Association Between Estimated Pulse Wave Velocity and 30 Day All-Cause Mortality in Patients with Acute Pancreatitis: a Retrospective Cohort Analysis of the MIMIC-IV Database

Association Between Estimated Pulse Wave Velocity and 30 Day All-Cause Mortality in Patients with Acute Pancreatitis: a Retrospective Cohort Analysis of the MIMIC-IV Database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association Between Estimated Pulse Wave Velocity and 30 Day All-Cause Mortality in Patients with Acute Pancreatitis: a Retrospective Cohort Analysis of the MIMIC-IV Database Yuxiang Zhai, Xiangtian Liu, Xinghan Tian, Liping Ye This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7393160/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Estimated pulse wave velocity (ePWV) is a validated surrogate marker of arterial stiffness and has demonstrated robust prognostic value in various cardiovascular diseases. Acute pancreatitis (AP) is a prevalent and potentially life-threatening gastrointestinal disorder; however, to our knowledge, no prior study has investigated the prognostic significance of ePWV in this population. Methods We identified adult patients with AP admitted to the intensive care unit (ICU) from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. ePWV was calculated using an established formula based on age and mean arterial pressure (MAP) recorded on the first ICU day, and categorized patients into high- and low-ePWV groups based on the median value. The primary endpoint was 30-day all-cause mortality; secondary endpoints included 60- and 90-day mortality. The Kaplan–Meier method and multivariable Cox proportional-hazards models were applied to assess associations between ePWV and outcomes, and restricted cubic spline analysis was performed to explore the dose–response relationship. Results A total of 1,351 patients with AP were included (mean age, 51.2 years; 48.7% male). Patients in the high-ePWV group were older (64.3 vs. 37.8 years, P < 0.001) and had significantly higher 30-, 60-, and 90-day mortality rates. In multivariable analysis, elevated ePWV was independently associated with an increased risk of 30-day mortality (hazard ratio, 2.12; 95% CI, 1.59–2.82; P < 0.001). Restricted cubic spline analysis revealed a positive, dose–response association between ePWV and 30-day mortality, consistent across subgroups stratified by age, race, and hypertension status. Conclusion Elevated ePWV is independently associated with higher short-term mortality in patients with AP, supporting its potential role as a simple and readily obtainable prognostic biomarker in the ICU setting. Estimated pulse wave velocity Mortality Acute pancreatitis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acute pancreatitis (AP) is a common disorder of the digestive system, most frequently precipitated by gallstones, excessive alcohol consumption, or hypertriglyceridemia. Approximately 20% of AP cases progress to moderate or severe disease—characterized by pancreatic and peripancreatic necrosis and, in some instances, multi-organ failure—with mortality rates as high as 30%[ 1 ]. Early assessment of disease severity and prompt intervention are therefore critical. Widely used clinical scoring systems for AP severity include the Ranson criteria, which integrate multiple clinical and laboratory variables[ 2 ]; the Bedside Index for Severity in Acute Pancreatitis (BISAP) score[ 3 ]; the modified Marshall scoring system for organ dysfunction[ 4 ]; and the Balthazar grading system based on computed tomography findings[ 5 ]. However, these tools require collection of multiple parameters and do not provide a single rapid predictor of severity. Arteriosclerosis, primarily in the form of atherosclerosis characterized by arterial plaque formation, may contribute to chronic pancreatic injury by reducing islet perfusion and inducing hypoxia. This process can lead to progressive β-cell dysfunction, structural alterations of the islets, β-cell loss, and diminished insulin production[ 6 ]. This process fosters dyslipidemia, obesity, and hypertension, creating a vicious cycle that exacerbates arterial stiffening. Advanced age, obesity, diabetes mellitus, and hypertriglyceridemia are established atherosclerosis risk factors and have also been closely associated with AP onset and severity[ 7 ]. Pulse wave velocity (PWV) is a validated measure of arterial stiffness and vascular elasticity, but its clinical use is constrained by the need for specialized equipment. An equation combining patient age and blood pressure to estimate PWV (ePWV) has been validated as a reliable surrogate for measured PWV[ 8 ]. ePWV has shown prognostic utility across various conditions, particularly cardiovascular diseases[ 9 ]; however, its prognostic significance in AP remains unexplored. Accordingly, this study evaluates the predictive value of ePWV in patients with AP using a large intensive care database. Method Dataextraction This study used data from MIMIC-IV version 3.1, a publicly available, de-identified dataset containing detailed information on ICU admissions at Beth Israel Deaconess Medical Center in Boston, USA[ 10 ]. Because only anonymized, third-party data were used, the study was exempt from institutional review board approval. Xiangtian Liu (certification ID: 65112747) was granted access to the MIMIC-IV database. Data extraction was performed using structured query language (SQL) in PostgreSQL (version 15.2.1) and Navicat Premium (version 15). The SQL scripts were obtained from the official GitHub repository ( https://github.com/MIT-LCP/mimic-iv ). Acute pancreatitis cases were identified in MIMIC-IV by International Classification of Diseases, Ninth and Tenth Revisions (ICD-9 and ICD-10) codes for acute pancreatitis. Exclusion criteria were age < 18 years, ICU length of stay < 24 hours, cirrhosis, end-stage renal disease, malignancy, or non-first ICU admission. Extracted patient variables included: (1)Demographics: age, sex, race; (2)First-day ICU vital signs: temperature, heart rate, blood pressure, and mean arterial pressure; (3)Comorbidities: Charlson Comorbidity Index components (e.g., myocardial infarction, congestive heart failure); (4)Therapies: antihypertensive drugs, hemopurification, mechanical ventilation; (5)Clinical outcomes: hospital length of stay, ICU duration, and survival status at 30, 60, and 90 days ; (6)Laboratory tests: first available values after admission; (7)Severity scores: Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score II (SAPS II) Estimated pulse wave velocity (ePWV) was calculated using patient age and the average mean arterial pressure (MAP) over the first 24 hours of ICU admission to minimize measurement error. eWPV = 9.587 - (0.402 × age) + (4.5610 × 0.001 × age2) - (2.621 × 0.00001 × age2 × MBP) + (3.176 × 0.001 × age × MBP) - (1.832 × 0.01 × MBP) Statistical Analysis: We assessed the distribution of continuous variables with the Shapiro–Wilk test. Variables with a normal distribution are presented as mean ± SD and compared using Student’s t-test or one-way ANOVA; non-normally distributed variables are reported as median (interquartile range) and compared using the Wilcoxon rank-sum test. Categorical variables are expressed as n (%) and compared with the chi-square test, continuity-corrected chi-square test, or Fisher’s exact test as appropriate.Kaplan–Meier curves were used to compare 30-day mortality between high- and low-ePWV groups, with the log-rank test assessing significance. Cox proportional-hazards models evaluated the association between ePWV and 30-day mortality. Non-linear relationships were modeled using restricted cubic splines with knots at the 0.25, 0.5, 0.75, and 0.95 quantiles of the ePWV distribution. Analyses were performed in R version 4.4.1. Variables with more than 10% missing values were excluded; those with up to 30% missingness were imputed using the missForest package (see Supplementary Table 1). Clinically relevant covariates were entered into multivariable models; variables with a variance inflation factor (VIF) > 5 were removed to mitigate multicollinearity. Predefined subgroup analyses employed Cox models to assess the association between ePWV and 30-day mortality stratified by age (< 65 vs. ≥ 65 years), sex, race, diabetes, hypertension, hemopurification (including RRT and CRRT), and mechanical ventilation. Results 1. Baseline Information and Clinical Outcomes Figure 1 displays the patient inclusion flowchart. A total of 1,351 patients with severe acute pancreatitis (SAP) who met the diagnostic criteria were initially identified. After applying the exclusion criteria, 1,351 patients remained, with 676 assigned to the low-ePWV group (T1) and 675 to the high-ePWV group (T2). Table 1 summarizes the baseline characteristics of the two groups of patients. A total of 1,351 eligible AP patients were included, of whom 51.2% were male and 53.3% were White. As an indicator of vascular aging, mean age was significantly lower in the low-ePWV group compared to the high-ePWV group (37.8 vs. 64.3 years; P < 0.001). The high-ePWV group also had significantly longer hospital and ICU stays and a higher in-hospital mortality rate. Regarding severity scores, patients in the high-ePWV group had higher median SOFA scores (4.00 vs. 2.00; P = 0.001) and SAPS II scores (35.0 vs. 23.0; P < 0.001). This group also had a higher prevalence of common comorbidities, including hypertension and diabetes, and a greater proportion received corresponding antihypertensive therapies. Table 1 Summary the characteristics in AP patients. All (n = 1351) T1 (n = 676) T2 (n = 675) p ePWV 7.49[6.34;8.91] 6.34[5.87;6.94] 8.91[8.08;10.3] < 0.001 Age(Year) 51.2[36.0;64.3] 37.8 [28.1;47.9] 64.3[55.1;72.1] < 0.001 Race(White) 720(53.3%) 352(52.1%) 368(54.5%) 0.485 Sex(Male) 658(48.7%) 295(43.6%) 363(53.8%) < 0.001 Length of hospital stay(day) 5.60[3.46;9.96] 4.27[2.87;7.54] 7.04[4.56;12.3] < 0.001 Length of ICU stay(day) 2.02[1.48;3.05] 1.93[1.41;2.84] 2.15[1.54;3.36] < 0.001 In-hospital mortality 74(5.48%) 19(2.81%) 55(8.15%) < 0.001 SOFA Score 3.00[2.00;5.00] 2.00[1.00;5.00] 4.00[2.00;6.00] < 0.001 SAPSII Score 28.0[20.0;39.0] 23.0[17.0;30.0] 35.0[27.0;43.0] < 0.001 Myocardial Infarct 248(18.4%) 56(8.28%) 192(28.4%) < 0.001 Congestive Heart Failure 260(19.2%) 72(10.7%) 188(27.9%) < 0.001 Peripheral Vascular Disease 107(7.92%) 31(4.59%) 76(11.3%) < 0.001 Cerebrovascular Disease 116(8.59%) 26(3.85%) 90(13.3%) < 0.001 Dementia 38(2.81%) 1(0.15%) 37(5.48%) < 0.001 Chronic Pulmonary_Disease 213(15.8%) 87(12.9%) 126(18.7%) 0.004 Rheumatic Disease 28(2.07%) 11(1.63%) 17(2.52%) 0.338 Mild Liver Disease 125(9.25%) 56(8.28%) 69(10.2%) 0.256 Peptic Ulcer_Disease 33(2.44%) 11(1.63%) 22(3.26%) 0.077 Paraplegia 31(2.29%) 5(0.74%) 26(3.85%) < 0.001 Renal Disease 429(31.8%) 135(20.0%) 294(43.6%) < 0.001 Diabetes 936(69.3%) 427(63.2%) 509(75.4%) < 0.001 Hypertension 480(35.5%) 194(28.7%) 286(42.4%) < 0.001 Coronary Heart Disease 171 (12.7%) 31 (4.59%) 140 (20.7%) < 0.001 Hemoglobin_(g/dL) 11.1[9.50;12.6] 11.3[9.70;12.9] 10.9[9.40;12.3] 0.004 Platelets_(K/uL) 236[181;300] 245[191;305] 228[173;294] 0.003 WBC (K/uL) 11.4[8.10;15.8] 10.9[7.68;15.9] 11.7[8.60;15.7] 0.054 Aniongap_(mmol/L) 20.0[16.0;25.0] 21.0[16.0;26.0] 19.0[16.0;24.0] 0.046 Bicarbonate_(mmol/L) 17.0[12.0;20.0] 15.0[10.0;19.0] 18.0[14.0;21.0] < 0.001 lacticdehydrogenase(U/L) 