Higher Lactate Levels Increased Risk Of 28-Day Mortality In Patients With Paralytic Intestinal Obstruction: A Retrospective Data Analysis Based On MIMIC-Ⅳ Database

Higher Lactate Levels Increased Risk Of 28-Day Mortality In Patients With Paralytic Intestinal Obstruction: A Retrospective Data Analysis Based On 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 Higher Lactate Levels Increased Risk Of 28-Day Mortality In Patients With Paralytic Intestinal Obstruction: A Retrospective Data Analysis Based On MIMIC-Ⅳ Database Yi Hao, Yunpeng Zhou, Yi Wang, Qinyang Du, Yunyan Dai, Zhiming Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7867124/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Introduction: The aim of this study was to investigate the relationship between serum lactate and clinical outcomes in patients with paralytic intestinal obstruction based on data from the MIMIC-IV database. Currently, elevated serum lactate levels have been reported to be associated with mortality in diseases such as sepsis and liver failure. However, there is a lack of evidence on the relationship between lactate and paralytic bowel obstruction, therefore, the aim of this paper is to investigate the relationship between lactate and 28-day mortality in patients with paralytic bowel obstruction. Methods: This was a single-center retrospective study. Based on specific screening criteria, 1472 patients with paralytic bowel obstruction were selected from the Medical Information Marketplace in Critical Care IV (MIMIC-IV) database. Inclusion criteria: ICD diagnosis codes=k56,k560,k567,5601. exclusion criteria: 1.days of survival on admission≤1 day; 2. various malignant tumors; 3. age≤18; 4. not the first ICU admission; 5. length of ICU stay≤1 day; 6. missing lactate data. Different models were constructed to explore the relationship between lactate and 28 d mortality. Results: A total of 1472 patients with paralytic bowel obstruction were included. 28-day mortality was 16.85% (n = 248). After screening the variables using Lasso regression, all the variables obtained were included in a logistic regression model, and a one-way logistic regression showed that the ratio of the odds ratios (OR) for 28-day mortality per 1 mmol/l increase in lactate was 1.21 (95% CI 1.14-1.28, p < 0.001). Significant variables obtained from univariate logistic regression were incorporated into multivariate logistic regression, and the final model showed that lactate was an independent risk factor for predicting 28-day mortality, with an odds ratio (OR) of 1.14 (95% CI 1.07-1.21, P < 0.001) for each 1 mmol/l increase in lactate. The area under the ROC curve (AUC) was 0.65 for lactate and 0.792 for the final model.The RCS model and the smoothed fitted curves showed a nonlinear positive correlation between lactate and 28-day mortality.The K-M curves showed that the group with higher values of LAC had a lower survival rate. Conclusion: Elevated LAC is associated with increased 28-day mortality in ICU paralytic bowel obstruction. This study helps to further explore the relationship between LAC and mortality in patients with paralytic bowel obstruction. Lactate Mortality Paralytic Intestinal Obstruction MIMIC-IV Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. INTRODUCTION Postoperative intestinal obstruction, a common condition and major clinical problem, presents shortly after surgery. It is primarily associated with gastrointestinal surgery, but can also manifest itself through other retroperitoneal pathologies such as aortic or urologic disease. It is characterized by a brief interruption of normal intestinal motility activity [ 1 ]. However, in some patients, prolonged postoperative bowel obstruction occurs, which is associated with 2 or more of the following 4 days after surgery, including vomiting, bloating, inability to tolerate mouth-to-mouth feedings, and absence of flatulence, a condition that is also commonly referred to as “paralytic bowel obstruction”[ 2 ]. Hospitalization costs for patients with the disease were reported to be 71% higher than for those without the disease[ 3 ]. Paralytic intestinal obstruction is a paralysis of intestinal incompetence, mainly caused by obstruction of local nerve conduction in the intestinal tract, autonomic nervous system disorders, and obstruction of intestinal smooth muscle contraction.Intestinal obstruction involves a serious disturbance of gastrointestinal dynamics, usually a complete cessation of normal, coordinated contractile activity. If the diagnosis and treatment of intestinal obstruction are not timely, the disease will develop seriously and even induce serious complications such as intestinal necrosis, perforation and bacterial peritonitis, which will jeopardize the patient's life [ 4 ]. There are two sources of lactic acid in the body: one is primarily from glycolysis, catalyzed by lactate dehydrogenase, and the other is from glutamine catabolism [ 5 ].Studies have shown that the increase in lactate concentration can be attributed to three mechanisms: tissue hypoxia caused by insufficient oxygen supply to the body, increased glycolytic activity under aerobic conditions, or decreased efficiency of lactate clearance due to abnormalities in hepatic and renal metabolic function [ 6 ][ 7 ]. The body of a healthy individual maintains the production and breakdown of lactic acid through a dynamic metabolic balancing mechanism, so that the concentration of lactic acid in the blood is always at a physiologically low level [ 8 ][ 9 ]. Hyperlactatemia occurs when the body experiences an accelerated production of lactic acid (rate of production exceeding clearance), a decreased rate of metabolism (impaired organ clearance), or a combination of both [ 10 ]. Clinically, when blood lactate levels significantly exceed the normal threshold (absolute hyperlactatemia), abnormal elevations of this biomarker have been shown to be positively associated with the risk of in-hospital death in critically ill patients [ 11 ][ 12 ][ 13 ]. Based on its significant prognostic value, lactate testing is not only used as a standard parameter for blood gas analysis in current clinical practice, but also dynamic monitoring is incorporated into the routine management process of critically ill patients, so as to realize early identification and precise intervention in high-risk cases. However, although the level of lactate is clinically important in diseases such as sepsis, liver failure, and cardiac arrest[ 14 ][ 15 ][ 16 ], no study has yet confirmed the relationship between lactate levels and short-term mortality in patients with paralytic bowel obstruction. In our study, we provide evidence on the relationship between lactate levels and clinical outcomes in patients with paralytic bowel obstruction. We found that lactate levels were a valid predictor of hospital prognosis,and its predictive value is independent of well-established Paralytic intestinal obstruction-related prognostic markers. 2. METHODS 2.1.Database, Definition, and Study Cohort This was a retrospective study based on the Medical Information Mart for Intensive Care (MIMIC)-IV database (version3.1, https://mimic.mit.edu/iv/ ), which included the medical records of all the patients admitted to the intensive care unit (ICU) in the Beth Israel Deaconess Medical Center from 2008 to 2019[ 17 ]. To apply for access to the database, the author (Y.H.) passed the Protecting Human Research Participants exam (No. 69397162). Our study included patients with a discharge diagnosis in MIMIC-IV that included paralytic bowel obstruction, with inclusion criteria of ICD diagnosis codes = k56,k560,k567,5601. The exclusion criteria were:1. days of survival on admission ≤ 1 day; 2. various malignant tumors; 3. age ≤ 18; 4. not the first ICU admission; 5. length of ICU stay ≤ 1 day; 6. missing lactate data.Finally,In our research,1472 participants were selected through the screening criteria shown in Fig. 1 for a fow chart. 2.2.Compliance with Ethics Guidelines This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments. MIMIC-IV is an anonymized public database. The project was approved by the institutional review boards of the Massachusetts Institute of Technology (MIT) and Beth Israel Deaconess Medical Center (BIDMC) and was given a waiver of informed consent. 