-risk groups. This study has several methodological limitations that warrant clarification. First, although we used AKI based on the KDIGO criteria as a surrogate for nephrotoxicity — which is consistent with most literature [2][67] — this may introduce bias in assessing drug-related nephrotoxicity in clinical practice [68]. Second, owing to database constraints, we could not differentiate between types of TDM modalities (e.g., AUC monitoring versus trough concentration monitoring alone) or access specific TDM protocols (e.g., sampling times, dose adjustment criteria) at individual centers, potentially affecting result interpretation. Third, despite the use of multivariate adjustment and propensity score matching (with a caliper of 0.1), residual confounding may persist in this retrospective design. Additionally, the database included only hospitalization data, preventing the assessment of delayed adverse events such as permanent hearing impairment that may manifest postdischarge. Finally, this study did not evaluate the economic aspects of TDM implementation; however, existing evidence suggests [17][38] that TDM can be cost-effective — particularly in critically ill, oncologic, or patients receiving conephrotoxic agents — a crucial consideration for future research and clinical decision-making. 5 conclusion This study confirms that implementing vancomycin TDM in ICU patients significantly enhances medication safety. Cohort analysis demonstrated that TDM is associated with a substantial reduction in vancomycin-related nephrotoxicity, hematotoxicity, and hepatotoxicity, as well as a notable decrease in ICU and in-hospital mortality. Importantly, TDM also benefits high-risk patients, including those with hypertension or those receiving nephrotoxic comedications. These findings underscore the importance of routine vancomycin TDM in critically ill populations. Abbreviations Abbreviation Full Term AKI Acute kidney injury APS III Acute Physiology Score III APACHE II Acute Physiology and Chronic Health Evaluation II ASHP American Society of Health-System Pharmacists BMI Body mass index BUN Blood urea nitrogen CB Cerebral bleeding CI Confidence interval CKD Chronic kidney disease Cr Serum creatinine CVA Cerebrovascular accident GCS Glasgow Coma Scale HF Heart failure Hosp Day Hospital length of stay Icu Day ICU length of stay ICD Ischemic heart disease ICU Intensive care unit IDSA Infectious Diseases Society of America IQR Interquartile range MIMIC-IV Medical Information Mart for Intensive Care IV MI Myocardial infarction MRSA Methicillin-resistant Staphylococcus aureus OASIS Oxford Acute Severity of Illness Score OR Odds ratio PSM Propensity score matching RDW Red cell distribution width SAPS II Simplified Acute Physiology Score II SIRS Systemic Inflammatory Response Syndrome SOFA Sequential Organ Failure Assessment SQL Structured Query Language T1DM Type 1 diabetes mellitus T2DM Type 2 diabetes mellitus TDM Therapeutic drug monitoring Declarations Data declarations The research involving human participants was approved, and the need for further ethical approval was waived by the Clinical Research Ethics Committee of the First Affiliated Hospital of Shantou University Medical College, Shantou. This exemption was granted because ethical approval for the MIMIC-IV database had already been obtained from the institutional review boards (IRBs) of Beth Israel Deaconess Medical Center and the Massachusetts Institute of Technology. The study complied with local regulations and institutional standards. Furthermore, written informed consent from participants or their legal guardians / next of kin was waived by the ethics committee / institutional review board, as the research followed applicable legal and institutional policies, and the database contains no protected health information. Consent for publication All authors have read and approved the final manuscript and consent to its publication in this journal. Availability of data and materials The MIMIC-IV database used in this study is publicly available to researchers who meet the criteria for access. Detailed instructions for obtaining the data can be found at https://mimic-iv.mit.edu/. Competing Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 81801189) and the “Ying Cai Tuo Ju” Program at the First Affiliated Hospital of Shantou University Medical College (Grant No. YCTJ-2022-03). Authors' contributions This short text acknowledges the contributions of specific colleagues, institutions, or agencies that aided the efforts of the authors. All the authors contributed to the study conception and design. Project design, patient information verification, and data cleaning, W.J.; paper writing and data checking, W.Z.M.; data inclusion and cleaning, H.C.Z.; data organization and statistical analysis, C.Y.; and data statistics, H.Y.L. All the authors have read and agreed to the published version of the manuscript. 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Antimicrob Agents Chemother. 2009;53:483–6. Humphrey C, Veve MP, Walker B, Shorman MA. Long-term vancomycin use had low risk of ototoxicity. PLoS One. 2019 Nov 6;14(11):e0224561. doi: 10.1371/journal.pone.0224561. PMID: 31693679; PMCID: PMC6834250. Bruniera FR, Ferreira FM, Saviolli LR, Bacci MR, Feder D, da Luz Gonçalves Pedreira M, Sorgini Peterlini MA, Azzalis LA, Campos Junqueira VB, Fonseca FL. The use of vancomycin with its therapeutic and adverse effects: a review. Eur Rev Med Pharmacol Sci. 2015 Feb;19(4):694-700. PMID: 25753888. Pritchard L, Baker C, Leggett J, Sehdev P, Brown A, Bayley KB. Increasing vancomycin serum trough concentrations and incidence of nephrotoxicity. Am J Med. 2010 Dec;123(12):1143-9. doi: 10.1016/j.amjmed.2010.07.025. PMID: 21183005. Farber BF, Moellering RC Jr. Retrospective study of the toxicity of preparations of vancomycin from 1974 to 1981. Antimicrob Agents Chemother. 1983 Jan;23(1):138-41. doi: 10.1128/AAC.23.1.138. PMID: 6219616; PMCID: PMC184631. Bosso JA, Nappi J, Rudisill C, Wellein M, Bookstaver PB, Swindler J, Mauldin PD. Relationship between vancomycin trough concentrations and nephrotoxicity: a prospective multicenter trial. Antimicrob Agents Chemother. 2011 Dec;55(12):5475-9. doi: 10.1128/AAC.00168-11. Epub 2011 Sep 26. PMID: 21947388; PMCID: PMC3232787. Rybak MJ. The pharmacokinetic and pharmacodynamic properties of vancomycin. Clin Infect Dis. 2006 Jan 1;42 Suppl 1:S35-9. doi: 10.1086/491712. PMID: 16323118. Moise-Broder PA, Forrest A, Birmingham MC, Schentag JJ. Pharmacodynamics of vancomycin and other antimicrobials in patients with Staphylococcus aureus lower respiratory tract infections. Clin Pharmacokinet. 2004;43:925–42 Kullar R, Davis SL, Levine DP, Rybak MJ. Impact of vanco mycin exposure on outcomes in patients with methicillin-resis tant Staphylococcus aureus bacteremia: support for consensus guidelines suggested targets. Clin Infect Dis. 2011;52:975–81. 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Balancing vancomycin efficacy and nephrotoxicity: should we be aiming for trough or AUC/MIC? Paediatr Drugs. 2015 Apr;17(2):97-103. doi: 10.1007/s40272-015-0117-5. PMID: 25644329. Frymoyer A, Hersh AL, El-Komy MH, Gaskari S, Su F, Drover DR, Van Meurs K. Association between vancomycin trough concentration and area under the concentration-time curve in neonates. Antimicrob Agents Chemother. 2014 Nov;58(11):6454-61. doi: 10.1128/AAC.03620-14. Epub 2014 Aug 18. PMID: 25136027; PMCID: PMC4249374. McKamy S, Hernandez E, Jahng M, Moriwaki T, Deveikis A, Le J. Incidence and risk factors influencing the development of vancomycin nephrotoxicity in children. J Pediatr. 2011 Mar;158(3):422-6. doi: 10.1016/j.jpeds.2010.08.019. PMID: 20888013. Launay-Vacher V, Izzedine H, Mercadal L, Deray G. Clinical review: use of vancomycin in haemodialysis patients. Crit Care. 2002 Aug;6(4):313-6. doi: 10.1186/cc1516. Epub 2002 Jun 10. PMID: 12225605; PMCID: PMC137311. Kang, J. S., & Lee, M. H. (2009). Overview of therapeutic drug monitoring. The Korean journal of internal medicine, 24(1), 1. Ingram PR, Lye DC, Fisher DA, Goh WP, Tam VH. Nephro toxicity of continuous versus intermittent infusion of vanco mycin in outpatient parenteral antimicrobial therapy. Int J Antimicrob Agents. 2009;34:570–4. Hutschala D, Kinstner C, Skhirdladze K, Thalhammer F, Mu¨ller M, Tschernko E. Influence of vancomycin on renal function in critically ill patients after cardiac surgery: continuous versus intermittent infusion. Anesthesiology. 2009;111:356–65 Cataldo MA, Tacconelli E, Grilli E, Pea F, Petrosillo N. Con tinuous versus intermittent infusion of vancomycin for the treatment of gram-positive infections: systematic review and meta-analysis. J Antimicrob Chemother. 2012;67:17–24. Wunderink RG, Niederman MS, Kollef MH, Shorr AF, Kunkel MJ, Baruch A, McGee WT, Reisman A, Chastre J. Linezolid in methicillin-resistant Staphylococcus aureus nosocomial pneumonia: a randomized, controlled study. Clin Infect Dis. 2012 Mar 1;54(5):621-9. doi: 10.1093/cid/cir895. Epub 2012 Jan 12. PMID: 22247123. Filippone, E. J., Kraft, W. K., & Farber, J. L. (2017). The nephrotoxicity of vancomycin. Clinical Pharmacology & Therapeutics, 102(3), 459-469. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":91766,"visible":true,"origin":"","legend":"\u003cp\u003ePatient inclusion flow chart.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7437818/v1/d76ba24ce8866bf748e5ae3a.png"},{"id":94046719,"identity":"a5cc8449-c3df-43fc-b7c6-e099b27f0959","added_by":"auto","created_at":"2025-10-21 23:08:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":272205,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLove plot of standardized mean differences for covariate balance\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7437818/v1/49443fb2a1db940a67032e2e.png"},{"id":94046725,"identity":"f4b48164-76e8-40c4-9225-6746332f65d3","added_by":"auto","created_at":"2025-10-21 23:08:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":99287,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot: TDM-associated outcomes after PSM analysis\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7437818/v1/5830e7e5b3103900364c7df3.png"},{"id":94047631,"identity":"96a3d465-6a8c-488b-b505-45a1283bcbcc","added_by":"auto","created_at":"2025-10-21 23:16:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":269907,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot: Subgroup analysis of the effects of TDM on vancomycin-associated AKI, cardiotoxicity and hepatotoxicity in ICU patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7437818/v1/ee7de79bfd6ccd413941b5b5.png"},{"id":94046724,"identity":"3925d465-72c4-4637-8631-479069f11451","added_by":"auto","created_at":"2025-10-21 23:08:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":141647,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAfter PSM survival analysis (left: ICU mortality; right: in-hospital mortality\u003c/strong\u003e)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7437818/v1/61d72aa819f6f81d0fcec3e3.png"},{"id":104739446,"identity":"4361e0e0-a986-47ed-a96f-0555e740bfe8","added_by":"auto","created_at":"2026-03-16 