8.50[8.07;9.00] 8.30[7.90;8.80] 8.70[8.30;9.11] < 0.001 Chloride(mEq/l) 103[97.0;108] 104[98.0;109] 101[97.0;107] < 0.001 Creatinine_(mg/dl) 1.30[0.90;2.20] 1.00[0.80;1.70] 1.60[1.10;2.60] < 0.001 Glucose(mg/dL) 279[192;414] 262[187;401] 300[198;429] 0.004 Sodium(mmol/L) 137[133;140] 137[133;140] 137[134;141] 0.009 Potassium(mmol/L) 4.30[3.80;4.80] 4.20[3.80;4.62] 4.30[3.80;4.90] 0.005 BUN(mg/dL) 26.0[14.7;46.0] 18.0[11.0;36.0] 35.0[22.0;52.0] < 0.001 INR 1.10[1.00;1.20] 1.10[1.00;1.20] 1.10[1.00;1.30] < 0.001 PT(seconds) 12.2[11.4;13.5] 12.1[11.4;13.2] 12.3[11.4;14.0] 0.015 Heart_Rate(beats/minute) 28.7[26.1;33.3] 28.6[26.3;32.3] 28.9[25.9;34.5] 0.141 MAP(mmHg) 81.4[73.4;91.4] 79.0[72.4;87.3] 84.3[74.8;95.5] < 0.001 Resp Rate (beats/minute) 18.7[16.8;21.4] 18.6[16.4;20.8] 19.0[17.0;22.0] < 0.001 Temperature(℃) 36.8[36.7;37.1] 36.9[36.7;37.1] 36.8[36.7;37.1] 0.260 Spo2(%) 97.8[96.5;98.8] 98.3[97.0;99.1] 97.3[96.2;98.5] < 0.001 Ventilation 556(41.2%) 212(31.4%) 344(51.0%) < 0.001 Hemopurification 167(12.4%) 66(9.76%) 101(15.0%) 0.005 ACEI 326(24.1%) 117(17.3%) 209(31.0%) < 0.001 ARB 118(8.73%) 18(2.66%) 100(14.8%) < 0.001 CCB 205(15.2%) 64(9.47%) 141(20.9%) < 0.001 Table 1 summarizes the characteristics of the two groups of patients. SOFA: Sequential Organ Failure Assessment; WBC: White Blood Cell; BUN: Blood Urea Nitrogen; INR: International Normalized Ratio; PT: Prothrombin Time; MAP: Mean Arterial Pressure; ACEI: Angiotensin-Converting Enzyme Inhibitor; ARB: Angiotensin II Receptor Blocker; CCB: Calcium Channel Blocker 2. Outcome analysis We assessed 30-, 60-, and 90-day all-cause mortality by constructing Kaplan–Meier survival curves and comparing groups using the log-rank test. As shown in Fig. 3, survival rates at all three time points were significantly higher in the low-ePWV group than in the high-ePWV group (P < 0.0001). 3. The ePWV is an independen trisk factor for 30-day All-Cause mortality To further explore the relationship between ePWV and patient outcomes, we conducted both univariate and multivariate Cox regression analyses. Initially, univariate analysis was used to identify potential risk factors. The unadjusted model demonstrated a significant association between ePWV and 30-day all-cause mortality (hazard ratio [HR], 2.12; 95% confidence interval [CI], 1.59–2.82; P < 0.001) (Table 2). Variables with P < 0.05 in the univariate analysis, along with clinically relevant factors based on prior experience, were included in the multivariate model. After adjusting for ePWV, age, SOFA score, SAPS II score, history of myocardial infarction, respiratory rate, temperature, sepsis, and hemopurification, ePWV remained independently associated with 30-day mortality (adjusted HR, 1.76; 95% CI, 1.30–2.39; P < 0.001) (Table 2). Table 2 Univariate and multivariate COX regression analysis for AP within 30days Variable Univariate Cox regression Multivariate Cox regression Hazard Ratio (95% CI) p-value Hazard Ratio (95% CI) p-value ePWV 2.12 (1.59–2.82) < 0.001 1.34 (1.23–1.45) < 0.001 Gender 1.27 (0.84–1.91) 0.26 Race 0.45 (0.33–0.62) < 0.001 0.59 (0.44–0.81) < 0.001 Age 1.06 (1.04–1.07) < 0.001 SOFA 1.33 (1.28–1.39) < 0.001 1.28 (1.21–1.35) < 0.001 SAPS-II 1.08 (1.07–1.09) < 0.001 Myocardial Infarct 3.03 (2.00–4.61) < 0.001 Congestive Heart Failure 2.57 (1.68–3.92) < 0.001 Peripheral Vascular Disease 1.46 (0.76–2.82) 0.26 Cerebrovascular Disease 4.02 (2.52–6.40) < 0.001 Dementia 2.99 (1.38–6.46) 0.005 Chronic Pulmonary Disease 1.40 (0.85–2.32) 0.19 Rheumatic Disease 0.51 (0.07–3.69) 0.51 Peptic Ulcer Disease 1.34 (0.42–4.24) 0.61 Mild Liver Disease 1.48 (0.80–2.71) 0.21 Paraplegia 2.63 (1.07–6.48) 0.04 Renal Disease 2.02 (1.34–3.04) < 0.001 DM 1.14 (0.72–1.79) 0.58 Hypertension 1.01 (0.66–1.54) 0.97 Coronary Heart Disease 3.23 (2.07–5.03) < 0.001 1.43 (0.89–2.27) 0.136 Hematocrit 0.98 (0.94–1.01) 0.13 Hemoglobin 0.87 (0.79–0.95) 0.003 Platelets 1.00 (1.00–1.00) 0.03 WBC 1.05 (1.02–1.07) < 0.001 Aniongap 1.01 (0.98–1.04) 0.63 Bicarbonate 1.01 (0.98–1.05) 0.48 Chloride 0.88 (0.70–1.09) 0.24 Creatinine 1.01 (0.99–1.04) 0.33 Glucose 1.08 (1.02–1.14) 0.01 Sodium 1.00 (1.00–1.00) 0.04 Potassium 1.05 (1.02–1.07) < 0.001 BUN 1.09 (0.88–1.34) 0.43 INR 1.02 (1.01–1.03) < 0.001 PT 1.30 (1.11–1.53) 0.001 Heart Rate 0.99 (0.97–1.00) 0.09 MBP 0.95 (0.94–0.97) < 0.001 Resp Rate 1.13 (1.08–1.18) < 0.001 Temperature 0.62 (0.41–0.94) 0.02 Spo2 0.80 (0.74–0.86) < 0.001 Hemopurification 3.54 (2.28–5.49) < 0.001 1.53 (0.95–2.46) 0.083 ventilation 7.86 (4.52–13.70) < 0.001 1.94 (1.04–3.62) 0.036 acei 1.50 (1.11–2.03) 0.008 arb 2.16 (0.89–5.26) 0.09 ccb 3.08 (1.37–6.95) 0.007 4. The restricted cubic spline curves for the the ePWV value and 30 day all-cause mortality Restricted cubic spline (RCS) analysis (Fig. 3) was used to further characterize the non-linear relationship between ePWV and 30-day all-cause mortality. Both the unadjusted model (Fig. 3A) and the model adjusted for age, SOFA score, mechanical ventilation, and hemopurification (Fig. 3B) demonstrated an L-shaped association (P overall 0.05). 5. Subgroup analyses To assess the relationship between ePWV and 30-day all-cause mortality in SAP patients, we conducted subgroup analyses (Fig. 4). The results showed consistent trends across all subgroups: in multiple SAP patient strata, the high-ePWV group had higher all-cause mortality. No significant interactions were observed, indicating that the prognostic value of ePWV for mortality risk is stable across different subpopulations. Discussion Our study evaluated the relationship between ePWV and prognosis in AP patients admitted to the ICU. We extracted data on 931 ICU patients diagnosed with SAP from the MIMIC database and collected comprehensive clinical information for analysis. Our findings indicate that ePWV is significantly associated with 30-, 60-, and 90-day mortality in SAP patients, is an independent risk factor for 30-day mortality in Cox regression analysis, and shows a consistent trend across all subgroup analyses. These results suggest that ePWV may serve as an important prognostic indicator in AP and highlight the association between arterial stiffness and clinical outcomes in this population. Arterial stiffness is a common comorbidity in the elderly and is closely associated with atherosclerotic plaque formation. Its primary etiologies include metabolic disorders such as hyperlipidemia and diabetes. Stiffening of the arterial wall increases systolic blood pressure (SBP) while decreasing diastolic blood pressure (DBP); the loss of Windkessel buffering capacity promotes endothelial injury and plaque formation, positioning arterial stiffness as a central factor in the pathogenesis of cardiovascular events such as coronary artery disease, ischemic stroke, and abdominal aortic aneurysm. Pulse wave velocity (PWV) is considered the gold-standard measure of aortic stiffness and serves as a surrogate marker of vascular aging, providing more direct information than blood pressure or age alone[ 11 ]. The most commonly used measurement, carotid-femoral PWV (cfPWV), is defined by the European Society of Cardiology as > 10 m/s as indicative of target-organ damage and is minimally influenced by antihypertensive therapy[ 12 ]. However, both cfPWV and MRI-based PWV require specialized equipment, limiting their clinical applicability. ePWV, derived from age and mean arterial pressure, has demonstrated predictive accuracy comparable to that of cfPWV[ 13 ]. In general populations, ePWV is strongly correlated with vascular aging and stiffness; a large cohort study of 33,930 U.S. adults reported an approximately 50% increase in all-cause and cardiovascular mortality per unit increase in ePWV[ 14 ]. Beyond cardiovascular disease, elevated ePWV has been identified as a risk factor for poor prognosis in hypertension[ 15 ]and cerebrovascular disease[ 16 ]. Although fewer studies have examined ePWV in critically ill patients, MIMIC-based research has linked elevated ePWV with acute kidney injury (AKI) both overall[ 17 ] and after cardiac surgery[ 18 , 19 ], as well as with worse outcomes in ischemic stroke[ 20 ] and aneurysmal subarachnoid hemorrhage[ 21 ]. Research on the relationship between arterial stiffness and acute pancreatitis remains limited, and to date, no studies have specifically investigated PWV or ePWV in the context of acute pancreatitis, leaving their association uncertain. Endothelial injury—often considered the initiating event in atherosclerosis—can result from chronic hypertension or hyperglycemia. Acute pancreatitis frequently triggers immune activation and the release of inflammatory cytokines, which also damage endothelial cells and contribute to arterial stiffening[ 21 ]. Conversely, hyperlipidemia, a common cause of acute pancreatitis, is itself a major risk factor for atherosclerosis. Chronic arterial stiffening may lead to impaired pancreatic perfusion, thereby promoting the development of pancreatitis. These observations suggest a potential bidirectional link between arterial stiffness and acute pancreatitis.Our study further demonstrates that elevated ePWV is associated with worse outcomes. Subgroup analysis indicated a potential interaction with mechanical ventilation, which may reflect the link between increased ePWV and impaired cardiopulmonary function, thus increasing the likelihood of requiring ventilatory support. This is the first study to explore the association between ePWV levels and prognosis in patients with AP, suggesting that ePWV may have predictive value for both short- and long-term outcomes in this population. However, several limitations should be acknowledged. First, the study is a single-center retrospective analysis in which residual confounding cannot be fully excluded, thereby precluding definitive causal conclusions. These factors may influence the accuracy of our findings; future validation in more diverse, multicenter cohorts is necessary to enhance generalizability. Prospective studies are also warranted to address these limitations. Second, although the ePWV formula has been validated in various clinical settings, it remains an estimated parameter and may be subject to unknown measurement errors or influencing factors, which could impact the reliability of our conclusions. Conclusion Our findings confirm that ePWV may serve as a simple, readily obtainable biomarker for predicting mortality risk in AP patients and offers robust prognostic value. By incorporating ePWV into clinical assessments, clinicians may enhance risk stratification and implement early, proactive interventions to improve patient outcomes. Declarations Ethics approval and consent to participate No ethics approval was needed for this study as it was conducted on publicly available material and no individual can be identified using the data in this study. Consent for publication Not applicable Availability of data and materials Publicly available datasets were analyzed in this study. All the data available in our articles has been saved inthe MIMIC-IV database (version 3.1; https://mimic.mit.edu/) . Author contributions XH .T designed research; YX.Z wrote the main manuscript text and all figures; XT.L collected the data; LP.Y analyzed and revised the paper . All authors reviewed the manuscript. Acknowledgments The manuscript was linguistically refined using ChatGPT , an AI tool developed by OpenAI, to ensure readability. Conflict of interest The authors declare no competing interests. Funding and Financial disclosure Not applicable References Wang J, Li H, Luo H, Shi R, Chen S, Hu J, Luo H, Yang P, Cai X, Wang Y et al : Association between serum creatinine to albumin ratio and short- and long-term all-cause mortality in patients with acute pancreatitis admitted to the intensive care unit: a retrospective analysis based on the MIMIC-IV database . Frontiers in immunology 2024, 15 :1373371. Ranson JH, Turner JW, Roses DF, Rifkind KM, Spencer FC: Respiratory complications in acute pancreatitis . Annals of surgery 1974, 179 (5):557-566. Bozorgi F, Hashemi SA, Jahanian F, Baktash K: Investigating the prognostic power of Bedside Index for Severity in Acute Pancreatitis (BISAP) score . Caspian journal of internal medicine 2025, 16 (2):297-304. Bateman RM, Sharpe MD, Jagger JE, Ellis CG, Solé-Violán J, López-Rodríguez M, Herrera-Ramos E, Ruíz-Hernández J, Borderías L, Horcajada J et al : 36th International Symposium on Intensive Care and Emergency Medicine : Brussels, Belgium. 