2.3.Variables General characteristics including age, gender, and comorbidities were extracted. Vital signs and laboratory variables of each patient in the 24 h after admission were included. Only the first value of the variable which was recorded in 24 h was utilized for analysis. The following data were used in our research: age, weight, hemoglobin(Hb), platelet(PLT), red blood cell distribution width(RDW), red blood cell(RBC), albumin(Alb), chloride(Cl-), sodium(Na+), lactate(LAC), prothrombin time(PT), bilirubin(BIL), urea nitrogen(BUN), heart rate(HR), respiratory rate(RR), SpO2, hypertension(HTN), acute kidney injury(AKI), hepatitis(HEP), hyperlipidemia(HLD), heart failure(HF). The main outcome variable is: icu 28day mortality.The secondary outcome variable is:hosp 28day mortality,is icu dead,hosp and icu survival time. 2.4.Data Extraction and Statistical Analysis Data analyses were performed using R(version 4.5.0;R Foundation for Statistical Computing) and the DecisionLinnc1.0(DecisionLinnc Core Team) software. DecisionLinnc1.0 is a versatile platform that integrates various programming language enviroments,enabling data processing,analysis,and ML through an intuitive visual interface. Continuous variables were compared between groups using a Student t-test with Welch’s correction or a Mann–Whitney t-test when appropriate. Categorical variables were compared by using a χ2-test. A P value less than 0.05 was considered statistically significant. Multiple imputation (MI) is acommonly used statistical technique for handling missing data[ 18 ]. Vital signs and clinical indices with missing values exceeding 30% were removed, and the remaining missing values were imputed using random forest(rf). With MI, several plausible values for a specific variable are imputed or filled in for each subject who has missing data for that variable. The Kaplan-Meier curve was our chosen method for a graphical representation of 28day mortality, which is well-known for effectively illustrating survival trends. We applied Lasso regression analysis to explore the relationship between 28-day mortality and various factors, an analytical strategy that allowed us to rule out multicollinearity between different independent variables, thus providing a solid basis for assessing statistical significance. All patients with paralytic bowel obstruction included in the study were divided into two groups based on whether or not they died within 28 days of ICU admission, Different variables were reported as follows: (1)continuous variables as Mean(SD); (2)categories variables as percentages or frequencies. Chi-squared test and Mann–Whitney U test were applied for data analysis. First, we compared the different variables between the two groups. Second, we used Lasso regression to exclude a portion of the independent variables with covariates. Afterwards, we implemented univariate and multivariate analyses using the filtered variables and investigated the correlation of the different variables with 28-day mortality by logistic regression. We assessed the ratio of ratios (OR) and 95% confidence intervals (CI) for each variable and included those that were significant in multifactorial logistic regression, and those that were significant in both univariate and multifactorial logistic regression were independent risk factors for predicting 28-day mortality in the ICU, and these were included in the final model. Afterwards, lactate subject operating characteristic (ROC) analysis was performed to predict 28 d mortality. Predictive performance was analyzed using area under the curve (AUC). All patients with paralytic bowel obstruction were divided into three groups according to tertiles of lactate levels (Q1,2.4 mmol/l) and lactate ORs and 95% confidence intervals based on tertiles (Q1-Q3) were analyzed in the two models and p-values were statistically computed in the two different models. In addition, a Kaplan-Meier analysis of the cumulative risk of 28-day mortality based on lactate tertiles was constructed to compare different risks of death between groups. The existence of a correlation between lactate and 28-day mortality was explored using RCS models and smoothed fitted curves. 3. RESULTS 3.1.Subject Characteristics A total of 1472 patients were included in our study (Tables 1 and 2 ) with a mean age of 62.514 years and a 28-day mortality rate of 16.85% (n = 248). There were 987 (67.05%) and 485 (32.95%) males and females respectively. P values for all variables were less than 0.05 except for weight,gender,WBC,ALT which had p values greater than 0.05.The median days to ICU and hospital LOS were 3.78 and 9.53 respectively. In Table 2 , the entire cohort was categorized into three groups based on tertiles of lactate level: Q1 ( 2.4 mmol/l, n = 488). Comparing the different clinical outcomes between the 3 groups, the ICU 28-day mortality rates in the Q1-Q3 groups were 9.92% (n = 50), 15.83% (n = 76) and 25% (n = 122)respectively (P < 0.001). Table 1 is 28d dead Variable Overall No Yes p N = 1472 N = 1224 N = 248 Age 62.514 (15.468) 61.996 (15.623) 65.069 (14.442) 0.004 Weight 88.467 (33.557) 88.884 (33.866) 86.406 (31.977) 0.289 gender (%) F 485 (32.95) 399 (32.60) 86 (34.68) 0.575 M 987 (67.05) 825 (67.40) 162 (65.32) Race (%) asian 42 (2.85) 40 (3.27) 2 (0.81) 0.010 black 179 (12.16) 150 (12.25) 29 (11.69) other 365 (24.80) 286 (23.37) 79 (31.85) white 886 (60.19) 748 (61.11) 138 (55.65) Hb 10.452 (2.354) 10.509 (2.293) 10.172 (2.621) 0.040 PLT 204.832 (122.532) 208.222 (119.082) 188.097 (137.345) 0.018 RDW 15.460 (2.619) 15.174 (2.395) 16.869 (3.166) < 0.001 RBC 3.478 (0.821) 3.509 (0.789) 3.322 (0.950) 0.001 WBC 13.740 (10.541) 13.505 (10.402) 14.900 (11.149) 0.057 Alb 2.899 (0.616) 2.916 (0.590) 2.815 (0.728) 0.019 Cl- 103.517 (6.988) 103.819 (6.583) 102.024 (8.575) < 0.001 K+ 4.337 (0.835) 4.317 (0.795) 4.435 (1.005) 0.042 Na+ 137.715 (5.764) 137.850 (5.310) 137.044 (7.597) 0.045 LAC 2.499 (2.111) 2.316 (1.881) 3.397 (2.837) < 0.001 INR 1.643 (1.039) 1.576 (0.983) 1.976 (1.230) < 0.001 PT 17.853 (10.440) 17.122 (9.597) 21.461 (13.319) < 0.001 ALT 114.198 (435.675) 105.805 (422.250) 155.621 (495.515) 0.101 AST 175.442 (661.940) 154.953 (622.938) 276.560 (822.023) 0.008 BIL 2.343 (5.032) 1.943 (4.466) 4.316 (6.882) < 0.001 Cr 1.703 (1.783) 1.625 (1.778) 2.088 (1.762) < 0.001 BUN 29.667 (24.742) 27.637 (23.387) 39.685 (28.572) < 0.001 HR 94.874 (21.921) 94.301 (21.835) 97.702 (22.169) 0.026 RR 20.601 (6.988) 20.181 (6.765) 22.673 (7.682) < 0.001 Spo2 96.508 (4.480) 96.723 (4.001) 95.448 (6.237) < 0.001 HTN (%) No 933 (63.38) 757 (61.85) 176 (70.97) 0.008 Yes 539 (36.62) 467 (38.15) 72 (29.03) AKI(%) No 601 (40.83) 559 (45.67) 42 (16.94) < 0.001 Yes 871 (59.17) 665 (54.33) 206 (83.06) HEP (%) No 1338 (90.90) 1130 (92.32) 208 (83.87) < 0.001 Yes 134 (9.10) 94 (7.68) 40 (16.13) CKD(%) No 1170 (79.48) 987 (80.64) 183 (73.79) 0.019 Yes 302 (20.52) 237 (19.36) 65 (26.21) HLD(%) No 974 (66.17) 792 (64.71) 182 (73.39) 0.010 Yes 498 (33.83) 432 (35.29) 66 (26.61) HF(%) No 1079 (73.30) 919 (75.08) 160 (64.52) 0.001 Yes 393 (26.70) 305 (24.92) 88 (35.48) Abbreviations: HB,hemoglobin;PLT,platelet;RDW,red blood cell distribution width;RBC,red blood cell;WBC,hemameba;Alb,albumin;Cl-,chloride;K+,potassium;Na+,sodium;LAC,lactate;INR,international normalized ratio;PT,prothrombin time;ALT,alanine aminotransferase;AST,aspartate aminotransferase;BIL,bilirubin;Cr,creatinine;BUN,urea nitrogen;HR,heart rate;RR,respiratory rate; HTN,hypertension;AKI,acute kidney injury;HEP,hepatitis;CKD,chronic kidney disease;HLD,hyperlipidemia;HF,heart failure Table 2 VariableNames level Overall 1 2 3 p N = 1472 N = 504 N = 480 N = 488 hosp survival time 20.865 (1.93-3297.48) 34.91 (3-2837.95) 22.72 (2.13-3297.48) 16.625 (1.93-2269.98) 0.001 icu survival time 18.825 (1.39-3297.42) 32.31 (1.39-2836.95) 20.25 (2.04-3297.42) 14.5 (1.89-2268.68) 0.001 icu dead (%) 0 1154 (78.40) 415 (82.34) 380 (79.17) 359 (73.57) 0.003 1 318 (21.60) 89 (17.66) 100 (20.83) 129 (26.43) hosp 28day mortality(%) 0 1239 (84.17) 459 (91.07) 410 (85.42) 370 (75.82) < 0.001 1 233 (15.83) 45 (8.93) 70 (14.58) 118 (24.18) icu 28day mortality(%) 0 1224 (83.15) 454 (90.08) 404 (84.17) 366 (75.00) < 0.001 1 248 (16.85) 50 (9.92) 76 (15.83) 122 (25.00) 3.2.Lasso Regression Analyses The LASSO coefficient profiles in Fig. 2 A represent a graphical summary of the selection process for the variables that contribute to predicting icu 28-day mortality in patients with Paralytic Intestinal Obstruction.As the log lambda regularization parameter varies,the coefficients of the 30 variables included in the model change,with some variables being progressively eliminated due to their non-significant contribution to the model’s predictive power.The profile provides insights into the most influential factors that affect 28-day mortality in this subset of Paralytic Intestinal Obstruction patients. The relationship between the log lambda and the mean-squared error(MSE) in the LASSO regression,as shown in Fig. 2 B,highlights the trade-off between model complexity and prediction accuracy.As the log lambda increases,the model complexity decreases as less essential variables are excluded. Concurrently, the MSE initially decreases, indicating improved model performance,but may eventually start to increase if too many relevant variables are excluded,leading to underfitting.This plot helps select the optimal regularization parameter that balances the model’s predictive performance with its interpretability. 