16:07:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1875969,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7437818/v1/b5dd3cbd-4120-4d6a-ba9a-46aec07cd8ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Vancomycin Therapeutic Drug Monitoring Reduces Toxicity in ICU Patients: A MIMIC-IV Retrospective Study","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eVancomycin is the first-line antibiotic for treating methicillin-resistant Staphylococcus aureus (MRSA) infections and is also employed in the management of other severe gram-positive bacterial infections[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As one of the most widely used antibiotics in the United States, vancomycin has been in clinical use for nearly 50 years [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nonetheless, its application has long been complicated by a narrow therapeutic window and the risk of toxicity. Research has indicated that \u003cem\u003eS. aureus\u003c/em\u003e infections, particularly MRSA infections, significantly increase patient morbidity, mortality, and healthcare burdens [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Moreover, vancomycin therapy can cause various adverse reactions, including red man syndrome [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], nephrotoxicity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and ototoxicity [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The incidence of acute kidney injury (AKI) associated with vancomycin ranges from 5\u0026ndash;43% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], with a 2.45-fold higher risk of nephrotoxicity than that associated with non-glycopeptide antibiotics [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Importantly, this increased risk exists independently of other confounding factors. There is substantial evidence linking vancomycin to nephrotoxicity, demonstrating this association even when vancomycin is not explicitly classified as nephrotoxic in guidelines [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo optimize therapeutic efficacy while minimizing toxicity, therapeutic drug monitoring (TDM) of vancomycin is currently recommended by organizations such as the American Society of Health-System Pharmacists (ASHP), the Infectious Diseases Society of America (IDSA), and the Japanese Society of Chemotherapy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the evidence supporting these recommendations remains contentious. On the one hand, the TDM criteria in these guidelines are primarily based on pharmacodynamic targets, such as the area under the concentration‒time curve to minimum inhibitory concentration ratio (AUC/MIC), which may not be fully applicable to patients in ICU, whose pathophysiological states can significantly vary. On the other hand, several studies have reported that TDM implementation has not markedly improved clinical outcomes or decreased the incidence of nephrotoxicity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Moreover, some research indicates that the cost-effectiveness of TDM may be limited to specific high-risk populations, including ICU patients, those receiving concomitant nephrotoxic drugs, or oncology patients [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This ongoing debate highlights a critical issue: without high-quality evidence, the clinical value of vancomycin TDM remains to be conclusively established.\u003c/p\u003e\u003cp\u003eCurrent research on vancomycin TDM has notable limitations. Most studies have focused primarily on nephrotoxicity and have often neglected other critical adverse effects, such as hepatotoxicity and hematologic toxicity. Additionally, there is a paucity of research specifically targeting ICU populations, with existing studies confounded by factors such as concomitant nephrotoxic drugs, hemodynamic fluctuations, and underlying diseases. To address these gaps, the present study utilized the MIMIC-IV database\u0026mdash;a comprehensive, real-world dataset\u0026mdash;to systematically evaluate the impact of vancomycin TDM on multiorgan toxicity, including nephrotoxicity, hepatotoxicity, and hematotoxicity. Employing a rigorous methodological approach\u0026mdash;including a large sample size (n\u0026thinsp;=\u0026thinsp;28,451), propensity score matching (PSM), and multiple sensitivity analyses\u0026mdash;this study aims to provide a more reliable and high-quality evidence base to inform clinical practice. Ultimately, we hope these findings will facilitate more precise individualized dosing strategies for vancomycin therapy in ICU patients.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cp\u003e2.1 Sources of Data\u003c/p\u003e\n\u003cp\u003eThis retrospective study utilized health-related data obtained from the MIMIC-IV (version 3.1) database, a comprehensive and extensive resource developed and managed by the MIT Computational Physiology Laboratory. This database comprises high-quality medical MIMIC-IV contains de-identified clinical data corresponding to all medical record numbers of patients admitted to the ICU or emergency department between 2008 and 2022 records of patients admitted to the intensive care units of the Beth Israel Deaconess Medical Center. MIMIC-IV contains de-identified clinical data corresponding to all medical record numbers of patients admitted to the ICU or emergency department between 2008 and 2022 [18]. Jia Wang, one of the authors, collected clinical data from the MIMIC database (certification number: 42257067), including patient demographic information, laboratory findings, and medication usage. This project adhered to the principles of the Helsinki Declaration, and approval from the ethics committee was not required because of participant anonymity and data standardization within the database.\u003c/p\u003e\n\u003cp\u003e2.2 Study population\u003c/p\u003e\n\u003cp\u003eAll adult patients (\u0026ge;18 years) admitted to the ICU recorded in the MIMIC-IV database were screened for this study. We included patients who were administered vancomycin intravenously after ICU admission. Vancomycin TDM was defined as at least one measurement of the blood vancomycin concentration in laboratory indices at MIMIC-IV during ICU hospitalization. We categorized patients who were or were not treated with vancomycin TDM into a vancomycin group (TDM group) and a control group (non-TDM group). For patients with multiple ICU admissions, only data from their first ICU stay were analyzed. The patient enrollment process for this study is depicted in \u003cstrong\u003eFigure 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2.3 Data collection and definitions\u003c/p\u003e\n\u003cp\u003eStructured Query Language (SQL) was employed to extract data via Navicat Premium software (version 15) on the basis of unique patient identifiers (e.g., stay_id). We collected demographic information, including\u0026nbsp;age,\u0026nbsp;sex,\u0026nbsp;BMI, and\u0026nbsp;race. Disease severity and laboratory indices were assessed via the\u0026nbsp;SOFA score,\u0026nbsp;APS III score,\u0026nbsp;SAPS II score,\u0026nbsp;OASIS score,\u0026nbsp;GCS score,\u0026nbsp;Charlson comorbidity index, and\u0026nbsp;APACHE II score\u0026nbsp;within the first 24 hours of ICU admission. The\u0026nbsp;SIRS\u0026nbsp;criteria were also evaluated. Comorbidities were identified using ICD-9/10 codes, including\u0026nbsp;hypertension,\u0026nbsp;liver cirrhosis,\u0026nbsp;hepatitis,\u0026nbsp;CVA,\u0026nbsp;CKD,\u0026nbsp;cancer,\u0026nbsp;T1DM and T2DM,\u0026nbsp;obesity,\u0026nbsp;sepsis,\u0026nbsp;CB,\u0026nbsp;HF,\u0026nbsp;MI, and\u0026nbsp;IHD, were identified via ICD-9/10 codes. The use of medications, including\u0026nbsp;aspirin\u0026nbsp;and\u0026nbsp;antibiotics, was documented. The laboratory variables collected included\u0026nbsp;RDW,\u0026nbsp;red blood cell count,\u0026nbsp;creatinine,\u0026nbsp;BUN,\u0026nbsp;calcium,\u0026nbsp;chloride, and\u0026nbsp;glucose. The primary outcomes included AKI,\u0026nbsp;hematotoxicity, and\u0026nbsp;hepatotoxicity. The secondary outcomes included\u0026nbsp;Hosp Day and Icu Day.\u003c/p\u003e\n\u003cp\u003eIn this study, nephrotoxicity was defined according to the AKI criteria [19], with patients considered positive if they exhibited either an absolute serum creatinine (Cr) increase \u0026ge;0.3 mg/dL or a \u0026ge;50% Cr elevation from baseline (highest value within 3 days prevancomycin) during treatment [13][20], confirmed by two consecutive measurements. Hematotoxicity was identified by laboratory abnormalities: thrombocytopenia (platelet count \u0026lt;100\u0026times;10^9/L), leukopenia (white blood cell count \u0026lt;4\u0026times;10^9/L), neutropenia (absolute neutrophil count \u0026lt;1.5\u0026times;10^9/L), or anemia (hemoglobin \u0026lt;10 g/dL). Hepatotoxicity required elevations in alanine aminotransferase (ALT \u0026ge;120 U/L), aspartate aminotransferase (AST \u0026ge;120 U/L), or total bilirubin (\u0026ge;2.5 mg/dL). All laboratory values were assessed via baseline measurements taken within 24 hours of ICU admission or pretreatment. Patients meeting \u0026ge;1 criterion for any toxicity were classified as affected, ensuring standardized and clinically meaningful assessment.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.4 Outcomes\u003c/p\u003e\n\u003cp\u003eThis study aimed to investigate the impact of TDM on medication safety during vancomycin administration in ICU patients. The primary safety endpoints studied include nephrotoxicity, hematotoxicity, and hepatotoxicity. Secondary outcomes focus on the associations between TDM and in-hospital mortality and ICU mortality. In addition, the study will assess the impact of different comorbidities (e.g., hypertension,\u0026nbsp;liver cirrhosis,\u0026nbsp;hepatitis, etc.). on the effect of TDM through subgroup analyses, with a special focus on whether concomitant use of nephrotoxic medications (e.g., aspirin, antibiotics) affects the safety profile of vancomycin.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.5 Statistical analysis\u003c/p\u003e\n\u003cp\u003eIn this study, continuous variables did not follow a normal distribution and are therefore presented as medians with interquartile ranges (IQRs). Categorical variables are expressed as frequencies and percentages. The baseline characteristics of statin-treated and untreated patients were compared via the Mann‒Whitney test for continuous variables and the chi‒square test for categorical variables. Variables with less than 20% missing data were retained. All missing values were addressed via multiple imputation methods in SPSS version 27.\u003c/p\u003e\n\u003cp\u003eMultivariable logistic regression models were constructed to adjust for potential confounders in assessing the associations between TDM use and outcomes. Cox proportional hazards models were employed to estimate the associations of TDM use with survival rates in both hospital and ICU settings. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for all the models. Model 1 (Crude): Unadjusted analysis. Model 2: Adjusted for race, hypertension, liver cirrhosis, CVA, CKD, cancer, T2DM, T1DM, obesity, sepsis, CB, HF, MI, IHD, aspirin, and antibiotics. Model 3 (Fully Adjusted): Further adjusted for hepatitis, SIRS, age, BMI, SOFA score, APS III, SAPS II, OASIS, GCS, Charlson comorbidity index, APACHE II score, RDW, red blood cell count, creatinine, BUN, calcium, chloride, and glucose. For survival outcomes (in-hospital and in-ICU mortality), HRs and 95% CIs were derived from Cox models via the same adjustment hierarchy.