15-18 March 2016 . Critical care (London, England) 2016, 20 (Suppl 2):94. Balthazar EJ, Robinson DL, Megibow AJ, Ranson JH: Acute pancreatitis: value of CT in establishing prognosis . Radiology 1990, 174 (2):331-336. Rosso D, Carnazzo G, Giarelli L, Motta L, Maugeri D: Atherosclerosis and pancreatic damage . Archives of gerontology and geriatrics 2001, 32 (2):95-100. Szentesi A, Párniczky A, Vincze Á, Bajor J, Gódi S, Sarlós P, Gede N, Izbéki F, Halász A, Márta K et al : Multiple Hits in Acute Pancreatitis: Components of Metabolic Syndrome Synergize Each Other's Deteriorating Effects . Frontiers in physiology 2019, 10 :1202. van Hout MJ, Dekkers IA, Lin L, Westenberg JJ, Schalij MJ, Jukema JW, Widya RL, Boone SC, de Mutsert R, Rosendaal FR et al : Estimated pulse wave velocity (ePWV) as a potential gatekeeper for MRI-assessed PWV: a linear and deep neural network based approach in 2254 participants of the Netherlands Epidemiology of Obesity study . The international journal of cardiovascular imaging 2022, 38 (1):183-193. Prelević V, Blagus L, Bošnjak V, Radunović D, Marinović Glavić M, Premužić V, Kos J, Pećin I, Željković Vrkić T, Domislović M et al : Estimated Pulse Wave Velocity and All-Cause and Cardiovascular Mortality in the General Population . Journal of clinical medicine 2024, 13 (12). Johnson AEW, Bulgarelli L, Shen L, Gayles A, Shammout A, Horng S, Pollard TJ, Hao S, Moody B, Gow B et al : MIMIC-IV, a freely accessible electronic health record dataset . Scientific data 2023, 10 (1):1. Heffernan KS, Stoner L, London AS, Augustine JA, Lefferts WK: Estimated pulse wave velocity as a measure of vascular aging . PloS one 2023, 18 (1):e0280896. Townsend RR, Wilkinson IB, Schiffrin EL, Avolio AP, Chirinos JA, Cockcroft JR, Heffernan KS, Lakatta EG, McEniery CM, Mitchell GF et al : Recommendations for Improving and Standardizing Vascular Research on Arterial Stiffness: A Scientific Statement From the American Heart Association . Hypertension (Dallas, Tex : 1979) 2015, 66 (3):698-722. Greve SV, Blicher MK, Kruger R, Sehestedt T, Gram-Kampmann E, Rasmussen S, Vishram JK, Boutouyrie P, Laurent S, Olsen MH: Estimated carotid-femoral pulse wave velocity has similar predictive value as measured carotid-femoral pulse wave velocity . Journal of hypertension 2016, 34 (7):1279-1289. Cheng W, Kong F, Pan H, Luan S, Yang S, Chen S: Superior predictive value of estimated pulse wave velocity for all-cause and cardiovascular disease mortality risk in U.S. general adults . BMC public health 2024, 24 (1):600. Cheng W, Xu W, Luan S, Wen G, Kong F: Predictive value of estimated pulse wave velocity with all-cause and cause-specific mortality in the hypertensive population: the National Health and Nutrition Examination Surveys 1999-2014 . Journal of hypertension 2023, 41 (8):1313-1322. Huang H, Bu X, Pan H, Yang S, Cheng W, Shubhra QTH, Ma N: Estimated pulse wave velocity is associated with all-cause and cardio-cerebrovascular disease mortality in stroke population: Results from NHANES (2003-2014) . Frontiers in cardiovascular medicine 2023, 10 :1140160. Wei L, Cui X, Lv Y, Zhang F, Wu J: The relationship between estimated pulse wave velocity and 28-day mortality in patients with sA-AKI: a retrospective cohort analysis of the MIMIC-IV database . Renal failure 2025, 47 (1):2507162. Wei L, Liu F, Lv Y, Wu J: The relationship between estimated pulse wave velocity and 28-day mortality in patients with acute kidney injury combined with congestive heart failure: a retrospective cohort analysis of the MIMIC-IV database . Renal failure 2025, 47 (1):2506831. Yang X, Zhang L, Wei H, Zhang F, Yang H, Shi J: Estimated pulse wave velocity and the risk of acute kidney injury in patients undergoing coronary revascularization: a retrospective cohort study from MIMIC-IV . Renal failure 2025, 47 (1):2532859. Zhang Y, Cai P, Wu Y, Yu Y, Chen Z, Wang G, Zhang M, Zheng W: Association between estimated pulse wave velocity and mortality risk in patients with acute ischemic stroke . Scientific reports 2025, 15 (1):22237. Li J, Zhang M, Ye B, Lu M, Liao G: Association between estimation of pulse wave velocity and all-cause mortality in critically ill patients with non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database . Frontiers in neurology 2024, 15 :1451116. Additional Declarations No competing interests reported. Supplementary Files Stable1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 May, 2026 Reviews received at journal 03 May, 2026 Reviewers agreed at journal 25 Apr, 2026 Reviews received at journal 25 Dec, 2025 Reviewers agreed at journal 05 Dec, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers invited by journal 14 Sep, 2025 Editor invited by journal 19 Aug, 2025 Editor assigned by journal 18 Aug, 2025 Submission checks completed at journal 18 Aug, 2025 First submitted to journal 17 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7393160","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517457480,"identity":"99a76cbb-a8df-4e8b-a64b-f2369fb42550","order_by":0,"name":"Yuxiang Zhai","email":"","orcid":"","institution":"Yuhuangding Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuxiang","middleName":"","lastName":"Zhai","suffix":""},{"id":517457481,"identity":"b36ec55a-138c-4854-b57d-154dab1736b0","order_by":1,"name":"Xiangtian Liu","email":"","orcid":"","institution":"Yuhuangding Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiangtian","middleName":"","lastName":"Liu","suffix":""},{"id":517457482,"identity":"1bef0ec8-0332-4735-841d-e57a002f6eb0","order_by":2,"name":"Xinghan Tian","email":"","orcid":"","institution":"Yuhuangding Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xinghan","middleName":"","lastName":"Tian","suffix":""},{"id":517457483,"identity":"87216805-171f-48a4-91e4-67dbb513259a","order_by":3,"name":"Liping Ye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBAC+/7G9g8JP/4zs7E3EKnFQOJwG8PHHmZ2Pp4DxGphSG9jnMHGzC8nkUCkFnOGg22PeXjYpNkkH2+8wVBjE01Qi2VzY7sxjwWPMZt0WrEFw7G03AaCeg4cbJDm4ZFIZpPOMZNgbDhMjJZEoBY2g/o2yTNEajE4kNgmOYMtgZlNgodILZIzDjYbfOw5wMzGA/RLAjF+4edvf/gg4ccBZvn2wxtvfKixIcIvyI4kOmqQtJCqYxSMglEwCkYGAAA4Ozy2OzqQMwAAAABJRU5ErkJggg==","orcid":"","institution":"Yuhuangding Hospital","correspondingAuthor":true,"prefix":"","firstName":"Liping","middleName":"","lastName":"Ye","suffix":""}],"badges":[],"createdAt":"2025-08-17 15:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7393160/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7393160/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91960723,"identity":"fa7e5517-b49b-4acd-a815-5a918345ec23","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":674544,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.docx","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/cf093c5efc8e40d64b7e7d84.docx"},{"id":91960727,"identity":"b9fb629e-3d02-47ba-80e4-e99c19096667","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":520364,"visible":true,"origin":"","legend":"","description":"","filename":"sapePWVBMCG.docx","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/76418cff65b14555a0136942.docx"},{"id":91960722,"identity":"11323b5d-8842-4e95-be7a-7528c2e0aae3","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"json","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6380,"visible":true,"origin":"","legend":"","description":"","filename":"449d75efd6c941c6a4b45fa98db558b2.json","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/b0bb05d016f91de196d66ec9.json"},{"id":91959750,"identity":"e4daac96-7c13-400d-8578-7d7f97cfe8f8","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12961,"visible":true,"origin":"","legend":"","description":"","filename":"Stable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/e042806df1cb4de199406cb4.docx"},{"id":91962627,"identity":"057dfbcf-026e-476e-ac7f-04f94d668225","added_by":"auto","created_at":"2025-09-23 07:56:16","extension":"xml","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108523,"visible":true,"origin":"","legend":"","description":"","filename":"449d75efd6c941c6a4b45fa98db558b21enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/61c3ebc49f90e106fc0932d8.xml"},{"id":91960724,"identity":"369710c0-3b12-4475-b8e5-8ec786a41baf","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":42000,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/0ed4b16ec41a376d6f1f1fcc.png"},{"id":91959765,"identity":"044b0a09-ccac-42d6-8606-9cfabe0af595","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1315930,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/725bcf5f63b94f7042dae44d.jpeg"},{"id":91960726,"identity":"3b1c2701-a61d-4c53-ae48-7209eb52d020","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32270,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/a62c0e23f0bc433f2d929a33.png"},{"id":91959764,"identity":"d7142fb1-24b7-466e-9a10-950ff480fede","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":226861,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/7b040d6b80991560be93b53f.png"},{"id":91959751,"identity":"e82526df-0d98-4761-ab65-55de27e3dd70","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":42000,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/b5dcfda41254462ac04c6c43.png"},{"id":91960730,"identity":"d95b7158-bc56-4d73-bcc4-999e189232d8","added_by":"auto","created_at":"2025-09-23 07:48:17","extension":"jpeg","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3891144,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/0746248d0e1776000cf0a964.jpeg"},{"id":91962628,"identity":"3a885767-3b4a-4d29-8740-38ff0a148983","added_by":"auto","created_at":"2025-09-23 