3.3.Univariate and Multivariate Analyses Variables screened by Lasso regression were included in the logistic regression analysis, and Table 3 summarizes the univariate and multivariate analyses of 28-day mortality in patients with paralytic bowel obstruction. An univariate analysis showed that,RDW,1.23(1.18–1.30, p < .001);LAC,1.21(1.14–1.28, p < .001);PT,1.03(1.02–1.04, p < .001);BIL,1.07(1.05–1.10, p < .001);BUN,1.02(1.01–1.02, p < .001);RR,1.05(1.03–1.07, p < .001);AKI,4.12(2.90–5.85, p < .001);HEP,2.31(1.55–3.44, p < .001);HF,1.66(1.24–2.22, p < .001) are risk factors for 28-day mortality,RBC,0.75(0.63–0.89, p = .001);Alb,0.76(0.61–0.96, p = .019);Cl-,0.96(0.95–0.98, p < .001);SpO2,0.95(0.92–0.97, p < .001);HTN,0.66(0.49–0.89, p = .007);HLD,0.66(0.49–0.90, p = .009) are protective factors for 28-day mortality. It is worth noting that by including the above variables in the multifactorial analysis, some of the variables became meaningless, and of those that were meaningful, those that were risk factors were age,Hb,RDW,LAC,AKI, and the only one that was a protective factor was RBC. The variables that were significant in both univariate and multivariate analyses were used as independent risk factors for 28-day mortality in patients with paralytic intestinal obstruction, and the above variables were included in the final model, and the variables that were significant in all three models were RDW,RBC,LAC,RR, and AKI, which indicated that the five variables mentioned above were significantly correlated with 28- Table 3 Variables Univariate analysis (OR,95%CI,P) Multivariate analysis (OR,95%CI,P) OR (final model) Age 1.01 (1.00-1.02, p = .004) 1.03 (1.01–1.04, p < .001) 1.02 (1.01–1.04, p < .001) Weight 1.00 (0.99-1.00, p = .278) Hb 0.94 (0.89-1.00, p = .040) 1.42 (1.19–1.70, p < .001) 1.44 (1.21–1.71, p < .001) PLT 1.00 (1.00–1.00, p = .019) 1.00 (1.00–1.00, p = .886) RDW 1.23 (1.18–1.30, p < .001) 1.19 (1.12–1.26, p < .001) 1.19 (1.12–1.27, p < .001) RBC 0.75 (0.63–0.89, p = .001) 0.41 (0.25–0.69, p < .001) 0.39 (0.24–0.65, p < .001) Alb 0.76 (0.61–0.96, p = .019) 0.79 (0.61–1.02, p = .066) 0.81 (0.63–1.03, p = .087) Cl- 0.96 (0.95–0.98, p < .001) 1.00 (0.97–1.03, p = .860) Na- 0.98 (0.95-1.00, p = .045) 0.99 (0.96–1.03, p = .668) LAC 1.21 (1.14–1.28, p < .001) 1.14 (1.07–1.22, p < .001) 1.14 (1.07–1.21, p < .001) PT 1.03 (1.02–1.04, p < .001) 1.01 (1.00-1.03, p = .047) 1.01 (1.00-1.03, p = .047) BIL 1.07 (1.05–1.10, p < .001) 1.02 (0.99–1.05, p = .138) 1.03 (1.00-1.06, p = .069) BUN 1.02 (1.01–1.02, p < .001) 1.01 (1.00-1.01, p = .035) 1.01 (1.00-1.01, p = .024) HR 1.01 (1.00-1.01, p = .026) 1.00 (0.99–1.01, p = .660) RR 1.05 (1.03–1.07, p < .001) 1.04 (1.02–1.06, p = .001) 1.04 (1.02–1.06, p < .001) Spo2 0.95 (0.92–0.97, p < .001) 0.97 (0.93-1.00, p = .032) 0.97 (0.94-1.00, p = .035) HTN No Ref Ref Yes 0.66 (0.49–0.89, p = .007) 0.88 (0.62–1.24, p = .471) AKI No Ref Ref Ref Yes 4.12 (2.90–5.85, p < .001) 2.32 (1.57–3.41, p < .001) 2.35 (1.60–3.46, p < .001) HEP No Ref Ref Yes 2.31 (1.55–3.44, p < .001) 1.30 (0.78–2.16, p = .319) HLD No Ref Ref Ref Yes 0.66 (0.49–0.90, p = .009) 0.71 (0.50–1.01, p = .058) 0.71 (0.50-1.00, p = .052) HF No Ref Ref Ref Yes 1.66 (1.24–2.22, p < .001) 1.31 (0.92–1.88, p = .138) 1.35 (0.96–1.91, p = .085) day mortality in patients with paralytic intestinal obstruction. The results of the univariate and multivariate analyses of different lactate levels (Q1,Q2,Q3) and 28-day mortality are summarized separately in Table 4, with the same covariates included as in Table 3. When lactate levels were Q2 (1.5–2.4 mmol/l,n = 321), univariate analysis showed 1.68 (1.03–2.72,p = .036) increased risk of death compared to Q1 ( 2.4 mmol/l,n = 337), a 3.33-fold(2.14–5.19,p < .001) increase in the risk of death was shown in the univariate analysis and in the multivariate analysis, a 2.44-fold(1.50–3.99,p < .001) increase in the risk of death was shown, when compared to Q1. It further illustrates that lactate content is significantly associated with 28-day mortality in patients with paralytic intestinal obstruction. Table 4 Exposure Univariate analysis (OR, 95% CI, P) Multivariate analysis (OR, 95% CI, P) 28-day mortality Lactate (mmol/l) quartiles Q1( 2.4 mmol/l, n = 337) 3.33 (2.14–5.19, p < .001) 2.44 (1.50–3.99, p < .001) 3.4. Predictive Performance of Lactate for 28Day Mortality The predictive performance of lactate and the final model for 28-day mortality in patients with paralytic bowel obstruction is summarized in A and B of Fig. 3 , respectively. Figure 3 A shows that the area under the ROC curve (AUC) for lactic acid was 0.650 (95% CI 0.613–0.687), with an optimal threshold of 0.141, which corresponded to a specificity and sensitivity of 0.458 and 0.754, respectively. Figure 3 B shows that the area under the ROC curve (AUC) of the model was 0.792 (95% CI 0.762–0.822), with an optimal threshold of 0.201, corresponding to specificities and sensitivities of 0.788, and 0.673, respectively. Demonstrating the good results obtained in the prediction of 28-day mortality by both the lactate and the model. 3.5. Relationship Between Lactate and 28-Day Mortality We divided all patients with paralytic intestinal obstruction into 3 groups according to tertiles of lactate levels (Q1,2.4 mmol/l,n = 488), and Kaplan-Meier analysis of cumulative risk of 28-day mortality is shown in Fig. 4 . As shown in Fig. 4 , the Q3 group had the highest risk of 28-day mortality (> 2.4 mmol/l) according to tertiles of lactate levels (P < 0.0001). 3.6.Non-linear Relationship Between LAC Levels And Mortality As shown in Fig. 5A, the RCS results indicated a non-linear relationship between lactate and the OR of 28-day mortality similar to a ‘J-shape’ (P for Nonlinear = 0.005), while a histogram demonstrated the distribution of the number of patients with different lactate levels. Figure 5B shows the smoothed fitted curves of lactate content and 28-day mortality, and the results likewise indicate a nonlinear relationship, with mortality showing a trend of increasing, then decreasing, then increasing as lactate content increases. Figure5 Relationship Between LAC and 28-day Mortality in Patients with Paralytic Intestinal Obstruction.(A) Graphs show ORs between LAC and 28day mortality, adjusted for age, Hb, RDW, RBC, Alb, PT, BIL, BUN, RR, SpO2, AKI, HLD, HF. Data were fitted by a restricted cubic spline model, and the model was conducted with 4 knots. Solid lines indicate ORs, and shadow shapes indicate 95% CIs.The red line represents the density distribution curve.(B) Association between LAC and 28 day mortality for patients with paralytic intestinal obstruction.The solid line in the middle represents the smooth curve fitting between variables.Imaginary lines represent the 95% of confidence interval from the fit. 4. DISCUSSION In our study, we found a nonlinear positive correlation between lactate levels and 28-day mortality in patients with paralytic bowel obstruction. In addition, the prognostic value of lactate for paralytic bowel obstruction was determined. To the best of our knowledge, this is the first MIMIC-IV-based study to explore the relationship between serum lactate levels and clinical outcomes in patients with paralytic bowel obstruction. It has been demonstrated that in patients with paralytic intestinal obstruction, a neurogenic component plays an important role, with activation of sympathetic pathways leading to widespread inhibition of gastrointestinal motility through inhibition of intestinal nerve reflex pathways[ 19 ]. Lactic acid or paralytic bowel obstruction has been partially investigated in previous studies. A systematic evaluation showed that inflammatory parameters including interleukin (IL)-6, IL-1, and TNF-α may be useful for early detection of prolonged paralytic bowel obstruction[ 20 ], Another study, also on 28-day mortality in patients with paralytic intestinal obstruction, found a nonlinear positive correlation between erythrocyte distribution width and mortality[ 21 ], Other associated risk factors include C-reactive protein, leukocytes, mononuclear leukocytes, neutrophils, interleukin-6, and erythrocyte sedimentation rate[ 22 ][ 23 ], All of these indicators are valid predictors of mortality. Lactate can be used as an objective biomarker of tissue perfusion as an easily available and simple laboratory indicator, which is superior to urine output and physical examination[ 24 ]. Some previous studies have shown that lactate levels can be used to risk-stratify the severity of some diseases, and that elevated lactate levels reveal a poorer prognosis for sepsis, liver failure, cardiac arrest, and other diseases[ 14 ][ 15 ][ 16 ]. Although lactate is important for the prognosis of numerous diseases, there are no studies on the correlation between clinical prognosis and lactate levels in patients with paralytic intestinal obstruction.The aim of our study was to explore the relationship between serum lactate and clinical outcomes in patients with paralytic intestinal obstruction based on large-scale public databases, which can be used to help physicians to risk stratify different types of patients. Our study showed an OR of 1.14 (1.07–1.21, p < .001) for 28-day mortality per 1-mmol/l increase in lactate in the adjusted final model.The analysis of K-M curves for the cumulative risk of 28-day mortality in patients with different lactate levels also showed that the higher the lactate level, the higher the risk of 28-day mortality in patients with paralytic bowel obstruction. Our study suggests that in patients with paralytic bowel obstruction, physicians should pay more attention to actively measuring and monitoring his lactate level, because lactate level can reflect the patient's prognosis to some extent. The strength of this study is that physicians can risk stratify patients with paralytic bowel obstruction according to different lactate levels based on our results. However, our study has some limitations, firstly, it is a study based on a public database in the United States, and due to the lack of some data, some interventions or medications that may affect the prognosis were not included in the study, which may cause some bias. Secondly, this study is a single-center study, and the conclusions drawn may not be generally applicable to patients in other countries or regions. 