\u003c/p\u003e\n\u003cp\u003eTo control for potential confounders, PSM was performed in this study via a 1:1 nearest-neighbor matching method with a caliper value set at 0.1. The matched variables included all the baseline variables except the outcome indicators (AKI, hematotoxicity, and hepatotoxicity). The balance of covariates after matching was assessed by the standardized mean difference (SMD). In the matched cohort, the associations of TDM with the primary safety outcomes (AKI, hematotoxicity, and hepatotoxicity) were assessed via logistic regression analysis. Moreover, the Cox proportional risk model was used to analyze the association of TDM with secondary outcomes (hospital mortality and ICU mortality).\u003c/p\u003e\n\u003cp\u003eSubgroup analyses were performed to assess potential effect modifications by clinically relevant factors, including comorbidities (e.g.,\u0026nbsp;hypertension,\u0026nbsp;liver cirrhosis,\u0026nbsp;hepatitis,\u0026nbsp;CVA,\u0026nbsp;CKD,\u0026nbsp;cancer,\u0026nbsp;T1DM and T2DM,\u0026nbsp;obesity,\u0026nbsp;sepsis,\u0026nbsp;CB,\u0026nbsp;HF,\u0026nbsp;MI, and\u0026nbsp;IHD), and concomitant medications (e.g., aspirin, antibiotics).\u003c/p\u003e\n\u003cp\u003eAll the statistical analyses were performed via R version 4.4.1 and SPSS version 27. A two-sided P value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e3.1 Patient characteristics\u003c/p\u003e\n\u003cp\u003eA total of\u0026nbsp;28,451 ICU patients\u0026nbsp;receiving intravenous vancomycin were included in this study from the MIMIC-IV database (\u003cstrong\u003eTable 1\u003c/strong\u003e), with\u0026nbsp;10,758 (37.8%)\u0026nbsp;undergoing TDM and\u0026nbsp;17,693 (62.2%)\u0026nbsp;not receiving TDM. Before PSM, the TDM group was significantly older (median age 68 vs. 66 years,\u0026nbsp;p\u0026nbsp;\u0026lt; 0.001) and had higher illness severity scores (SOFA\u0026nbsp;score: 3 vs. 3,\u0026nbsp;p\u0026nbsp;\u0026lt; 0.001; APS III\u0026nbsp;score: 38 vs. 36,\u0026nbsp;p\u0026nbsp;\u0026lt; 0.001). Comorbidities such as hypertension (97.74% vs. 94.83%,\u0026nbsp;p\u0026nbsp;\u0026lt; 0.001), liver cirrhosis (0.12% vs. 0.24%,\u0026nbsp;p\u0026nbsp;= 0.003), and sepsis (1.05% vs. 0.75%,\u0026nbsp;p\u0026nbsp;\u0026lt; 0.001) were more prevalent in the TDM group.\u003c/p\u003e\n\u003cp\u003eAfter PSM (9,785 patients per group), all baseline characteristics were well balanced (SMD \u0026lt; 0.10) (\u003cstrong\u003eFigure 2\u003c/strong\u003e). The TDM group had a lower incidence of AKI (23.21% vs. 34.95%, p \u0026lt; 0.001), with reduced AKI severity (stage 3: 43.20% vs. 27.57%, p \u0026lt; 0.001). Hematotoxicity was less common in the TDM group (45.03% vs. 52.36%, p \u0026lt; 0.001), whereas hepatotoxicity was more common (23.33% vs. 18.48%, p \u0026lt; 0.001). The hospital length of stay was longer in the TDM group (median 9.73 vs. 8.88 days, p \u0026lt; 0.001), as was the ICU stay (1.76 vs. 1.62 days, p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Baseline characteristics of patients before and after propensity score matching\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"96%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 19px;\"\u003eVariables\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 39px;\"\u003eBefore PSM\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 40px;\"\u003eAfter PSM\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003eTotal (n = 28451)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003eNon TDM (n = 17693)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003eTDM (n = 10758)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u003cem\u003eP\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003eTotal (n = 19570)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003eNon TDM (n = 9785)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003eTDM (n = 9785)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u003cem\u003eP\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003ePatient characteristics\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAge, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e68.00 (57.00, 79.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e69.00 (59.00, 79.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e66.00 (55.00, 77.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e67.00 (56.00, 78.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e68.00 (57.00, 79.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e67.00 (55.00, 78.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eBMI, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e27.76 (24.06, 32.32)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e27.68 (24.06, 32.01)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e27.96 (24.02, 32.91)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e27.73 (23.95, 32.43)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e27.65 (23.92, 32.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e27.85 (23.98, 32.72)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.002\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eGender, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.243\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.235\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; F\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e11597 (40.76)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e7165 (40.50)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4432 (41.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8198 (41.89)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e4140 (42.31)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4058 (41.47)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; M\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e16854 (59.24)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e10528 (59.50)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e6326 (58.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e11372 (58.11)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e5645 (57.69)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5727 (58.53)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eRace, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.029\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; OTHER\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e11970 (42.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e7926 (44.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4044 (37.59)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7213 (36.86)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3533 (36.11)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3680 (37.61)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; WHITE\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e16481 (57.93)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e9767 (55.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e6714 (62.41)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e12357 (63.14)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e6252 (63.89)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e6105 (62.39)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eLaboratory Index\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eSOFA, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.00 (1.00, 5.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3.00 (1.00, 5.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.00 (1.00, 5.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.574\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.00 (1.00, 5.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3.00 (1.00, 5.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.00 (1.00, 5.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.407\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAPS III, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e37.00 (28.00, 46.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e36.00 (28.00, 45.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e38.00 (29.00, 47.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e38.00 (29.00, 46.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e37.00 (29.00, 46.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e38.00 (29.00, 47.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.082\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eSAPS II, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e32.00 (25.00, 40.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e32.00 (25.00, 40.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e32.00 (24.00, 40.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e32.00 (24.00, 40.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e32.00 (24.00, 40.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e32.00 (24.00, 40.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.057\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eOASIS, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e28.00 (23.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e28.00 (23.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e28.00 (23.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.357\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e28.00 (23.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e28.00 (23.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e28.00 (23.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.169\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eGCS, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (14.00, 15.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e15.00 (14.00, 15.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (14.00, 15.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (14.00, 15.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e15.00 (14.00, 15.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (14.00, 15.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.007\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCharlson, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5.00 (3.00, 7.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e5.00 (3.00, 7.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5.00 (3.00, 8.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.003\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5.00 (3.00, 8.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e5.00 (3.00, 8.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5.00 (3.00, 8.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.067\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAPACHE II, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (11.00, 19.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e15.00 (11.00, 19.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (11.00, 20.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.391\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (11.00, 19.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e15.00 (11.00, 19.