07:56:16","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32270,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/0b6adb23858d4561c1f6d6f9.png"},{"id":91959762,"identity":"25c01272-4f98-451d-9b35-cd0956fa2ee0","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":248714,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/8227c8b8f836e0db177810d9.png"},{"id":91959766,"identity":"ac262bc5-6cee-4029-8ec2-f56b139c5ec6","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13068,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/3dd5e7b9587b1939bfdee768.png"},{"id":91959757,"identity":"19988046-e7ae-47e1-a5e2-74879db32672","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16769,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/33276f8a18c5b05ba2e0dd15.png"},{"id":91959759,"identity":"78d44fea-5df0-469c-afd8-0d943401bb77","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20760,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/b5b6a2c985eb470925397809.png"},{"id":91960729,"identity":"d295a36b-095c-4978-83b3-2590fa2b77e8","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47087,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/0b3340dcb3070fde68e69728.png"},{"id":91959768,"identity":"5d08d575-a312-4493-ae44-1368f3e45b4f","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13068,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/aa592737aed44384433470eb.png"},{"id":91959771,"identity":"fc9427d9-e19c-46c3-837c-bc7c802cff0e","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":264136,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/e5c291b3d94f0ce659aab833.png"},{"id":91960731,"identity":"ac5d85f3-0bc1-40b6-99ba-4169d44375ad","added_by":"auto","created_at":"2025-09-23 07:48:17","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20760,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/ebbd05ccc852cfa6a539b49e.png"},{"id":91959767,"identity":"bcfd3f51-4568-443f-b62d-2e560cfb45a0","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51855,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/ab01e37c45aebdbbc4955d3c.png"},{"id":91959774,"identity":"ed35ef58-7f35-4fea-9d3d-36b5009c58e0","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"xml","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":109311,"visible":true,"origin":"","legend":"","description":"","filename":"449d75efd6c941c6a4b45fa98db558b21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/3dba6a079634cfc4b7a7a129.xml"},{"id":91959773,"identity":"1ba5f92a-0e87-4086-9f7a-ba1c4982bfa8","added_by":"auto","created_at":"2025-09-23 07:40:17","extension":"html","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114799,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/2f989cca100f9bdeff60ed15.html"},{"id":91960721,"identity":"84e815b5-6fbc-408d-b32e-f8f4f36c93c5","added_by":"auto","created_at":"2025-09-23 07:48:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":42000,"visible":true,"origin":"","legend":"\u003cp\u003eAP patient screening flowchart\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/6b548b8308021afa7ec8911b.png"},{"id":91959748,"identity":"82872c7e-5a64-4d66-8d3f-d3b4828c6f29","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77971,"visible":true,"origin":"","legend":"\u003cp\u003eThe Kaplan–Meier survival curves of all-cause mortality in 30-day, 60-day and 90-day. (A)30-day (B)60-day(C)90-day\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/90947ec99d9dc718516a49e3.png"},{"id":91959745,"identity":"ca719737-fe1b-4bab-94d4-babb8d844bad","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":32270,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline analysis showing the relationship of ePWV with 30day mortality. (A) Unadjusted RCS of ePWV with 30day mortality (B) Multivariable RCS.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/30c8aaa14f64b7cf4ffb16ef.png"},{"id":91959755,"identity":"54c3baaf-2d8a-4592-a6bf-0151def8c813","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":226861,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of hazard ratios for the primary endpoint in different subgroups.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/a79815688e1575793d0470e3.png"},{"id":91963382,"identity":"05cfcd02-337c-4ab5-bc5f-dc1013bf8958","added_by":"auto","created_at":"2025-09-23 08:04:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2320509,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/4a5abf3f-d299-4b66-a661-6a46f97887c5.pdf"},{"id":91959746,"identity":"c400bcc7-7c6c-4398-b25c-1082a661af30","added_by":"auto","created_at":"2025-09-23 07:40:16","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":12961,"visible":true,"origin":"","legend":"","description":"","filename":"Stable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7393160/v1/25f505d834b9f2d5f4b0013e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Estimated Pulse Wave Velocity and 30 Day All-Cause Mortality in Patients with Acute Pancreatitis: a Retrospective Cohort Analysis of the MIMIC-IV Database","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute pancreatitis (AP) is a common disorder of the digestive system, most frequently precipitated by gallstones, excessive alcohol consumption, or hypertriglyceridemia. Approximately 20% of AP cases progress to moderate or severe disease\u0026mdash;characterized by pancreatic and peripancreatic necrosis and, in some instances, multi-organ failure\u0026mdash;with mortality rates as high as 30%[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Early assessment of disease severity and prompt intervention are therefore critical. Widely used clinical scoring systems for AP severity include the Ranson criteria, which integrate multiple clinical and laboratory variables[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]; the Bedside Index for Severity in Acute Pancreatitis (BISAP) score[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]; the modified Marshall scoring system for organ dysfunction[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; and the Balthazar grading system based on computed tomography findings[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, these tools require collection of multiple parameters and do not provide a single rapid predictor of severity.\u003c/p\u003e\u003cp\u003eArteriosclerosis, primarily in the form of atherosclerosis characterized by arterial plaque formation, may contribute to chronic pancreatic injury by reducing islet perfusion and inducing hypoxia. This process can lead to progressive β-cell dysfunction, structural alterations of the islets, β-cell loss, and diminished insulin production[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This process fosters dyslipidemia, obesity, and hypertension, creating a vicious cycle that exacerbates arterial stiffening. Advanced age, obesity, diabetes mellitus, and hypertriglyceridemia are established atherosclerosis risk factors and have also been closely associated with AP onset and severity[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Pulse wave velocity (PWV) is a validated measure of arterial stiffness and vascular elasticity, but its clinical use is constrained by the need for specialized equipment. An equation combining patient age and blood pressure to estimate PWV (ePWV) has been validated as a reliable surrogate for measured PWV[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. ePWV has shown prognostic utility across various conditions, particularly cardiovascular diseases[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; however, its prognostic significance in AP remains unexplored. Accordingly, this study evaluates the predictive value of ePWV in patients with AP using a large intensive care database.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDataextraction\u003c/h2\u003e\u003cp\u003eThis study used data from MIMIC-IV version 3.1, a publicly available, de-identified dataset containing detailed information on ICU admissions at Beth Israel Deaconess Medical Center in Boston, USA[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Because only anonymized, third-party data were used, the study was exempt from institutional review board approval. Xiangtian Liu (certification ID: 65112747) was granted access to the MIMIC-IV database.\u003c/p\u003e\u003cp\u003eData extraction was performed using structured query language (SQL) in PostgreSQL (version 15.2.1) and Navicat Premium (version 15). The SQL scripts were obtained from the official GitHub repository (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/MIT-LCP/mimic-iv\u003c/span\u003e\u003cspan address=\"https://github.com/MIT-LCP/mimic-iv\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Acute pancreatitis cases were identified in MIMIC-IV by International Classification of Diseases, Ninth and Tenth Revisions (ICD-9 and ICD-10) codes for acute pancreatitis. Exclusion criteria were age\u0026thinsp;\u0026lt;\u0026thinsp;18 years, ICU length of stay\u0026thinsp;\u0026lt;\u0026thinsp;24 hours, cirrhosis, end-stage renal disease, malignancy, or non-first ICU admission. Extracted patient variables included: (1)Demographics: age, sex, race; (2)First-day ICU vital signs: temperature, heart rate, blood pressure, and mean arterial pressure; (3)Comorbidities: Charlson Comorbidity Index components (e.g., myocardial infarction, congestive heart failure); (4)Therapies: antihypertensive drugs, hemopurification, mechanical ventilation; (5)Clinical outcomes: hospital length of stay, ICU duration, and survival status at 30, 60, and 90 days ; (6)Laboratory tests: first available values after admission; (7)Severity scores: Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score II (SAPS II)\u003c/p\u003e\u003cp\u003eEstimated pulse wave velocity (ePWV) was calculated using patient age and the average mean arterial pressure (MAP) over the first 24 hours of ICU admission to minimize measurement error. eWPV\u0026thinsp;=\u0026thinsp;9.587 - (0.402 \u0026times; age) + (4.5610 \u0026times; 0.001 \u0026times; age2) - (2.621 \u0026times; 0.00001 \u0026times; age2 \u0026times; MBP) + (3.176 \u0026times; 0.001 \u0026times; age \u0026times; MBP) - (1.832 \u0026times; 0.01 \u0026times; MBP)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis:\u003c/h2\u003e\u003cp\u003eWe assessed the distribution of continuous variables with the Shapiro\u0026ndash;Wilk test. Variables with a normal distribution are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and compared using Student\u0026rsquo;s t-test or one-way ANOVA; non-normally distributed variables are reported as median (interquartile range) and compared using the Wilcoxon rank-sum test. Categorical variables are expressed as n (%) and compared with the chi-square test, continuity-corrected chi-square test, or Fisher\u0026rsquo;s exact test as appropriate.Kaplan\u0026ndash;Meier curves were used to compare 30-day mortality between high- and low-ePWV groups, with the log-rank test assessing significance. Cox proportional-hazards models evaluated the association between ePWV and 30-day mortality. Non-linear relationships were modeled using restricted cubic splines with knots at the 0.25, 0.5, 0.75, and 0.95 quantiles of the ePWV distribution.\u003c/p\u003e\u003cp\u003eAnalyses were performed in R version 4.4.1. Variables with more than 10% missing values were excluded; those with up to 30% missingness were imputed using the missForest package (see Supplementary Table\u0026nbsp;1). Clinically relevant covariates were entered into multivariable models; variables with a variance inflation factor (VIF)\u0026thinsp;\u0026gt;\u0026thinsp;5 were removed to mitigate multicollinearity. Predefined subgroup analyses employed Cox models to assess the association between ePWV and 30-day mortality stratified by age (\u0026lt;\u0026thinsp;65 vs. \u0026ge; 65 years), sex, race, diabetes, hypertension, hemopurification (including RRT and CRRT), and mechanical ventilation.