5. CONCLUSION Trough analysis of the MIMIC database,In patients with paralytic intestinal obstruction, a non-linear positive relationship was discovered between serum lactate and 28-day mortality. Physicians should be alert to lactate assessment at admission and pay more attention to those patients with higher levels of lactate. More research is needed to explore further the relationship between the two. Declarations ACKNOWLEDGEMENTS Funding: The author(s) declare financial support was received for the research, authorship, and/or ublication of this article. This work was supported by: Research on New MALDI Source Mass Spectrometry Imaging Technology in Surgical Specimens(ZC2025004916).Research and Innovation Team Project for Scientific Breakthroughs at Shanxi Bethune Hospital (2024ZHANCHI07).Shanxi Province Basic Research Program (Free Exploration) Surface Project (Grant No: 202303021221189).Science and research fund of Shanxi Health Commission (Grant No. 2019059, 2022042, 2022043).Shanxi Scholarship Council of China (Grant No. 2021-165). Shanxi Province Science Foundation for Distinguished Young Scholar (Grant No. 201901D211547). Shanxi Province “136 Revitalization Medical Project Construction Funds”. National Natural Science Foundation of China for Young Scholars (Grant No. 81201810). The doctor project of Shanxi Cancer Hospital, China (2017A06). Natural Science Foundation of Guangdong Province, China (2015A030313057). Author Contributions: YH: Writing– original draft. ZW: Writing– review & editing. YD: Writing– review & editing. YPZ: Writing– review & editing. YW: Writing– review & editing. QD: Writing– review & editing.RG: Writing– review & editing. GL: Writing– review & editing. Disclosures: All the authors have nothing to disclose. Compliance with Ethics Guidelines: This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments. MIMIC-IV is an anonymized public database. The project was approved by the institutional review boards of the Massachusetts Institute of Technology (MIT) and Beth Israel Deaconess Medical Center (BIDMC) and was given a waiver of informed consent. Data Availability: The data utilized in this investigation was sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV), which is accessible at the following link: https://mimic-iv.mit.edu. To gain access to the data, one must be an authenticated user, complete the required training, and adhere to the project’s data usage agreement. To apply for access to the database, the author (Y.H.) passed the Protecting Human Research Participants exam (No. 69397162). However, The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Wattchow D, Heitmann P, Smolilo D, et al. Postoperative ileus-An ongoing conundrum. Neurogastroenterol Motil . 2021;33(5):e14046. Vather R, O'Grady G, Bissett IP, Dinning PG. Postoperative ileus: mechanisms and future directions for research. Clin Exp Pharmacol Physiol. 2014;41(5):358-370. Mao H, Milne TG, O’Grady G, Vather R, Edlin R, Bissett I. Prolonged postoperative ileus significantly increases the cost of inpatient stay for patients undergoing elective colorectal surgery: results of a multivariate analysis of prospective data at a single institution. Dis Colon Rectum. 2019;62(5):631-637. A. H. Daniels, S. A. Ritterman, and L. E. Rubin, “Paralytic ileus in the orthopaedic patient,” J AM ACAD ORTHOP SUR, vol. 23, no. 6, pp. 365–372, 2015. DeBerardinis RJ, et al. Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc Natl Acad Sci U S A. 2007;104(49):19345–50. Yoon S, Choi B, Eun S, Bae G, Koo C, Kim M. Using the lactate-to-albumin ratio to predict mortality in patients with sepsis or septic shock: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci. 2022;26(5):1743–52. Jouffroy R, Vivien B. Initial antimicrobial management of sepsis: increased prehospital blood lactate levels for identifying sicker patients who may benefit from prehospital antibiotic therapy initiation. Crit Care. 2021;25(1):377. De Backer D. Lactic acidosis. Intensive Care Med. 2003;29:699–702. De Backer D. Lactic acidosis. Minerva Anestesiol. 2003;69:281–284. Nichol AD, Egi M, Pettila V, Bellomo R, French C, Hart G, Davies A, Stachowski E, Reade MC, Bailey M, Cooper DJ. Relative hyperlactatemia and hospital mortality in critically ill patients: a retrospective multi-centre study. Crit Care. 2010;14(1):R25. Husain FA, Martin MJ, Mullenix PS, Steele SR, Elliott DC. Serum lactate and base deficit as predictors of mortality and morbidity. Am J Surg. 2003;185:485–491. Jansen TC, van Bommel J, Woodward R, Mulder PG, Bakker J. Association between blood lactate levels, Sequential Organ Failure Assessment subscores, and 28-day mortality during early and late intensive care unit stay: a retrospective observational study. Crit Care Med. 2009;37:2369–2374. Khosravani H, Shahpori R, Stelfox HT, Kirkpatrick AW, Laupland KB. Occurrence and adverse effect on outcome of hyperlactatemia in the critically ill. Crit Care. 2009;13:R90. He L, Yang D, Ding Q, Su Y, Ding N. Association Between Lactate and 28-Day Mortality in Elderly Patients with Sepsis: Results from MIMIC-IV Database. Infect Dis Ther . 2023;12(2):459-472. Zhang M, Zhang Q, Yu Y, An L, Qi Z, Li C. Effects of early hemodynamics, oxygen metabolism, and lactate dynamics on prognosis of post-cardiac arrest syndrome. Chin Med J. 2021;135(3):344–6. Gao Y, Zhang H, Zhong H, Yang S, Wang Q. Lactate and blood ammonia on admission as biomarkers to predict the prognosis of patients with acute mushroom poisoning and liver failure: a retrospective study. Toxicol Res. 2021;10(4):850–5. Johnson A, Stone D, Celi L, Pollard T. The MIMIC code repository: enabling reproducibility in critical care research. J Am Med Inf Assoc. 2018;25(1):32–9. Austin PC, White IR, Lee DS, van Buuren S. Missing Data in Clinical Research: A Tutorial on Multiple Imputation. Can J Cardiol . 2021;37(9):1322-1331. Bauer AJ, Boeckxstaens GE. Mechanisms of postoperative ileus. Neurogastroenterol Motil. 2004;16(Suppl 2):54-60. Wu Z, Boersema GS, Dereci A, Menon AG, Jeekel J, Lange JF. Clinical endpoint, early detection, and differential diagnosis of postoperative ileus: a systematic review of the literature. Eur Surg Res . 2015;54(3-4):127-138. Zhao X, Wan X, Gu C, et al. Association between Red Blood Cell Distribution Width and Short-Term Mortality in Patients with Paralytic Intestinal Obstruction: Retrospective Data Analysis Based on the MIMIC-III Database. Emerg Med Int . 2023;2023:6739136. Published 2023 Oct 23. J. C. Kalf, T. M. Carlos, W. H. Schraut, T. R. Billiar, R. L. Simmons, and A. J. Bauer, “Surgically induced leukocytic infltrates within the rat intestinal muscularis mediate postoperative ileus,” Gastroenterology, vol. 117, no. 2, pp. 378–387, 1999. Y. Sun, H. Shi, Z. Hong, and P. Chi, “Inhibition of JAK1 mitigates postoperative ileus in mice,” Surgery, vol. 166, no. 6, pp. 1048–1054, 2019. Weinberger J, Klompas M, Rhee C. What is the utility of measuring lactate levels in patients with sepsis and septic shock? Sem Respir Crit Care Med. 2021;42(5):650–61. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 22 Nov, 2025 Reviewers agreed at journal 19 Nov, 2025 Reviewers agreed at journal 17 Nov, 2025 Reviewers invited by journal 10 Nov, 2025 Editor invited by journal 19 Oct, 2025 Editor assigned by journal 16 Oct, 2025 Submission checks completed at journal 16 Oct, 2025 First submitted to journal 15 Oct, 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. 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08:14:31","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126110,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/54946f5bfe231e22d0db87f9.html"},{"id":96366953,"identity":"69ccd30e-9926-43f3-910a-a6d31f099b69","added_by":"auto","created_at":"2025-11-20 10:12:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":71388,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of selection for patients.Notes:the patients with paralytic intestinal obstruction were extracted(n=2150).Then, patients with the following standards were excluded:age\u0026lt;18 years old (n=0),ICU stay\u0026lt;1 day(n=211),malignant cancer (n=298),admission survival days\u0026lt;24h(n=7),no lactate record(n=162). Finally, this study screened 1472 patients for analysis.Abbreviations:MIMIC-Ⅳ,medical information mart for intensive care Ⅳ;ICU,intensive care unit;ICD,international classifcation of diseases.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/75b23d6602719129bd842645.png"},{"id":96354954,"identity":"8a3143e5-cf24-4a23-a142-afa1938962aa","added_by":"auto","created_at":"2025-11-20 08:14:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":119615,"visible":true,"origin":"","legend":"\u003cp\u003e(A) shows the contribution of different features in Lasso regression and the Lambda value;(B) lists the percentage of regularization parameters used to balance the model’s predictive performance and interpretability.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/a834dbd8a3aaa50f2eaff279.png"},{"id":96354959,"identity":"d02b8f17-6aab-450f-98c1-41555f650408","added_by":"auto","created_at":"2025-11-20 08:14:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":115856,"visible":true,"origin":"","legend":"\u003cp\u003eTime-dependent receiver operating characteristic(t-ROC) curves are used to assess the performance of the Logistic regression model in predicting 28d Mortality for patients with Paralytic Intestinal Obstruction. (A)ROC for Lactate (B)ROC for Model\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/54329498423fa3b639107ff8.png"},{"id":96354960,"identity":"f4c12b53-9670-4d1a-9101-9ddebcd89e75","added_by":"auto","created_at":"2025-11-20 08:14:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":117889,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curves are used to visualize the survival outcomes of patients with Paralytic Intestinal Obstruction.