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15.00 (11.00, 19.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.597\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eSIRS, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.122\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e205 (0.72)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e147 (0.83)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e58 (0.54)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e114 (0.58)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e60 (0.61)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e54 (0.55)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3115 (10.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1955 (11.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1160 (10.78)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2176 (11.12)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1104 (11.28)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1072 (10.96)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 2\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e9693 (34.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e6158 (34.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3535 (32.86)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e6642 (33.94)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3385 (34.59)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3257 (33.29)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 3\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e12358 (43.44)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e7631 (43.13)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4727 (43.94)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8458 (43.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e4188 (42.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4270 (43.64)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 4\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3080 (10.83)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1802 (10.18)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1278 (11.88)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2180 (11.14)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1048 (10.71)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1132 (11.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eComorbidities\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHypertension,n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1157 (4.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e914 (5.17)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e243 (2.26)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e523 (2.67)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e283 (2.89)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e240 (2.45)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.057\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eLiver cirrhosis,\u003cbr\u003en(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e55 (0.19)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e42 (0.24)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e13 (0.12)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.030\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e32 (0.16)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e19 (0.19)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e13 (0.13)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.288\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHepatitis, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e87 (0.31)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e51 (0.29)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e36 (0.33)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.492\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e65 (0.33)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e33 (0.34)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e32 (0.33)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.901\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCVA, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e181 (0.64)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e144 (0.81)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e37 (0.34)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e78 (0.40)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e42 (0.43)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e36 (0.37)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.496\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCKD, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e269 (0.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e211 (1.19)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e58 (0.54)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e119 (0.61)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e65 (0.66)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e54 (0.55)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.312\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCancer, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e478 (1.68)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e373 (2.11)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e105 (0.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e221 (1.13)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e117 (1.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e104 (1.06)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.379\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eT2DM, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e580 (2.04)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e463 (2.62)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e117 (1.09)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e236 (1.21)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e120 (1.23)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e116 (1.19)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.793\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eT1DM, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e34 (0.12)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e27 (0.15)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7 (0.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.038\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15 (0.08)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e8 (0.08)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7 (0.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.796\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eObesity, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e94 (0.33)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e68 (0.38)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e26 (0.24)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.042\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e54 (0.28)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e30 (0.31)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e24 (0.25)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.414\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eSepsis, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e246 (0.86)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e133 (0.75)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e113 (1.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.008\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e201 (1.03)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e101 (1.03)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e100 (1.02)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.943\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCB, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e211 (0.74)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e154 (0.87)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e57 (0.53)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e130 (0.66)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e73 (0.75)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e57 (0.58)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.159\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHF, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e447 (1.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e356 (2.01)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e91 (0.85)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e192 (0.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e104 (1.06)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e88 (0.90)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.246\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eMI, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e165 (0.58)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e149 (0.84)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e16 (0.15)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e40 (0.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e24 (0.25)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e16 (0.16)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.205\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eIHD, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e882 (3.10)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e786 (4.44)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e96 (0.89)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e203 (1.04)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e107 (1.09)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e96 (0.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.438\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eMedications\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAspirin, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.074\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e20332 (71.46)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e11866 (67.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8466 (78.69)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e14984 (76.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e7439 (76.02)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7545 (77.11)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8119 (28.54)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e5827 (32.93)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2292 (21.31)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4586 (23.43)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e2346 (23.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2240 (22.89)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAntibiotics, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.397\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5530 (19.44)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e5134 (29.02)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e396 (3.68)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e769 (3.93)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e373 (3.81)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e396 (4.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e22921 (80.56)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e12559 (70.