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. Baseline Information and Clinical Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 displays the patient inclusion flowchart. A total of 1,351 patients with severe acute pancreatitis (SAP) who met the diagnostic criteria were initially identified. After applying the exclusion criteria, 1,351 patients remained, with 676 assigned to the low-ePWV group (T1) and 675 to the high-ePWV group (T2).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1 summarizes the baseline characteristics of the two groups of patients. A total of 1,351 eligible AP patients were included, of whom 51.2% were male and 53.3% were White. As an indicator of vascular aging, mean age was significantly lower in the low-ePWV group compared to the high-ePWV group (37.8 vs. 64.3 years; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The high-ePWV group also had significantly longer hospital and ICU stays and a higher in-hospital mortality rate. Regarding severity scores, patients in the high-ePWV group had higher median SOFA scores (4.00 vs. 2.00; P\u0026thinsp;=\u0026thinsp;0.001) and SAPS II scores (35.0 vs. 23.0; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This group also had a higher prevalence of common comorbidities, including hypertension and diabetes, and a greater proportion received corresponding antihypertensive therapies.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSummary the characteristics in AP patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eAll\u003cbr\u003e(n\u0026thinsp;=\u0026thinsp;1351)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eT1\u003cbr\u003e(n\u0026thinsp;=\u0026thinsp;676)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eT2\u003cbr\u003e(n\u0026thinsp;=\u0026thinsp;675)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ep\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eePWV\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e7.49[6.34;8.91]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e6.34[5.87;6.94]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e8.91[8.08;10.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAge(Year)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e51.2[36.0;64.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e37.8 [28.1;47.9]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e64.3[55.1;72.1]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eRace(White)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e720(53.3%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e352(52.1%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e368(54.5%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.485\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSex(Male)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e658(48.7%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e295(43.6%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e363(53.8%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eLength of hospital stay(day)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e5.60[3.46;9.96]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e4.27[2.87;7.54]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e7.04[4.56;12.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eLength of ICU stay(day)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.02[1.48;3.05]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.93[1.41;2.84]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.15[1.54;3.36]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eIn-hospital mortality\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e74(5.48%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e19(2.81%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e55(8.15%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSOFA Score\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.00[2.00;5.00]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.00[1.00;5.00]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e4.00[2.00;6.00]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSAPSII Score\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e28.0[20.0;39.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e23.0[17.0;30.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e35.0[27.0;43.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eMyocardial Infarct\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e248(18.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e56(8.28%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e192(28.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCongestive Heart Failure\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e260(19.2%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e72(10.7%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e188(27.9%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePeripheral Vascular Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e107(7.92%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e31(4.59%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e76(11.3%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCerebrovascular Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e116(8.59%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e26(3.85%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e90(13.3%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eDementia\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e38(2.81%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1(0.15%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e37(5.48%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eChronic Pulmonary_Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e213(15.8%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e87(12.9%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e126(18.7%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.004\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eRheumatic Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e28(2.07%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11(1.63%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e17(2.52%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.338\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eMild Liver Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e125(9.25%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e56(8.28%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e69(10.2%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.256\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePeptic Ulcer_Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e33(2.44%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11(1.63%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e22(3.26%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.077\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eParaplegia\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e31(2.29%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e5(0.74%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e26(3.85%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eRenal Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e429(31.8%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e135(20.0%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e294(43.6%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eDiabetes\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e936(69.3%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e427(63.2%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e509(75.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHypertension\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e480(35.5%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e194(28.7%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e286(42.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCoronary Heart Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e171 (12.7%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e31 (4.59%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e140 (20.7%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHemoglobin_(g/dL)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11.1[9.50;12.6]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11.3[9.70;12.9]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e10.9[9.40;12.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.004\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePlatelets_(K/uL)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e236[181;300]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e245[191;305]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e228[173;294]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.003\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eWBC (K/uL)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11.4[8.10;15.8]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e10.9[7.68;15.9]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e11.7[8.60;15.7]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.054\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAniongap_(mmol/L)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e20.0[16.0;25.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e21.0[16.0;26.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e19.0[16.0;24.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.046\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBicarbonate_(mmol/L)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e17.0[12.0;20.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e15.0[10.0;19.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e18.0[14.0;21.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003elacticdehydrogenase(U/L)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e8.50[8.07;9.00]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e8.30[7.90;8.80]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e8.70[8.30;9.11]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eChloride(mEq/l)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e103[97.0;108]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e104[98.0;109]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e101[97.0;107]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCreatinine_(mg/dl)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.30[0.90;2.20]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.00[0.80;1.70]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.60[1.10;2.60]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGlucose(mg/dL)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e279[192;414]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e262[187;401]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e300[198;429]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.004\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSodium(mmol/L)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e137[133;140]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e137[133;140]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e137[134;141]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.009\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePotassium(mmol/L)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e4.30[3.80;4.80]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e4.20[3.80;4.62]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e4.30[3.80;4.90]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.005\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBUN(mg/dL)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e26.0[14.7;46.