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/86668f484ba0657e4b71d08b.png"},{"id":96366834,"identity":"2dbdf98b-3bdb-4e00-a674-c7c2b4eac7ba","added_by":"auto","created_at":"2025-11-20 10:11:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":91579,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship Between LAC and 28-day Mortality in Patients with Paralytic Intestinal Obstruction.(A) Graphs show ORs between LAC and 28day mortality, adjusted for age, Hb, RDW, RBC, Alb, PT, BIL, BUN, RR, SpO2, AKI, HLD, HF. Data were fitted by a restricted cubic spline model, and the model was conducted with 4 knots. Solid lines indicate ORs, and shadow shapes indicate 95% CIs.The red line represents the density distribution curve.(B) Association between LAC and 28 day mortality for patients with paralytic intestinal obstruction.The solid line in the middle represents the smooth curve fitting between variables.Imaginary lines represent the 95% of confidence interval from the fit.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/6348d2e9aea9ffad71f0d90c.png"},{"id":96369437,"identity":"7d9143a0-0f26-4287-944c-75ae6fe09d3f","added_by":"auto","created_at":"2025-11-20 10:20:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3127092,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7867124/v1/a2409f20-2639-4af3-b432-1de3ddc70841.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Higher Lactate Levels Increased Risk Of 28-Day Mortality In Patients With Paralytic Intestinal Obstruction: A Retrospective Data Analysis Based On MIMIC-Ⅳ Database","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003ePostoperative intestinal obstruction, a common condition and major clinical problem, presents shortly after surgery. It is primarily associated with gastrointestinal surgery, but can also manifest itself through other retroperitoneal pathologies such as aortic or urologic disease. It is characterized by a brief interruption of normal intestinal motility activity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, in some patients, prolonged postoperative bowel obstruction occurs, which is associated with 2 or more of the following 4 days after surgery, including vomiting, bloating, inability to tolerate mouth-to-mouth feedings, and absence of flatulence, a condition that is also commonly referred to as \u0026ldquo;paralytic bowel obstruction\u0026rdquo;[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Hospitalization costs for patients with the disease were reported to be 71% higher than for those without the disease[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Paralytic intestinal obstruction is a paralysis of intestinal incompetence, mainly caused by obstruction of local nerve conduction in the intestinal tract, autonomic nervous system disorders, and obstruction of intestinal smooth muscle contraction.Intestinal obstruction involves a serious disturbance of gastrointestinal dynamics, usually a complete cessation of normal, coordinated contractile activity. If the diagnosis and treatment of intestinal obstruction are not timely, the disease will develop seriously and even induce serious complications such as intestinal necrosis, perforation and bacterial peritonitis, which will jeopardize the patient's life [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThere are two sources of lactic acid in the body: one is primarily from glycolysis, catalyzed by lactate dehydrogenase, and the other is from glutamine catabolism [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].Studies have shown that the increase in lactate concentration can be attributed to three mechanisms: tissue hypoxia caused by insufficient oxygen supply to the body, increased glycolytic activity under aerobic conditions, or decreased efficiency of lactate clearance due to abnormalities in hepatic and renal metabolic function [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The body of a healthy individual maintains the production and breakdown of lactic acid through a dynamic metabolic balancing mechanism, so that the concentration of lactic acid in the blood is always at a physiologically low level [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Hyperlactatemia occurs when the body experiences an accelerated production of lactic acid (rate of production exceeding clearance), a decreased rate of metabolism (impaired organ clearance), or a combination of both [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Clinically, when blood lactate levels significantly exceed the normal threshold (absolute hyperlactatemia), abnormal elevations of this biomarker have been shown to be positively associated with the risk of in-hospital death in critically ill patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Based on its significant prognostic value, lactate testing is not only used as a standard parameter for blood gas analysis in current clinical practice, but also dynamic monitoring is incorporated into the routine management process of critically ill patients, so as to realize early identification and precise intervention in high-risk cases.\u003c/p\u003e\u003cp\u003eHowever, although the level of lactate is clinically important in diseases such as sepsis, liver failure, and cardiac arrest[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], no study has yet confirmed the relationship between lactate levels and short-term mortality in patients with paralytic bowel obstruction.\u003c/p\u003e\u003cp\u003eIn our study, we provide evidence on the relationship between lactate levels and clinical outcomes in patients with paralytic bowel obstruction. We found that lactate levels were a valid predictor of hospital prognosis,and its predictive value is independent of well-established Paralytic intestinal obstruction-related prognostic markers.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1.Database, Definition, and Study Cohort\u003c/h2\u003e\u003cp\u003eThis was a retrospective study based on the Medical Information Mart for Intensive Care (MIMIC)-IV database (version3.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mimic.mit.edu/iv/\u003c/span\u003e\u003cspan address=\"https://mimic.mit.edu/iv/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which included the medical records of all the patients admitted to the intensive care unit (ICU) in the Beth Israel Deaconess Medical Center from 2008 to 2019[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To apply for access to the database, the author (Y.H.) passed the Protecting Human Research Participants exam (No. 69397162).\u003c/p\u003e\u003cp\u003eOur study included patients with a discharge diagnosis in MIMIC-IV that included paralytic bowel obstruction, with inclusion criteria of ICD diagnosis codes\u0026thinsp;=\u0026thinsp;k56,k560,k567,5601. The exclusion criteria were:1. days of survival on admission\u0026thinsp;\u0026le;\u0026thinsp;1 day; 2. various malignant tumors; 3. age\u0026thinsp;\u0026le;\u0026thinsp;18; 4. not the first ICU admission; 5. length of ICU stay\u0026thinsp;\u0026le;\u0026thinsp;1 day; 6. missing lactate data.Finally,In our research,1472 participants were selected through the screening criteria shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for a fow chart.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2.Compliance with Ethics Guidelines\u003c/h2\u003e\u003cp\u003e This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments. MIMIC-IV is an anonymized public database. The project was approved by the institutional review boards of the Massachusetts Institute of Technology (MIT) and Beth Israel Deaconess Medical Center (BIDMC) and was given a waiver of informed consent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3.Variables\u003c/h2\u003e\u003cp\u003eGeneral characteristics including age, gender, and comorbidities were extracted. Vital signs and laboratory variables of each patient in the 24 h after admission were included. Only the first value of the variable which was recorded in 24 h was utilized for analysis.\u003c/p\u003e\u003cp\u003eThe following data were used in our research: age, weight, hemoglobin(Hb), platelet(PLT), red blood cell distribution width(RDW), red blood cell(RBC), albumin(Alb), chloride(Cl-), sodium(Na+), lactate(LAC), prothrombin time(PT), bilirubin(BIL), urea nitrogen(BUN), heart rate(HR), respiratory rate(RR), SpO2, hypertension(HTN), acute kidney injury(AKI), hepatitis(HEP), hyperlipidemia(HLD), heart failure(HF). The main outcome variable is: icu 28day mortality.The secondary outcome variable is:hosp 28day mortality,is icu dead,hosp and icu survival time.