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e10362 (96.32)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e18801 (96.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e9412 (96.19)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e9389 (95.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eLab variables\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eRDW, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e14.50 (13.40, 16.10)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e14.30 (13.30, 15.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e14.80 (13.60, 16.60)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e14.70 (13.50, 16.40)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e14.60 (13.50, 16.30)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e14.70 (13.60, 16.50)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eRed blood, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.43 (2.93, 4.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3.41 (2.91, 3.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.47 (2.95, 4.06)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.48 (2.96, 4.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3.48 (2.97, 4.04)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3.47 (2.95, 4.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e0.451\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCreatinine, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.00 (0.70, 1.50)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1.00 (0.70, 1.40)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.10 (0.80, 1.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.00 (0.80, 1.60)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1.00 (0.80, 1.50)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.10 (0.80, 1.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eBUN, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e20.00 (14.00, 33.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e19.00 (13.00, 30.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e22.00 (14.00, 38.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e21.00 (14.00, 35.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e20.00 (14.00, 34.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e22.00 (14.00, 37.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eCalcium, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8.20 (7.70, 8.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e8.30 (7.80, 8.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8.20 (7.70, 8.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8.20 (7.70, 8.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e8.20 (7.70, 8.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8.20 (7.70, 8.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eChloride, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e105.00 (100.00, 108.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e105.00 (101.00, 109.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e104.00 (99.00, 108.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e104.00 (100.00, 108.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e104.00 (100.00, 108.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e104.00 (100.00, 108.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eGlucose, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e127.00 (105.00, 162.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e124.00 (104.00, 156.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e131.00 (106.00, 172.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e129.00 (106.00, 168.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e127.00 (105.00, 164.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e131.00 (106.00, 171.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003ePrimary Outcomes\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAKI, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e10888 (38.27)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e8391 (47.43)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2497 (23.21)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5732 (29.29)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e3420 (34.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2312 (23.63)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e17563 (61.73)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e9302 (52.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8261 (76.79)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e13838 (70.71)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e6365 (65.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7473 (76.37)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAki Stage, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4180 (23.80)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e2770 (29.78)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1410 (17.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2948 (21.30)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1663 (26.13)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1285 (17.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 2\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7725 (43.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e4443 (47.76)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3282 (39.73)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e6002 (43.37)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e2947 (46.30)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3055 (40.88)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 3\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5658 (32.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e2089 (22.46)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3569 (43.20)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4888 (35.32)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1755 (27.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3133 (41.92)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHematotoxicity, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15775 (55.45)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e10931 (61.78)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4844 (45.03)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e9563 (48.87)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e5123 (52.36)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4440 (45.38)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e12676 (44.55)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e6762 (38.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5914 (54.97)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e10007 (51.13)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e4662 (47.64)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e5345 (54.62)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHepatotoxicity, n(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 0\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e23905 (84.02)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e15657 (88.49)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8248 (76.67)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e15602 (79.72)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e7977 (81.52)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e7625 (77.93)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u0026nbsp; 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e4546 (15.98)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e2036 (11.51)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2510 (23.33)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e3968 (20.28)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1808 (18.48)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e2160 (22.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eSecondary outcomes\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHosp Day, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e8.78 (5.63, 16.65)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e8.15 (5.38, 14.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e9.73 (6.01, 20.14)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e9.11 (5.80, 17.94)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e8.88 (5.63, 16.82)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e9.67 (6.00, 19.17)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eIcu Day, M (Q₁, Q₃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.55 (1.00, 3.18)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1.46 (0.99, 2.88)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.76 (1.04, 4.06)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.66 (1.01, 3.53)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e1.62 (1.00, 3.23)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.71 (1.02, 3.83)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eZ: Mann‒Whitney test, \u0026chi;\u0026sup2;: Chi‒square test\u003c/p\u003e\n\u003cp\u003eM: Median, Q₁: 1st quartile, Q₃: 3rd quartile\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBody mass index (BMI), Sequential Organ Failure Assessment (SOFA), Acute Physiology Score III (APS III), Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), Glasgow Coma Scale (GCS), Acute Physiology and Chronic Health Evaluation II (APACHE II),\u0026nbsp;Systemic Inflammatory Response Syndrome (SIRS), cerebrovascular accident (CVA), chronic kidney disease (CKD),\u0026nbsp;type 1 and type 2 diabetes mellitus (T1DM, T2DM), cerebral bleeding (CB), heart failure (HF), myocardial infarction (MI), ischemiaemic heart disease (IHD), red cell distribution width (RDW), blood urea nitrogen (BUN), acute kidney injury (AKI), hospital length of stay (Hosp Day), and ICU length of stay (Icu Day)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Multivariable logistic and Cox regression analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the primary outcome, TDM of vancomycin demonstrated significant safety benefits after comprehensive adjustment for confounding factors (Table 2). While initial unadjusted analyses revealed greater risks of adverse events in the TDM group (AKI: OR=2.98, 95% CI=2.83--3.15; hematotoxicity: OR=1.97, 95% CI=1.88--2.07; hepatotoxicity: OR=2.34, 95% CI=2.19--2.50; all p\u0026lt;0.001), these associations substantially attenuated with progressive adjustment (Model 3: AKI OR=1.93, hematotoxicity: OR=1.55, hepatotoxicity: OR=1.25; all p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eFor the secondary outcome, the TDM group had a lower risk of in-hospital mortality (OR: 0.63, 95% CI: 0.54\u0026ndash;0.74, p \u0026lt; 0.001) after full adjustment (Model 3). Similarly, ICU mortality was reduced in the TDM group (adjusted OR: 0.72, 95% CI: 0.62\u0026ndash;0.85, p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e. \u003cstrong\u003eMultivariate-Adjusted Associations between Vancomycin Use and Clinical Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 19px;\"\u003eVariables\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 15px;\"\u003eTDM\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 19px;\"\u003eModel1\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 15px;\"\u003eModel2\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 22px;\"\u003eModel3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 8px;\"\u003eNon use\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003eUse\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003eOR (95%CI)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u003cem\u003eP\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003eOR (95%CI)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u003cem\u003eP\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003eOR (95%CI)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u003cem\u003eP\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003ePrimary Outcomes\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eAKI\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e9302 (52.