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e18.0[11.0;36.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e35.0[22.0;52.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eINR\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.10[1.00;1.20]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.10[1.00;1.20]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.10[1.00;1.30]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePT(seconds)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e12.2[11.4;13.5]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e12.1[11.4;13.2]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e12.3[11.4;14.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.015\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHeart_Rate(beats/minute)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e28.7[26.1;33.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e28.6[26.3;32.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e28.9[25.9;34.5]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.141\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eMAP(mmHg)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e81.4[73.4;91.4]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e79.0[72.4;87.3]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e84.3[74.8;95.5]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eResp Rate (beats/minute)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e18.7[16.8;21.4]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e18.6[16.4;20.8]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e19.0[17.0;22.0]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTemperature(℃)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e36.8[36.7;37.1]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e36.9[36.7;37.1]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e36.8[36.7;37.1]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.260\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSpo2(%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e97.8[96.5;98.8]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e98.3[97.0;99.1]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e97.3[96.2;98.5]\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eVentilation\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e556(41.2%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e212(31.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e344(51.0%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHemopurification\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e167(12.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e66(9.76%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e101(15.0%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.005\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eACEI\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e326(24.1%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e117(17.3%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e209(31.0%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eARB\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e118(8.73%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e18(2.66%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e100(14.8%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCCB\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e205(15.2%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e64(9.47%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e141(20.9%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;1 summarizes the characteristics of the two groups of patients. SOFA: Sequential Organ Failure Assessment; WBC: White Blood Cell; BUN: Blood Urea Nitrogen; INR: International Normalized Ratio; PT: Prothrombin Time; MAP: Mean Arterial Pressure; ACEI: Angiotensin-Converting Enzyme Inhibitor; ARB: Angiotensin II Receptor Blocker; CCB: Calcium Channel Blocker\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Outcome analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe assessed 30-, 60-, and 90-day all-cause mortality by constructing Kaplan\u0026ndash;Meier survival curves and comparing groups using the log-rank test. As shown in Fig. 3, survival rates at all three time points were significantly higher in the low-ePWV group than in the high-ePWV group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. The ePWV is an independen trisk factor for 30-day All-Cause mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further explore the relationship between ePWV and patient outcomes, we conducted both univariate and multivariate Cox regression analyses. Initially, univariate analysis was used to identify potential risk factors. The unadjusted model demonstrated a significant association between ePWV and 30-day all-cause mortality (hazard ratio [HR], 2.12; 95% confidence interval [CI], 1.59\u0026ndash;2.82; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;2). Variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariate analysis, along with clinically relevant factors based on prior experience, were included in the multivariate model. After adjusting for ePWV, age, SOFA score, SAPS II score, history of myocardial infarction, respiratory rate, temperature, sepsis, and hemopurification, ePWV remained independently associated with 30-day mortality (adjusted HR, 1.76; 95% CI, 1.30\u0026ndash;2.39; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;2).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eUnivariate and multivariate COX regression analysis for AP within 30days\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003eVariable\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003eUnivariate Cox regression\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003eMultivariate Cox regression\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eHazard Ratio (95% CI)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ep-value\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eHazard Ratio (95% CI)\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003ep-value\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eePWV\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.12 (1.59\u0026ndash;2.82)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.34 (1.23\u0026ndash;1.45)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGender\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.27 (0.84\u0026ndash;1.91)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eRace\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.45 (0.33\u0026ndash;0.62)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.59 (0.44\u0026ndash;0.81)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAge\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.06 (1.04\u0026ndash;1.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSOFA\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.33 (1.28\u0026ndash;1.39)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.28 (1.21\u0026ndash;1.35)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSAPS-II\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.08 (1.07\u0026ndash;1.09)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eMyocardial Infarct\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.03 (2.00\u0026ndash;4.61)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCongestive Heart Failure\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.57 (1.68\u0026ndash;3.92)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePeripheral Vascular Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.46 (0.76\u0026ndash;2.82)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.26\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCerebrovascular Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e4.02 (2.52\u0026ndash;6.40)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eDementia\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.99 (1.38\u0026ndash;6.46)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.005\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eChronic Pulmonary Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.40 (0.85\u0026ndash;2.32)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eRheumatic Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.51 (0.07\u0026ndash;3.69)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.51\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePeptic Ulcer Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.34 (0.42\u0026ndash;4.24)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eMild Liver Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.48 (0.80\u0026ndash;2.71)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eParaplegia\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.63 (1.07\u0026ndash;6.48)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eRenal Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.02 (1.34\u0026ndash;3.04)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eDM\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.14 (0.72\u0026ndash;1.79)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.58\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHypertension\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.01 (0.66\u0026ndash;1.54)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.97\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCoronary Heart Disease\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.23 (2.07\u0026ndash;5.03)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.43 (0.89\u0026ndash;2.27)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.136\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHematocrit\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.98 (0.94\u0026ndash;1.01)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.13\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHemoglobin\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.87 (0.79\u0026ndash;0.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.003\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePlatelets\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.00 (1.00\u0026ndash;1.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.03\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eWBC\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.05 (1.02\u0026ndash;1.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eAniongap\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.01 (0.98\u0026ndash;1.04)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBicarbonate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.01 (0.98\u0026ndash;1.05)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.48\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eChloride\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.88 (0.70\u0026ndash;1.09)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eCreatinine\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.01 (0.99\u0026ndash;1.04)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eGlucose\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.08 (1.02\u0026ndash;1.14)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.01\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSodium\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.00 (1.00\u0026ndash;1.