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4.Data Extraction and Statistical Analysis\u003c/h2\u003e\u003cp\u003eData analyses were performed using R(version 4.5.0;R Foundation for Statistical Computing) and the DecisionLinnc1.0(DecisionLinnc Core Team) software. DecisionLinnc1.0 is a versatile platform that integrates various programming language enviroments,enabling data processing,analysis,and ML through an intuitive visual interface. Continuous variables were compared between groups using a Student t-test with Welch\u0026rsquo;s correction or a Mann\u0026ndash;Whitney t-test when appropriate. Categorical variables were compared by using a χ2-test. A P value less than 0.05 was considered statistically significant. Multiple imputation (MI) is acommonly used statistical technique for handling missing data[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Vital signs and clinical indices with missing values exceeding 30% were removed, and the remaining missing values were imputed using random forest(rf). With MI, several plausible values for a specific variable are imputed or filled in for each subject who has missing data for that variable. The Kaplan-Meier curve was our chosen method for a graphical representation of 28day mortality, which is well-known for effectively illustrating survival trends. We applied Lasso regression analysis to explore the relationship between 28-day mortality and various factors, an analytical strategy that allowed us to rule out multicollinearity between different independent variables, thus providing a solid basis for assessing statistical significance.\u003c/p\u003e\u003cp\u003eAll patients with paralytic bowel obstruction included in the study were divided into two groups based on whether or not they died within 28 days of ICU admission, Different variables were reported as follows: (1)continuous variables as Mean(SD); (2)categories variables as percentages or frequencies. Chi-squared test and Mann\u0026ndash;Whitney U test were applied for data analysis.\u003c/p\u003e\u003cp\u003eFirst, we compared the different variables between the two groups. Second, we used Lasso regression to exclude a portion of the independent variables with covariates. Afterwards, we implemented univariate and multivariate analyses using the filtered variables and investigated the correlation of the different variables with 28-day mortality by logistic regression. We assessed the ratio of ratios (OR) and 95% confidence intervals (CI) for each variable and included those that were significant in multifactorial logistic regression, and those that were significant in both univariate and multifactorial logistic regression were independent risk factors for predicting 28-day mortality in the ICU, and these were included in the final model. Afterwards, lactate subject operating characteristic (ROC) analysis was performed to predict 28 d mortality. Predictive performance was analyzed using area under the curve (AUC). All patients with paralytic bowel obstruction were divided into three groups according to tertiles of lactate levels (Q1,\u0026lt;1.5 mmol/l; Q2,1.5\u0026ndash;2.4 mmol/l; Q3,\u0026gt;2.4 mmol/l) and lactate ORs and 95% confidence intervals based on tertiles (Q1-Q3) were analyzed in the two models and p-values were statistically computed in the two different models. In addition, a Kaplan-Meier analysis of the cumulative risk of 28-day mortality based on lactate tertiles was constructed to compare different risks of death between groups. The existence of a correlation between lactate and 28-day mortality was explored using RCS models and smoothed fitted curves.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1.Subject Characteristics\u003c/h2\u003e\u003cp\u003eA total of 1472 patients were included in our study (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) with a mean age of 62.514 years and a 28-day mortality rate of 16.85% (n\u0026thinsp;=\u0026thinsp;248). There were 987 (67.05%) and 485 (32.95%) males and females respectively. P values for all variables were less than 0.05 except for weight,gender,WBC,ALT which had p values greater than 0.05.The median days to ICU and hospital LOS were 3.78 and 9.53 respectively.\u003c/p\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the entire cohort was categorized into three groups based on tertiles of lactate level: Q1 (\u0026lt;\u0026thinsp;1.5 mmol/l, n\u0026thinsp;=\u0026thinsp;504), Q2 (1.5\u0026ndash;2.4 mmol/l, n\u0026thinsp;=\u0026thinsp;480) and Q3 (\u0026gt;\u0026thinsp;2.4 mmol/l, n\u0026thinsp;=\u0026thinsp;488). Comparing the different clinical outcomes between the 3 groups, the ICU 28-day mortality rates in the Q1-Q3 groups were 9.92% (n\u0026thinsp;=\u0026thinsp;50), 15.83% (n\u0026thinsp;=\u0026thinsp;76) and 25% (n\u0026thinsp;=\u0026thinsp;122)respectively (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eis 28d dead\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd 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(38.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 (29.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAKI(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e601 (40.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e559 (45.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (16.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e871 (59.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e665 (54.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e206 (83.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEP (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1338 (90.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1130 (92.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e208 (83.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e134 (9.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94 (7.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (16.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCKD(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1170 (79.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e987 (80.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e183 (73.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e302 (20.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e237 (19.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65 (26.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHLD(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e974 (66.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e792 (64.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e182 (73.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e498 (33.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e432 (35.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66 (26.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHF(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1079 (73.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e919 (75.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e160 (64.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e393 (26.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e305 (24.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88 (35.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations: HB,hemoglobin;PLT,platelet;RDW,red blood cell distribution width;RBC,red blood cell;WBC,hemameba;Alb,albumin;Cl-,chloride;K+,potassium;Na+,sodium;LAC,lactate;INR,international normalized ratio;PT,prothrombin time;ALT,alanine aminotransferase;AST,aspartate aminotransferase;BIL,bilirubin;Cr,creatinine;BUN,urea nitrogen;HR,heart rate;RR,respiratory rate; HTN,hypertension;AKI,acute kidney injury;HEP,hepatitis;CKD,chronic kidney disease;HLD,hyperlipidemia;HF,heart failure\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariableNames\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003elevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;1472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;504\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ehosp survival time\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.865 (1.93-3297.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.91 (3-2837.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22.72 (2.13-3297.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.625 (1.93-2269.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eicu survival time\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.825 (1.39-3297.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32.31 (1.39-2836.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20.25 (2.04-3297.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14.5 (1.89-2268.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eicu dead (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1154 (78.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e415 (82.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e380 (79.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e359 (73.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e318 (21.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e89 (17.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100 (20.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e129 (26.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ehosp 28day mortality(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1239 (84.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e459 (91.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e410 (85.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e370 (75.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e233 (15.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45 (8.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70 (14.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e118 (24.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eicu 28day mortality(%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1224 (83.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e454 (90.