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e8261 (76.79)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e2.98 (2.83 ~ 3.15)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.99 (1.87 ~ 2.12)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.93 (1.81 ~ 2.06)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHematotoxicity\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e6762 (38.22)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e5914 (54.97)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e1.97 (1.88 ~ 2.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.39 (1.32 ~ 1.47)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.55 (1.46 ~ 1.65)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eHepatotoxicity\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e2036 (11.51)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e2510 (23.33)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e2.34 (2.19 ~ 2.50)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.49 (1.39 ~ 1.59)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e1.25 (1.16 ~ 1.34)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eSecondary outcomes\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eIn-Hospital Mortality\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e8.15 (5.38, 14.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e9.73 (6.01, 20.14)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e0.49 (0.42 ~ 0.57)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e0.58 (0.49 ~ 0.67)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e0.63 (0.54 ~ 0.74)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003eIn-ICU Mortality\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e1.46 (0.99, 2.88)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e1.76 (1.04, 4.06)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e0.51 (0.44 ~ 0.59)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e0.64 (0.55 ~ 0.75)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2px;\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e0.72 (0.62 ~ 0.85)\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\u0026lt;.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003eOR: Odds Ratio, CI: Confidence Interval\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003eModel1: Crude\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003eModel2: Adjust: race, Hypertension, Liver_cirrhosis, CVA, CKD, Cancer, T2DM, T1DM, Obesity, Sepsis, CB, HF, MI, IHD, Aspirin, Antibiotics\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003eModel3: Adjust: race, Hypertension, Liver_cirrhosis, Hepatitis, CVA, CKD, Cancer, T2DM, T1DM, Obesity, Sepsis, CB, HF, MI, IHD, SIRS, Aspirin, Antibiotics, age, BMI, SOFA, APS III, SAPS II, OASIS, GCS, Charlson, APACHE II, RDW, Red_blood, Creatinine, BUN, Calcium, Chloride, Glucose\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Sensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLogistic regression analysis after PSM demonstrated significant associations between vancomycin TDM and clinical outcomes (Figure 3). For primary safety outcomes, TDM was associated with reduced risks of AKI (OR 0.580, 95% CI 0.540\u0026ndash;0.610; P=0.001), hematotoxicity (OR 0.760, 95% CI 0.710\u0026ndash;0.800; P=0.001), and hepatotoxicity (OR 0.800, 95% CI 0.750\u0026ndash;0.860; P=0.001).\u003c/p\u003e\n\u003cp\u003eWith respect to secondary outcomes, TDM had protective effects on in-hospital mortality (OR 0.672, 95% CI 0.570\u0026ndash;0.790; P=0.001) and ICU mortality (OR 0.691, 95% CI 0.580\u0026ndash;0.820; P=0.001). All associations were statistically significant, with P values of 0.001 and odds ratios consistently below 1.0, indicating beneficial effects of TDM across all measured outcomes.\u003c/p\u003e\n\u003cp\u003eThe narrow confidence intervals for each outcome suggest precise effect estimates, supporting the robustness of these findings. The consistency in direction and significance across both primary and secondary outcomes reinforces the clinical benefits associated with vancomycin TDM in this patient population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Subgroup analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSubgroup analyses identified several significant risk factors for adverse outcomes (Figure 4). For AKI, hypertension (OR=2.14, 95% CI=1.25\u0026ndash;3.67, P=0.006), cancer (OR=2.64, 95% CI=1.04\u0026ndash;6.66, P=0.040), CB (OR=4.96, 95% CI=1.39\u0026ndash;17.72, P=0.014), aspirin use (OR=1.34, 95% CI=1.15\u0026ndash;1.57, P=0.001), and antibiotic use (OR=1.70, 95% CI=1.59\u0026ndash;1.81, P=0.001) were significantly associated with increased risk. For hematotoxicity, significant associations were observed with hypertension (OR=1.62, 95% CI=1.10\u0026ndash;2.40, P=0.015), hepatitis (OR=20.47, 95% CI=3.04\u0026ndash;138.05, P=0.002), aspirin use (OR=1.36, 95% CI=1.20\u0026ndash;1.54, P=0.001), and antibiotic use (OR=1.23, 95% CI=1.16\u0026ndash;1.31, P=0.001). Notably, T2DM was significantly associated with hematotoxicity outcomes (OR=1.16, 95% CI=1.08--1.25, P=0.001), whereas aspirin (OR=1.82, 95% CI=1.52--2.18, P=0.001) and antibiotics (OR=1.14, 95% CI=1.05--1.22, P=0.001) remained significant across all analyses. Several variables, including liver cirrhosis, CVA, T1DM, and obesity, presented extreme OR values with wide confidence intervals, likely due to small sample sizes, resulting in nonsignificant P values. The consistency of antibiotic and aspirin associations across multiple outcomes suggests their important role in adverse event risk.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Kaplan‒Meier analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Kaplan‒Meier survival analyses after propensity score matching demonstrated significant survival benefits associated with vancomycin TDM (Figure 5). For ICU survival, the TDM group had significantly better outcomes than did the non-TDM group (HR 0.691, 95% CI 0.585--0.816, log-rank P \u0026lt; 0.001), with consistently greater numbers at risk throughout the follow-up period (TDM vs non-TDM: 9785 vs 9785 at baseline; 1738 vs 1423 at later time points). Similarly, for in-hospital survival, the TDM group exhibited a significantly reduced mortality risk (HR 0.672, 95% CI 0.569\u0026ndash;0.794, log-rank P \u0026lt; 0.001), with maintained numerical advantages in patients at risk across all observed time intervals (TDM vs non-TDM: 9774 vs 9778 at baseline; 4673 vs 4246 at subsequent assessments). These robust findings, as evidenced by highly significant P values and hazard ratios below 1.0 with narrow confidence intervals, consistently support the survival benefit of vancomycin TDM in both ICU and hospital settings. The larger number of patients remaining at risk in the TDM groups at each follow-up point further reinforces these survival advantages.\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe results of this study suggest that although initial multimodel controlled logistic regression analyses revealed that the TDM group did not demonstrate a significant safety advantage (OR\u0026gt;1), this finding should be interpreted carefully in the context of baseline characteristics. Notably, baseline analyses revealed that patients in the TDM group had higher disease severity scores and worse clinical statuses. This group imbalance may have obscured the true effect of TDM. As more covariates were progressively controlled in the models, the ORs exhibited a decreasing trend, indicating that the initial negative results were likely driven by baseline disparities between the groups. This inference was further supported by PSM; after baseline characteristics were balanced, the TDM group showed significant improvement (OR\u0026lt;1) in all three safety outcomes \u0026mdash; AKI, hematotoxicity, and hepatotoxicity. Together, these findings suggest that vancomycin TDM indeed enhances therapeutic safety, and the earlier unfavorable results likely reflect the clinical reality that TDM is preferentially used in patients with more severe conditions. Consequently, this study provides compelling evidence to support the routine implementation of vancomycin TDM in ICU patients, particularly critically ill individuals, where safety benefits are more pronounced.\u003c/p\u003e\n\u003cp\u003eThe findings also diverge somewhat from the existing literature. For example, Yang et al.[21] reported no statistically significant association between vancomycin TDM and a reduced incidence of nephrotoxicity, whereas our study revealed that TDM significantly decreases the risk of nephrotoxicity in ICU patients. This discrepancy may be attributed to several factors: although Yang\u0026rsquo;s study included 971 treatment sessions, the intervention group comprised only 207 cases, and the follow-up period was short (one year), potentially limiting statistical validity. Additionally, as a single-center retrospective study, it may have suffered from selection bias and inadequate control of ICU-specific confounders such as SOFA scores and vasoactive medication use. Notably, multiple studies support our findings; for example, a systematic review and meta-analysis [22] confirmed that TDM significantly reduces nephrotoxicity risk (HR=0.25, 95% CI=0.13\u0026ndash;0.48; p\u0026lt;0.0001). Several researchers have also demonstrated that vancomycin therapeutic drug monitoring is associated with shorter treatment durations and lower total doses [2][23][24][25]. Regarding mortality outcomes, evidence from the MIMIC-IV database corroborates our finding that TDM is linked to reduced mortality, despite differences in database versions (3.1 vs. 2.1) [26]. The strengths of this study include the use of multicenter, large-sample ICU data from the MIMIC-IV, rigorous propensity score matching, multiple regression analyses, and sensitivity tests that validate the robustness of our results. These methodological strengths provide a greater level of evidence supporting the nephroprotective role of TDM in critically ill patients.