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePotassium\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.05 (1.02\u0026ndash;1.07)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eBUN\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.09 (0.88\u0026ndash;1.34)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.43\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eINR\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.02 (1.01\u0026ndash;1.03)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ePT\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.30 (1.11\u0026ndash;1.53)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHeart Rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.99 (0.97\u0026ndash;1.00)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eMBP\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.95 (0.94\u0026ndash;0.97)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eResp Rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.13 (1.08\u0026ndash;1.18)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTemperature\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.62 (0.41\u0026ndash;0.94)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eSpo2\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.80 (0.74\u0026ndash;0.86)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eHemopurification\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.54 (2.28\u0026ndash;5.49)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.53 (0.95\u0026ndash;2.46)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.083\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eventilation\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e7.86 (4.52\u0026ndash;13.70)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\u0026lt;\u0026thinsp;0.001\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.94 (1.04\u0026ndash;3.62)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.036\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eacei\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e1.50 (1.11\u0026ndash;2.03)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.008\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003earb\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e2.16 (0.89\u0026ndash;5.26)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eccb\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e3.08 (1.37\u0026ndash;6.95)\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"char\"\u003e0.007\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\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\u003e4. The restricted cubic spline curves for the the ePWV value and 30 day all-cause mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRestricted cubic spline (RCS) analysis (Fig.\u0026nbsp;3) was used to further characterize the non-linear relationship between ePWV and 30-day all-cause mortality. Both the unadjusted model (Fig.\u0026nbsp;3A) and the model adjusted for age, SOFA score, mechanical ventilation, and hemopurification (Fig.\u0026nbsp;3B) demonstrated an L-shaped association (P overall\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting a potential linear component to the relationship (P for nonlinearity\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Subgroup analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the relationship between ePWV and 30-day all-cause mortality in SAP patients, we conducted subgroup analyses (Fig.\u0026nbsp;4). The results showed consistent trends across all subgroups: in multiple SAP patient strata, the high-ePWV group had higher all-cause mortality. No significant interactions were observed, indicating that the prognostic value of ePWV for mortality risk is stable across different subpopulations.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study evaluated the relationship between ePWV and prognosis in AP patients admitted to the ICU. We extracted data on 931 ICU patients diagnosed with SAP from the MIMIC database and collected comprehensive clinical information for analysis. Our findings indicate that ePWV is significantly associated with 30-, 60-, and 90-day mortality in SAP patients, is an independent risk factor for 30-day mortality in Cox regression analysis, and shows a consistent trend across all subgroup analyses. These results suggest that ePWV may serve as an important prognostic indicator in AP and highlight the association between arterial stiffness and clinical outcomes in this population.\u003c/p\u003e\u003cp\u003eArterial stiffness is a common comorbidity in the elderly and is closely associated with atherosclerotic plaque formation. Its primary etiologies include metabolic disorders such as hyperlipidemia and diabetes. Stiffening of the arterial wall increases systolic blood pressure (SBP) while decreasing diastolic blood pressure (DBP); the loss of Windkessel buffering capacity promotes endothelial injury and plaque formation, positioning arterial stiffness as a central factor in the pathogenesis of cardiovascular events such as coronary artery disease, ischemic stroke, and abdominal aortic aneurysm. Pulse wave velocity (PWV) is considered the gold-standard measure of aortic stiffness and serves as a surrogate marker of vascular aging, providing more direct information than blood pressure or age alone[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The most commonly used measurement, carotid-femoral PWV (cfPWV), is defined by the European Society of Cardiology as \u0026gt;\u0026thinsp;10 m/s as indicative of target-organ damage and is minimally influenced by antihypertensive therapy[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, both cfPWV and MRI-based PWV require specialized equipment, limiting their clinical applicability. ePWV, derived from age and mean arterial pressure, has demonstrated predictive accuracy comparable to that of cfPWV[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In general populations, ePWV is strongly correlated with vascular aging and stiffness; a large cohort study of 33,930 U.S. adults reported an approximately 50% increase in all-cause and cardiovascular mortality per unit increase in ePWV[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Beyond cardiovascular disease, elevated ePWV has been identified as a risk factor for poor prognosis in hypertension[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]and cerebrovascular disease[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Although fewer studies have examined ePWV in critically ill patients, MIMIC-based research has linked elevated ePWV with acute kidney injury (AKI) both overall[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and after cardiac surgery[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], as well as with worse outcomes in ischemic stroke[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and aneurysmal subarachnoid hemorrhage[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eResearch on the relationship between arterial stiffness and acute pancreatitis remains limited, and to date, no studies have specifically investigated PWV or ePWV in the context of acute pancreatitis, leaving their association uncertain. Endothelial injury\u0026mdash;often considered the initiating event in atherosclerosis\u0026mdash;can result from chronic hypertension or hyperglycemia. Acute pancreatitis frequently triggers immune activation and the release of inflammatory cytokines, which also damage endothelial cells and contribute to arterial stiffening[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Conversely, hyperlipidemia, a common cause of acute pancreatitis, is itself a major risk factor for atherosclerosis. Chronic arterial stiffening may lead to impaired pancreatic perfusion, thereby promoting the development of pancreatitis. These observations suggest a potential bidirectional link between arterial stiffness and acute pancreatitis.Our study further demonstrates that elevated ePWV is associated with worse outcomes. Subgroup analysis indicated a potential interaction with mechanical ventilation, which may reflect the link between increased ePWV and impaired cardiopulmonary function, thus increasing the likelihood of requiring ventilatory support.\u003c/p\u003e\u003cp\u003eThis is the first study to explore the association between ePWV levels and prognosis in patients with AP, suggesting that ePWV may have predictive value for both short- and long-term outcomes in this population. However, several limitations should be acknowledged. First, the study is a single-center retrospective analysis in which residual confounding cannot be fully excluded, thereby precluding definitive causal conclusions. These factors may influence the accuracy of our findings; future validation in more diverse, multicenter cohorts is necessary to enhance generalizability. Prospective studies are also warranted to address these limitations. Second, although the ePWV formula has been validated in various clinical settings, it remains an estimated parameter and may be subject to unknown measurement errors or influencing factors, which could impact the reliability of our conclusions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings confirm that ePWV may serve as a simple, readily obtainable biomarker for predicting mortality risk in AP patients and offers robust prognostic value. By incorporating ePWV into clinical assessments, clinicians may enhance risk stratification and implement early, proactive interventions to improve patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo ethics approval was needed for this study as it was conducted on publicly available material and no individual can be identified using the data in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. All the data available in our articles has been saved inthe MIMIC-IV database (version 3.1; https://mimic.mit.edu/) .\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXH .T designed research; YX.Z wrote the main manuscript text and all figures; XT.L collected the data; LP.Y analyzed and revised the paper . All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe manuscript was linguistically refined using ChatGPT , an AI tool developed by OpenAI, to ensure readability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eand Financial disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang J, Li H, Luo H, Shi R, Chen S, Hu J, Luo H, Yang P, Cai X, Wang Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAssociation between serum creatinine to albumin ratio and short- and long-term all-cause mortality in patients with acute pancreatitis admitted to the intensive care unit: a retrospective analysis based on the MIMIC-IV database\u003c/strong\u003e. \u003cem\u003eFrontiers in immunology \u003c/em\u003e2024, \u003cstrong\u003e15\u003c/strong\u003e:1373371.\u003c/li\u003e\n\u003cli\u003eRanson JH, Turner JW, Roses DF, Rifkind KM, Spencer FC: \u003cstrong\u003eRespiratory complications in acute pancreatitis\u003c/strong\u003e. \u003cem\u003eAnnals of surgery \u003c/em\u003e1974, \u003cstrong\u003e179\u003c/strong\u003e(5):557-566.\u003c/li\u003e\n\u003cli\u003eBozorgi F, Hashemi SA, Jahanian F, Baktash K: \u003cstrong\u003eInvestigating the prognostic power of Bedside Index for Severity in Acute Pancreatitis (BISAP) score\u003c/strong\u003e. \u003cem\u003eCaspian journal of internal medicine \u003c/em\u003e2025, \u003cstrong\u003e16\u003c/strong\u003e(2):297-304.