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e404 (84.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e366 (75.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e248 (16.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50 (9.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76 (15.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e122 (25.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2.Lasso Regression Analyses\u003c/h2\u003e\u003cp\u003eThe LASSO coefficient profiles in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA represent a graphical summary of the selection process for the variables that contribute to predicting icu 28-day mortality in patients with Paralytic Intestinal Obstruction.As the log lambda regularization parameter varies,the coefficients of the 30 variables included in the model change,with some variables being progressively eliminated due to their non-significant contribution to the model\u0026rsquo;s predictive power.The profile provides insights into the most influential factors that affect 28-day mortality in this subset of Paralytic Intestinal Obstruction patients.\u003c/p\u003e\u003cp\u003eThe relationship between the log lambda and the mean-squared error(MSE) in the LASSO regression,as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB,highlights the trade-off between model complexity and prediction accuracy.As the log lambda increases,the model complexity decreases as less essential variables are excluded. Concurrently, the MSE initially decreases, indicating improved model performance,but may eventually start to increase if too many relevant variables are excluded,leading to underfitting.This plot helps select the optimal regularization parameter that balances the model\u0026rsquo;s predictive performance with its interpretability.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3.Univariate and Multivariate Analyses\u003c/h2\u003e\u003cp\u003eVariables screened by Lasso regression were included in the logistic regression analysis, and Table\u0026nbsp;3 summarizes the univariate and multivariate analyses of 28-day mortality in patients with paralytic bowel obstruction. An univariate analysis showed that,RDW,1.23(1.18\u0026ndash;1.30, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);LAC,1.21(1.14\u0026ndash;1.28, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);PT,1.03(1.02\u0026ndash;1.04, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);BIL,1.07(1.05\u0026ndash;1.10, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);BUN,1.02(1.01\u0026ndash;1.02, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);RR,1.05(1.03\u0026ndash;1.07, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);AKI,4.12(2.90\u0026ndash;5.85, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);HEP,2.31(1.55\u0026ndash;3.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);HF,1.66(1.24\u0026ndash;2.22, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) are risk factors for 28-day mortality,RBC,0.75(0.63\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;.001);Alb,0.76(0.61\u0026ndash;0.96, p\u0026thinsp;=\u0026thinsp;.019);Cl-,0.96(0.95\u0026ndash;0.98, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);SpO2,0.95(0.92\u0026ndash;0.97, p\u0026thinsp;\u0026lt;\u0026thinsp;.001);HTN,0.66(0.49\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;.007);HLD,0.66(0.49\u0026ndash;0.90, p\u0026thinsp;=\u0026thinsp;.009) are protective factors for 28-day mortality. It is worth noting that by including the above variables in the multifactorial analysis, some of the variables became meaningless, and of those that were meaningful, those that were risk factors were age,Hb,RDW,LAC,AKI, and the only one that was a protective factor was RBC.\u003c/p\u003e\u003cp\u003eThe variables that were significant in both univariate and multivariate analyses were used as independent risk factors for 28-day mortality in patients with paralytic intestinal obstruction, and the above variables were included in the final model, and the variables that were significant in all three models were RDW,RBC,LAC,RR, and AKI, which indicated that the five variables mentioned above were significantly correlated with 28-\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVariables\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eUnivariate analysis (OR,95%CI,P)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMultivariate analysis (OR,95%CI,P)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eOR (final model)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01 (1.00-1.02, p\u0026thinsp;=\u0026thinsp;.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03 (1.01\u0026ndash;1.04, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02 (1.01\u0026ndash;1.04, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWeight\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (0.99-1.00, p\u0026thinsp;=\u0026thinsp;.278)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHb\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94 (0.89-1.00, p\u0026thinsp;=\u0026thinsp;.040)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.42 (1.19\u0026ndash;1.70, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.44 (1.21\u0026ndash;1.71, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePLT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00 (1.00\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;.019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00 (1.00\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;.886)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRDW\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.23 (1.18\u0026ndash;1.30, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.19 (1.12\u0026ndash;1.26, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.19 (1.12\u0026ndash;1.27, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRBC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.75 (0.63\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.41 (0.25\u0026ndash;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.39 (0.24\u0026ndash;0.65, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAlb\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.76 (0.61\u0026ndash;0.96, p\u0026thinsp;=\u0026thinsp;.019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.79 (0.61\u0026ndash;1.02, p\u0026thinsp;=\u0026thinsp;.066)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.81 (0.63\u0026ndash;1.03, p\u0026thinsp;=\u0026thinsp;.087)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCl-\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.96 (0.95\u0026ndash;0.98, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00 (0.97\u0026ndash;1.03, p\u0026thinsp;=\u0026thinsp;.860)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNa-\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.98 (0.95-1.00, p\u0026thinsp;=\u0026thinsp;.045)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.99 (0.96\u0026ndash;1.03, p\u0026thinsp;=\u0026thinsp;.668)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLAC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.21 (1.14\u0026ndash;1.28, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.14 (1.07\u0026ndash;1.22, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 (1.07\u0026ndash;1.21, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.03 (1.02\u0026ndash;1.04, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01 (1.00-1.03, p\u0026thinsp;=\u0026thinsp;.047)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01 (1.00-1.03, p\u0026thinsp;=\u0026thinsp;.047)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBIL\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.07 (1.05\u0026ndash;1.10, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.02 (0.99\u0026ndash;1.05, p\u0026thinsp;=\u0026thinsp;.138)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.03 (1.00-1.06, p\u0026thinsp;=\u0026thinsp;.069)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBUN\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.02 (1.01\u0026ndash;1.02, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01 (1.00-1.01, p\u0026thinsp;=\u0026thinsp;.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01 (1.00-1.01, p\u0026thinsp;=\u0026thinsp;.024)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01 (1.00-1.01, p\u0026thinsp;=\u0026thinsp;.026)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00 (0.99\u0026ndash;1.01, p\u0026thinsp;=\u0026thinsp;.660)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.05 (1.03\u0026ndash;1.07, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.04 (1.02\u0026ndash;1.06, p\u0026thinsp;=\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.04 (1.02\u0026ndash;1.06, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSpo2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.95 (0.92\u0026ndash;0.97, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.97 (0.93-1.00, p\u0026thinsp;=\u0026thinsp;.032)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97 (0.94-1.00, p\u0026thinsp;=\u0026thinsp;.035)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHTN\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.66 (0.49\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;.007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.88 (0.62\u0026ndash;1.24, p\u0026thinsp;=\u0026thinsp;.471)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAKI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.12 (2.90\u0026ndash;5.85, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.32 (1.57\u0026ndash;3.41, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.35 (1.60\u0026ndash;3.46, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHEP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.31 (1.55\u0026ndash;3.