\u003c/p\u003e\n\u003cp\u003eIn this study, we systematically analyzed the risk factors associated with vancomycin-related toxicity. We found that hypertension, malignancy, CB, aspirin use, and antibiotic coadministration were significantly linked to an increased risk of nephrotoxicity. Conversely, hypertension, hepatitis, aspirin, and antibiotic use were significantly associated with hematologic toxicity. Notably, type 2 diabetes was specifically associated with hepatotoxicity, and the combination of aspirin with antibiotics consistently demonstrated significant correlations across all toxicity analyses. Previous studies have identified key risk factors for vancomycin-associated nephrotoxicity, including the concurrent use of nephrotoxic drugs (e.g., aminoglycosides, amphotericin B) [27][28][29], prolongation of treatment duration [27][30], and the use of vasoactive medications [30]. Vancomycin exhibits considerable interindividual variability in pharmacokinetics among adults [31], a variation that is particularly pronounced in critically ill populations such as patients with severe sepsis, those undergoing continuous veno-venous hemodialysis, patients with malignancies, neonates, and severe burn victims [10][14][32][33][34][35][36][37][38]. Moreover, predicting blood levels in specific high-risk groups\u0026mdash;such as patients with heart failure [39], obesity [40], or renal insufficiency[27][30][41]\u0026mdash;is challenging, underscoring the importance of TDM in these populations. Some studies [42] have also suggested that TDM provides limited clinical benefit in patients with normal renal function. Our findings confirm known risk factors and, importantly, for the first time, systematically reveal a potential synergistic effect of aspirin across multiple forms of vancomycin toxicity. This novel insight may inform more rational and evidence-based clinical use of vancomycin.\u003c/p\u003e\n\u003cp\u003eAlthough the present study was limited by the use of the MIMIC-IV database, which precluded the collection of data on ototoxicity and Red Man syndrome, the literature offers valuable insights into these adverse reactions. Research indicates that Red Man syndrome is primarily mediated by histamine release and manifests clinically as flushing and tingling sensations in the face, neck, and upper body [8]. Its occurrence is closely related to the infusion rate, with a significantly increased risk when doses exceeding 500 mg are infused rapidly over 30 minutes [11][17][43]. Consequently, clinical guidelines recommend controlling the infusion time for 1 g doses to at least 1 hour [44] and for higher doses (e.g., 2 g) to extend to 1.5\u0026ndash;2 hours [45]. These standardized practices effectively prevent the syndrome. With respect to ototoxicity, available studies depict a more complex picture. Early reports by Bailie et al. [46], covering studies from 1956--1986, linked ototoxicity mainly to vancomycin preparations with high impurity levels. Notably, several studies have failed to establish a clear association between vancomycin blood levels and ototoxicity [2][44], and the incidence of ototoxicity when vancomycin is used alone appears to be very low [2]. Age has emerged as a significant risk factor [47], with a retrospective study demonstrating a higher incidence in patients aged \u0026ge;53 years than in younger patients (p=0.008) [48]. Additionally, coadministration of other ototoxic agents (e.g., aminoglycosides and certain diuretics) may result in synergistic toxicity. On the basis of current evidence, heightened vigilance remains necessary for high-risk groups, such as elderly individuals, individuals with pre-existing hearing loss, and those receiving multiple ototoxic medications [49]. These findings increase our understanding of the adverse effects of vancomycin. Although this study\u0026rsquo;s database limitations prevented direct analysis of these outcomes, existing evidence suggests that these drug-related risks can be effectively managed through infusion standardization and identification of at-risk populations.\u003c/p\u003e\n\u003cp\u003eAlthough vancomycin dose and trough concentration data were not directly analyzed in this study, the available evidence indicates that these parameters are strongly associated with safety. The literature consistently demonstrates that elevated serum trough concentrations and prolonged vancomycin treatment duration increase the risk of nephrotoxicity [50]. Older age, longer treatment courses, and lower serum vancomycin concentrations (30\u0026ndash;65 mg/L) are significant risk factors for vancomycin-induced nephrotoxicity [51]. Notably, treatment durations exceeding one week can increase nephrotoxicity risk from 6% to 30% [52], and concomitant use of nephrotoxic agents (e.g., aminoglycosides) can increase the incidence from 5\u0026ndash;7% to as high as 22% with monotherapy [2][11][28]. The pharmacokinetic properties of vancomycin, which accounts for approximately 80\u0026ndash;90% of vancomycin renally excreted [20], underscore the importance of precise dose adjustment in patients with renal impairment [53]. Multiple studies have shown that higher doses significantly increase nephrotoxicity risk, with rates reaching 12\u0026ndash;42.7% [10][11][27][54][55]. While clinical guidelines for MRSA infection management [56] and the vancomycin TDM consensus [2] recommend maintaining trough levels between 15\u0026ndash;20 \u0026mu;g/mL and Australian guidelines suggest 12\u0026ndash;18 \u0026mu;g/mL [57]\u0026nbsp;\u003cstrong\u003e(to ensure an AUC/MIC \u0026ge;400\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e[2]\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e, recent research indicates that these ranges may heighten the risk of acute kidney injury\u0026nbsp;[58][59]. In high-risk populations,\u0026nbsp;such as pediatric, renal failure, or critically ill patients\u0026nbsp;[20][60][61][62],\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eindividualized dosing via TDM is essential because of significant pharmacokinetic variability\u0026nbsp;[63].\u0026nbsp;With respect to administration mode, studies comparing continuous versus intermittent infusion have yielded mixed results. Although some reports suggest potential advantages of continuous infusion, there is no conclusive evidence that it is superior in terms of clinical outcomes\u0026nbsp;[64][65][66]. Consequently, current guidelines continue to endorse intermittent infusion as the standard. These findings underscore the critical role of TDM in balancing efficacy and safety, particularly in high-risk groups.\u003c/p\u003e\n\u003cp\u003eThis study has several methodological limitations that warrant clarification. First, although we used AKI based on the KDIGO criteria as a surrogate for nephrotoxicity \u0026mdash; which is consistent with most literature [2][67] \u0026mdash; this may introduce bias in assessing drug-related nephrotoxicity in clinical practice [68]. Second, owing to database constraints, we could not differentiate between types of TDM modalities (e.g., AUC monitoring versus trough concentration monitoring alone) or access specific TDM protocols (e.g., sampling times, dose adjustment criteria) at individual centers, potentially affecting result interpretation. Third, despite the use of multivariate adjustment and propensity score matching (with a caliper of 0.1), residual confounding may persist in this retrospective design. Additionally, the database included only hospitalization data, preventing the assessment of delayed adverse events such as permanent hearing impairment that may manifest postdischarge. Finally, this study did not evaluate the economic aspects of TDM implementation; however, existing evidence suggests [17][38] that TDM can be cost-effective \u0026mdash; particularly in critically ill, oncologic, or patients receiving conephrotoxic agents \u0026mdash; a crucial consideration for future research and clinical decision-making.\u003c/p\u003e"},{"header":"5 conclusion","content":"\u003cp\u003eThis study confirms that implementing vancomycin TDM in ICU patients significantly enhances medication safety. Cohort analysis demonstrated that TDM is associated with a substantial reduction in vancomycin-related nephrotoxicity, hematotoxicity, and hepatotoxicity, as well as a notable decrease in ICU and in-hospital mortality. Importantly, TDM also benefits high-risk patients, including those with hypertension or those receiving nephrotoxic comedications. These findings underscore the importance of routine vancomycin TDM in critically ill populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFull Term\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAKI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAcute kidney injury\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAPS III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAcute Physiology Score III\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAPACHE II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAcute Physiology and Chronic Health Evaluation II\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eASHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAmerican Society of Health-System Pharmacists\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBody mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBUN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBlood urea nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCerebral bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eConfidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eChronic kidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSerum creatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCerebrovascular accident\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGlasgow Coma Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHeart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHosp Day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHospital length of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIcu Day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eICU length of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIschemic heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIntensive care unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIDSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfectious Diseases Society of America\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInterquartile range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMIMIC-IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedical Information Mart for Intensive Care IV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMyocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMRSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMethicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOASIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOxford Acute Severity of Illness Score\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePropensity score matching\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRDW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRed cell distribution width\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSAPS II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSimplified Acute Physiology Score II\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSystemic Inflammatory Response Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSOFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSQL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStructured Query Language\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eT1DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eType 1 diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eT2DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eType 2 diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTherapeutic drug monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research involving human participants was approved, and the need for further ethical approval was waived by the Clinical Research Ethics Committee of the First Affiliated Hospital of Shantou University Medical College, Shantou. This exemption was granted because ethical approval for the MIMIC-IV database had already been obtained from the institutional review boards (IRBs) of Beth Israel Deaconess Medical Center and the Massachusetts Institute of Technology. The study complied with local regulations and institutional standards. Furthermore, written informed consent from participants or their legal guardians / next of kin was waived by the ethics committee / institutional review board, as the research followed applicable legal and institutional policies, and the database contains no protected health information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript and consent to its publication in this journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MIMIC-IV database used in this study is publicly available to researchers who meet the criteria for access. Detailed instructions for obtaining the data can be found at https://mimic-iv.mit.edu/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 81801189) and the \u0026ldquo;Ying Cai Tuo Ju\u0026rdquo; Program at the First Affiliated Hospital of Shantou University Medical College (Grant No. YCTJ-2022-03).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis short text acknowledges the contributions of specific colleagues, institutions, or agencies that aided the efforts of the authors. All the authors contributed to the study conception and design. Project design, patient information verification, and data cleaning, W.J.; paper writing and data checking, W.Z.M.; data inclusion and cleaning, H.C.Z.; data organization and statistical analysis, C.Y.; and data statistics, H.Y.L. All the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciated the funders presented in the funding.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLevine DP. Vancomycin: understanding its past and preserving its future. South Med J. 2008 Mar;101(3):284-91. doi: 10.1097/SMJ.0b013e3181647037. PMID: 18364659.\u003c/li\u003e\n\u003cli\u003eRybak M, Lomaestro B, Rotschafer JC, Moellering R Jr, Craig W, Billeter M, Dalovisio JR, Levine DP. Therapeutic monitoring of vancomycin in adult patients: a consensus review of the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, and the Society of Infectious Diseases Pharmacists. Am J Health Syst Pharm. 2009 Jan 1;66(1):82-98. doi: 10.2146/ajhp080434. Erratum in: Am J Health Syst Pharm. 2009 May 15;66(10):887. PMID: 19106348.\u003c/li\u003e\n\u003cli\u003eAbramson MA, Sexton DJ. Nosocomial methicillin-resistant and methicillin-susceptible Staphylococcus aureus primary bacteremia: at what costs? Infect Control Hosp Epidemiol. 1999 Jun;20(6):408-11. doi: 10.1086/501641. PMID: 10395142.\u003c/li\u003e\n\u003cli\u003eCosgrove SE, Sakoulas G, Perencevich EN, Schwaber MJ, Karchmer AW, Carmeli Y. Comparison of mortality associated with methicillin-resistant and methicillin-susceptible Staphylococcus aureus bacteremia: a meta-analysis. Clin Infect Dis. 2003 Jan 1;36(1):53-9. doi: 10.1086/345476. Epub 2002 Dec 13. PMID: 12491202.\u003c/li\u003e\n\u003cli\u003eEngemann JJ, Carmeli Y, Cosgrove SE, Fowler VG, Bronstein MZ, Trivette SL, Briggs JP, Sexton DJ, Kaye KS. Adverse clinical and economic outcomes attributable to methicillin resistance among patients with Staphylococcus aureus surgical site infection. Clin Infect Dis. 2003 Mar 1;36(5):592-8. doi: 10.1086/367653. Epub 2003 Feb 7. PMID: 12594640.\u003c/li\u003e\n\u003cli\u003eHarbarth S, Rutschmann O, Sudre P, Pittet D. Impact of methicillin resistance on the outcome of patients with bacteremia caused by Staphylococcus aureus. Arch Intern Med. 1998 Jan 26;158(2):182-9. doi: 10.1001/archinte.158.2.182. PMID: 9448557.\u003c/li\u003e\n\u003cli\u003eNoskin GA, Rubin RJ, Schentag JJ, Kluytmans J, Hedblom EC, Smulders M, Lapetina E, Gemmen E. The burden of Staphylococcus aureus infections on hospitals in the United States: an analysis of the 2000 and 2001 Nationwide Inpatient Sample Database. 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J Antimicrob Chemother. 2012;67:17\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eWunderink RG, Niederman MS, Kollef MH, Shorr AF, Kunkel MJ, Baruch A, McGee WT, Reisman A, Chastre J. Linezolid in methicillin-resistant Staphylococcus aureus nosocomial pneumonia: a randomized, controlled study. Clin Infect Dis. 2012 Mar 1;54(5):621-9. doi: 10.1093/cid/cir895. Epub 2012 Jan 12. PMID: 22247123.\u003c/li\u003e\n\u003cli\u003eFilippone, E. J., Kraft, W. K., \u0026amp; Farber, J. L. (2017). The nephrotoxicity of vancomycin. Clinical Pharmacology \u0026amp; Therapeutics, 102(3), 459-469.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vancomycin, therapeutic drug monitoring, ICU, nephrotoxicity, hepatotoxicity, hematotoxicity, MIMIC-IV","lastPublishedDoi":"10.21203/rs.3.rs-7437818/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7437818/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Vancomycin is a first-line treatment for methicillin-resistant Staphylococcus aureus (MRSA)infections but is associated with risks of nephrotoxicity (5–43%), hepatotoxicity, and hematotoxicity. Therapeutic drug monitoring (TDM) is recommended to optimize dosing, yet its impact on multi-organ toxicity and mortality in intensive care unit (ICU) patients remains controversial because ofconflicting evidence and methodological limitations in prior studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v3.1) database for a retrospective cohort analysis of 28,451 ICU patients receiving intravenous vancomycin. The primary outcomes were vancomycin-associated nephrotoxicity (AKI according to the KDIGO criteria), hepatotoxicity (ALT/AST ≥120 U/L or bilirubin ≥2.5 mg/dL), and hematotoxicity (thrombocytopenia, anemia, or leukopenia); secondary outcomes included ICU / hospital mortality. Propensity score matching (PSM, 1:1 nearest neighbor with caliper=0.1) balanced 32 baseline covariates,including demographics. The associations between TDM and outcomes were evaluated via multivariable logistic regression and Cox proportional hazards models, with the results validated through subgroup analyses (stratified by comorbidities and concomitant medications) and sensitivity analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Data from 28,451 ICU patients receiving intravenous vancomycin were extracted from the MIMIC-IV database, with 10,758 (37.8%) receiving TDM and 17,693 (62.2%) not receiving TDM. Before PSM, the TDM group presented higher baseline illness severity scores (e.g., SOFA, APS III) and more comorbidities. Unadjusted analyses revealed increased risks of adverse outcomes in the TDM group (AKI: OR = 2.98, 95% CI: 2.83–3.15; hematotoxicity: OR = 1.97, 95% CI: 1.88–2.07; hepatotoxicity: OR = 2.34, 95% CI: 2.19–2.50; all \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). However, with progressive adjustment for confounders, these associations attenuated significantly (Model 3: AKI OR = 1.93, hematotoxicity OR = 1.55, hepatotoxicity OR = 1.25; all \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). After PSM, the TDM group demonstrated significantly reduced risks of AKI (OR = 0.580, 95% CI: 0.540–0.610, \u003cem\u003eP\u003c/em\u003e = 0.001), hematotoxicity (OR = 0.760, 95% CI: 0.710–0.800, \u003cem\u003eP\u003c/em\u003e = 0.001), and hepatotoxicity (OR = 0.800, 95% CI: 0.750–0.860, \u003cem\u003eP\u003c/em\u003e = 0.001). Secondary outcomes also favored TDM, with lower in-hospital mortality (OR = 0.672, 95% CI: 0.570–0.790, \u003cem\u003eP\u003c/em\u003e = 0.001) and ICU mortality (OR = 0.691, 95% CI: 0.580–0.820, \u003cem\u003eP\u003c/em\u003e = 0.001). Kaplan-Meier analysis further confirmed the survival benefits of TDM in both ICU and hospital settings (log-rank \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Subgroup analyses revealed that hypertension, type 2 diabetes mellitus (T2DM), cancer, cerebral bleeding (CB), and concomitant use of aspirin or antibiotics weresignificant risk factors for nephrotoxicity, hematotoxicity and hepatotoxicity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This study demonstrated that vancomycin TDM significantly reduces toxicity risks (nephrotoxicity, hepatotoxicity, hematotoxicity) and mortality in intensive care unit (ICU) patients, supporting its routine use in critically ill populations.\u003c/p\u003e","manuscriptTitle":"Vancomycin Therapeutic Drug Monitoring Reduces Toxicity in ICU Patients: A MIMIC-IV Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 23:08:06","doi":"10.21203/rs.3.rs-7437818/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-31T03:55:26+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"338066807257547605208746654783181277885","date":"2025-12-13T01:40:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-26T05:45:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T21:53:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46827100529976768470581328345947031891","date":"2025-10-23T01:32:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-20T15:52:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317363356745877223743076935493249051739","date":"2025-10-18T18:38:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25693716310500773234148917505931789286","date":"2025-10-18T04:19:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"119929545198936006364099085279723495956","date":"2025-10-16T04:29:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-08T07:29:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-07T06:18:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-01T04:34:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-28T08:26:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-28T08:21:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"586fb8fd-8ab6-46f2-9127-71c06c27d26a","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":56595406,"name":"Health sciences/Diseases"},{"id":56595407,"name":"Health sciences/Medical research"},{"id":56595408,"name":"Health sciences/Nephrology"},{"id":56595409,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-03-16T16:03:07+00:00","versionOfRecord":{"articleIdentity":"rs-7437818","link":"https://doi.org/10.1038/s41598-026-42395-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-03-11 15:59:37","publishedOnDateReadable":"March 11th, 2026"},"versionCreatedAt":"2025-10-21 23:08:06","video":"","vorDoi":"10.1038/s41598-026-42395-1","vorDoiUrl":"https://doi.org/10.1038/s41598-026-42395-1","workflowStages":[]},"version":"v1","identity":"rs-7437818","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7437818","identity":"rs-7437818","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}