\u003c/li\u003e\n\u003cli\u003eBateman RM, Sharpe MD, Jagger JE, Ellis CG, Sol\u0026eacute;-Viol\u0026aacute;n J, L\u0026oacute;pez-Rodr\u0026iacute;guez M, Herrera-Ramos E, Ru\u0026iacute;z-Hern\u0026aacute;ndez J, Border\u0026iacute;as L, Horcajada J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003e36th International Symposium on Intensive Care and Emergency Medicine : Brussels, Belgium. 15-18 March 2016\u003c/strong\u003e. \u003cem\u003eCritical care (London, England) \u003c/em\u003e2016, \u003cstrong\u003e20\u003c/strong\u003e(Suppl 2):94.\u003c/li\u003e\n\u003cli\u003eBalthazar EJ, Robinson DL, Megibow AJ, Ranson JH: \u003cstrong\u003eAcute pancreatitis: value of CT in establishing prognosis\u003c/strong\u003e. \u003cem\u003eRadiology \u003c/em\u003e1990, \u003cstrong\u003e174\u003c/strong\u003e(2):331-336.\u003c/li\u003e\n\u003cli\u003eRosso D, Carnazzo G, Giarelli L, Motta L, Maugeri D: \u003cstrong\u003eAtherosclerosis and pancreatic damage\u003c/strong\u003e. \u003cem\u003eArchives of gerontology and geriatrics \u003c/em\u003e2001, \u003cstrong\u003e32\u003c/strong\u003e(2):95-100.\u003c/li\u003e\n\u003cli\u003eSzentesi A, P\u0026aacute;rniczky A, Vincze \u0026Aacute;, Bajor J, G\u0026oacute;di S, Sarl\u0026oacute;s P, Gede N, Izb\u0026eacute;ki F, Hal\u0026aacute;sz A, M\u0026aacute;rta K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eMultiple Hits in Acute Pancreatitis: Components of Metabolic Syndrome Synergize Each Other\u0026apos;s Deteriorating Effects\u003c/strong\u003e. \u003cem\u003eFrontiers in physiology \u003c/em\u003e2019, \u003cstrong\u003e10\u003c/strong\u003e:1202.\u003c/li\u003e\n\u003cli\u003evan Hout MJ, Dekkers IA, Lin L, Westenberg JJ, Schalij MJ, Jukema JW, Widya RL, Boone SC, de Mutsert R, Rosendaal FR\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEstimated pulse wave velocity (ePWV) as a potential gatekeeper for MRI-assessed PWV: a linear and deep neural network based approach in 2254 participants of the Netherlands Epidemiology of Obesity study\u003c/strong\u003e. \u003cem\u003eThe international journal of cardiovascular imaging \u003c/em\u003e2022, \u003cstrong\u003e38\u003c/strong\u003e(1):183-193.\u003c/li\u003e\n\u003cli\u003ePrelević V, Blagus L, Bo\u0026scaron;njak V, Radunović D, Marinović Glavić M, Premužić V, Kos J, Pećin I, Željković Vrkić T, Domislović M\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEstimated Pulse Wave Velocity and All-Cause and Cardiovascular Mortality in the General Population\u003c/strong\u003e. \u003cem\u003eJournal of clinical medicine \u003c/em\u003e2024, \u003cstrong\u003e13\u003c/strong\u003e(12).\u003c/li\u003e\n\u003cli\u003eJohnson AEW, Bulgarelli L, Shen L, Gayles A, Shammout A, Horng S, Pollard TJ, Hao S, Moody B, Gow B\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eMIMIC-IV, a freely accessible electronic health record dataset\u003c/strong\u003e. \u003cem\u003eScientific data \u003c/em\u003e2023, \u003cstrong\u003e10\u003c/strong\u003e(1):1.\u003c/li\u003e\n\u003cli\u003eHeffernan KS, Stoner L, London AS, Augustine JA, Lefferts WK: \u003cstrong\u003eEstimated pulse wave velocity as a measure of vascular aging\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2023, \u003cstrong\u003e18\u003c/strong\u003e(1):e0280896.\u003c/li\u003e\n\u003cli\u003eTownsend RR, Wilkinson IB, Schiffrin EL, Avolio AP, Chirinos JA, Cockcroft JR, Heffernan KS, Lakatta EG, McEniery CM, Mitchell GF\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eRecommendations for Improving and Standardizing Vascular Research on Arterial Stiffness: A Scientific Statement From the American Heart Association\u003c/strong\u003e. \u003cem\u003eHypertension (Dallas, Tex : 1979) \u003c/em\u003e2015, \u003cstrong\u003e66\u003c/strong\u003e(3):698-722.\u003c/li\u003e\n\u003cli\u003eGreve SV, Blicher MK, Kruger R, Sehestedt T, Gram-Kampmann E, Rasmussen S, Vishram JK, Boutouyrie P, Laurent S, Olsen MH: \u003cstrong\u003eEstimated carotid-femoral pulse wave velocity has similar predictive value as measured carotid-femoral pulse wave velocity\u003c/strong\u003e. \u003cem\u003eJournal of hypertension \u003c/em\u003e2016, \u003cstrong\u003e34\u003c/strong\u003e(7):1279-1289.\u003c/li\u003e\n\u003cli\u003eCheng W, Kong F, Pan H, Luan S, Yang S, Chen S: \u003cstrong\u003eSuperior predictive value of estimated pulse wave velocity for all-cause and cardiovascular disease mortality risk in U.S. general adults\u003c/strong\u003e. \u003cem\u003eBMC public health \u003c/em\u003e2024, \u003cstrong\u003e24\u003c/strong\u003e(1):600.\u003c/li\u003e\n\u003cli\u003eCheng W, Xu W, Luan S, Wen G, Kong F: \u003cstrong\u003ePredictive value of estimated pulse wave velocity with all-cause and cause-specific mortality in the hypertensive population: the National Health and Nutrition Examination Surveys 1999-2014\u003c/strong\u003e. \u003cem\u003eJournal of hypertension \u003c/em\u003e2023, \u003cstrong\u003e41\u003c/strong\u003e(8):1313-1322.\u003c/li\u003e\n\u003cli\u003eHuang H, Bu X, Pan H, Yang S, Cheng W, Shubhra QTH, Ma N: \u003cstrong\u003eEstimated pulse wave velocity is associated with all-cause and cardio-cerebrovascular disease mortality in stroke population: Results from NHANES (2003-2014)\u003c/strong\u003e. \u003cem\u003eFrontiers in cardiovascular medicine \u003c/em\u003e2023, \u003cstrong\u003e10\u003c/strong\u003e:1140160.\u003c/li\u003e\n\u003cli\u003eWei L, Cui X, Lv Y, Zhang F, Wu J: \u003cstrong\u003eThe relationship between estimated pulse wave velocity and 28-day mortality in patients with sA-AKI: a retrospective cohort analysis of the MIMIC-IV database\u003c/strong\u003e. \u003cem\u003eRenal failure \u003c/em\u003e2025, \u003cstrong\u003e47\u003c/strong\u003e(1):2507162.\u003c/li\u003e\n\u003cli\u003eWei L, Liu F, Lv Y, Wu J: \u003cstrong\u003eThe relationship between estimated pulse wave velocity and 28-day mortality in patients with acute kidney injury combined with congestive heart failure: a retrospective cohort analysis of the MIMIC-IV database\u003c/strong\u003e. \u003cem\u003eRenal failure \u003c/em\u003e2025, \u003cstrong\u003e47\u003c/strong\u003e(1):2506831.\u003c/li\u003e\n\u003cli\u003eYang X, Zhang L, Wei H, Zhang F, Yang H, Shi J: \u003cstrong\u003eEstimated pulse wave velocity and the risk of acute kidney injury in patients undergoing coronary revascularization: a retrospective cohort study from MIMIC-IV\u003c/strong\u003e. \u003cem\u003eRenal failure \u003c/em\u003e2025, \u003cstrong\u003e47\u003c/strong\u003e(1):2532859.\u003c/li\u003e\n\u003cli\u003eZhang Y, Cai P, Wu Y, Yu Y, Chen Z, Wang G, Zhang M, Zheng W: \u003cstrong\u003eAssociation between estimated pulse wave velocity and mortality risk in patients with acute ischemic stroke\u003c/strong\u003e. \u003cem\u003eScientific reports \u003c/em\u003e2025, \u003cstrong\u003e15\u003c/strong\u003e(1):22237.\u003c/li\u003e\n\u003cli\u003eLi J, Zhang M, Ye B, Lu M, Liao G: \u003cstrong\u003eAssociation between estimation of pulse wave velocity and all-cause mortality in critically ill patients with non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database\u003c/strong\u003e. \u003cem\u003eFrontiers in neurology \u003c/em\u003e2024, \u003cstrong\u003e15\u003c/strong\u003e:1451116.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Estimated pulse wave velocity, Mortality, Acute pancreatitis","lastPublishedDoi":"10.21203/rs.3.rs-7393160/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7393160/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eEstimated pulse wave velocity (ePWV) is a validated surrogate marker of arterial stiffness and has demonstrated robust prognostic value in various cardiovascular diseases. Acute pancreatitis (AP) is a prevalent and potentially life-threatening gastrointestinal disorder; however, to our knowledge, no prior study has investigated the prognostic significance of ePWV in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe identified adult patients with AP admitted to the intensive care unit (ICU) from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. ePWV was calculated using an established formula based on age and mean arterial pressure (MAP) recorded on the first ICU day, and categorized patients into high- and low-ePWV groups based on the median value. The primary endpoint was 30-day all-cause mortality; secondary endpoints included 60- and 90-day mortality. The Kaplan\u0026ndash;Meier method and multivariable Cox proportional-hazards models were applied to assess associations between ePWV and outcomes, and restricted cubic spline analysis was performed to explore the dose\u0026ndash;response relationship.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 1,351 patients with AP were included (mean age, 51.2 years; 48.7% male). Patients in the high-ePWV group were older (64.3 vs. 37.8 years, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had significantly higher 30-, 60-, and 90-day mortality rates. In multivariable analysis, elevated ePWV was independently associated with an increased risk of 30-day mortality (hazard ratio, 2.12; 95% CI, 1.59\u0026ndash;2.82; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Restricted cubic spline analysis revealed a positive, dose\u0026ndash;response association between ePWV and 30-day mortality, consistent across subgroups stratified by age, race, and hypertension status.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eElevated ePWV is independently associated with higher short-term mortality in patients with AP, supporting its potential role as a simple and readily obtainable prognostic biomarker in the ICU setting.\u003c/p\u003e","manuscriptTitle":"Association Between Estimated Pulse Wave Velocity and 30 Day All-Cause Mortality in Patients with Acute Pancreatitis: a Retrospective Cohort Analysis of the MIMIC-IV Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 07:40:11","doi":"10.21203/rs.3.rs-7393160/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-04T07:38:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T03:32:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263660848673732485986099169830478344162","date":"2026-04-25T14:05:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-25T19:02:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324178486543385145852810710208149050221","date":"2025-12-05T08:28:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73449321864425381218791622332194817785","date":"2025-09-15T08:44:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-15T03:11:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-19T10:54:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-19T01:32:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-19T01:30:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-08-17T15:06:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cebf3035-d4f1-460b-b439-3a9e0a4d8787","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-04T07:38:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T03:32:55+00:00","index":99,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T12:23:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 07:40:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7393160","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7393160","identity":"rs-7393160","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}