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.30 (0.78\u0026ndash;2.16, p\u0026thinsp;=\u0026thinsp;.319)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHLD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.66 (0.49\u0026ndash;0.90, p\u0026thinsp;=\u0026thinsp;.009)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.71 (0.50\u0026ndash;1.01, p\u0026thinsp;=\u0026thinsp;.058)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.71 (0.50-1.00, p\u0026thinsp;=\u0026thinsp;.052)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHF\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.66 (1.24\u0026ndash;2.22, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.31 (0.92\u0026ndash;1.88, p\u0026thinsp;=\u0026thinsp;.138)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.35 (0.96\u0026ndash;1.91, p\u0026thinsp;=\u0026thinsp;.085)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eday mortality in patients with paralytic intestinal obstruction.\u003c/p\u003e\u003cp\u003eThe results of the univariate and multivariate analyses of different lactate levels (Q1,Q2,Q3) and 28-day mortality are summarized separately in Table\u0026nbsp;4, with the same covariates included as in Table\u0026nbsp;3. When lactate levels were Q2 (1.5\u0026ndash;2.4 mmol/l,n\u0026thinsp;=\u0026thinsp;321), univariate analysis showed 1.68 (1.03\u0026ndash;2.72,p\u0026thinsp;=\u0026thinsp;.036) increased risk of death compared to Q1 (\u0026lt;\u0026thinsp;1.5 mmol/l,n\u0026thinsp;=\u0026thinsp;342), whereas in multivariate analysis this change became meaningless. When the lactate level was Q3 (\u0026gt;\u0026thinsp;2.4 mmol/l,n\u0026thinsp;=\u0026thinsp;337), a 3.33-fold(2.14\u0026ndash;5.19,p\u0026thinsp;\u0026lt;\u0026thinsp;.001) increase in the risk of death was shown in the univariate analysis and in the multivariate analysis, a 2.44-fold(1.50\u0026ndash;3.99,p\u0026thinsp;\u0026lt;\u0026thinsp;.001) increase in the risk of death was shown, when compared to Q1. It further illustrates that lactate content is significantly associated with 28-day mortality in patients with paralytic intestinal obstruction.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExposure\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eUnivariate analysis (OR, 95% CI, P)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMultivariate analysis (OR, 95% CI, P)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e28-day mortality\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLactate (mmol/l) quartiles\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1(\u0026lt;\u0026thinsp;1.5 mmol/l, n\u0026thinsp;=\u0026thinsp;342)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2(1.5\u0026ndash;2.4 mmol/l, n\u0026thinsp;=\u0026thinsp;321)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.68 (1.03\u0026ndash;2.72, p\u0026thinsp;=\u0026thinsp;.036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.26 (0.75\u0026ndash;2.13, p\u0026thinsp;=\u0026thinsp;.382)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3(\u0026gt;\u0026thinsp;2.4 mmol/l, n\u0026thinsp;=\u0026thinsp;337)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.33 (2.14\u0026ndash;5.19, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.44 (1.50\u0026ndash;3.99, p\u0026thinsp;\u0026lt;\u0026thinsp;.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.4. Predictive Performance of Lactate for 28Day Mortality\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe predictive performance of lactate and the final model for 28-day mortality in patients with paralytic bowel obstruction is summarized in A and B of Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, respectively. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA shows that the area under the ROC curve (AUC) for lactic acid was 0.650 (95% CI 0.613\u0026ndash;0.687), with an optimal threshold of 0.141, which corresponded to a specificity and sensitivity of 0.458 and 0.754, respectively. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB shows that the area under the ROC curve (AUC) of the model was 0.792 (95% CI 0.762\u0026ndash;0.822), with an optimal threshold of 0.201, corresponding to specificities and sensitivities of 0.788, and 0.673, respectively. Demonstrating the good results obtained in the prediction of 28-day mortality by both the lactate and the model.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.5. Relationship Between Lactate and 28-Day Mortality\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eWe divided all patients with paralytic intestinal obstruction into 3 groups according to tertiles of lactate levels (Q1,\u0026lt;1.5 mmol/l,n\u0026thinsp;=\u0026thinsp;504; Q2,1.5\u0026ndash;2.4 mmol/l,n\u0026thinsp;=\u0026thinsp;480; Q3,\u0026gt;2.4 mmol/l,n\u0026thinsp;=\u0026thinsp;488), and Kaplan-Meier analysis of cumulative risk of 28-day mortality is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the Q3 group had the highest risk of 28-day mortality (\u0026gt;\u0026thinsp;2.4 mmol/l) according to tertiles of lactate levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.6.Non-linear Relationship Between LAC Levels And Mortality\u003c/h2\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;5A, the RCS results indicated a non-linear relationship between lactate and the OR of 28-day mortality similar to a \u0026lsquo;J-shape\u0026rsquo; (P for Nonlinear\u0026thinsp;=\u0026thinsp;0.005), while a histogram demonstrated the distribution of the number of patients with different lactate levels. Figure\u0026nbsp;5B shows the smoothed fitted curves of lactate content and 28-day mortality, and the results likewise indicate a nonlinear relationship, with mortality showing a trend of increasing, then decreasing, then increasing as lactate content increases.\u003c/p\u003e\u003cp\u003eFigure5 Relationship Between LAC and 28-day Mortality in Patients with Paralytic Intestinal Obstruction.(A) Graphs show ORs between LAC and 28day mortality, adjusted for age, Hb, RDW, RBC, Alb, PT, BIL, BUN, RR, SpO2, AKI, HLD, HF. Data were fitted by a restricted cubic spline model, and the model was conducted with 4 knots. Solid lines indicate ORs, and shadow shapes indicate 95% CIs.The red line represents the density distribution curve.(B) Association between LAC and 28 day mortality for patients with paralytic intestinal obstruction.The solid line in the middle represents the smooth curve fitting between variables.Imaginary lines represent the 95% of confidence interval from the fit.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eIn our study, we found a nonlinear positive correlation between lactate levels and 28-day mortality in patients with paralytic bowel obstruction. In addition, the prognostic value of lactate for paralytic bowel obstruction was determined. To the best of our knowledge, this is the first MIMIC-IV-based study to explore the relationship between serum lactate levels and clinical outcomes in patients with paralytic bowel obstruction.\u003c/p\u003e\u003cp\u003eIt has been demonstrated that in patients with paralytic intestinal obstruction, a neurogenic component plays an important role, with activation of sympathetic pathways leading to widespread inhibition of gastrointestinal motility through inhibition of intestinal nerve reflex pathways[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Lactic acid or paralytic bowel obstruction has been partially investigated in previous studies. A systematic evaluation showed that inflammatory parameters including interleukin (IL)-6, IL-1, and TNF-α may be useful for early detection of prolonged paralytic bowel obstruction[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Another study, also on 28-day mortality in patients with paralytic intestinal obstruction, found a nonlinear positive correlation between erythrocyte distribution width and mortality[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], Other associated risk factors include C-reactive protein, leukocytes, mononuclear leukocytes, neutrophils, interleukin-6, and erythrocyte sedimentation rate[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e][\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], All of these indicators are valid predictors of mortality.\u003c/p\u003e\u003cp\u003eLactate can be used as an objective biomarker of tissue perfusion as an easily available and simple laboratory indicator, which is superior to urine output and physical examination[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Some previous studies have shown that lactate levels can be used to risk-stratify the severity of some diseases, and that elevated lactate levels reveal a poorer prognosis for sepsis, liver failure, cardiac arrest, and other diseases[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough lactate is important for the prognosis of numerous diseases, there are no studies on the correlation between clinical prognosis and lactate levels in patients with paralytic intestinal obstruction.The aim of our study was to explore the relationship between serum lactate and clinical outcomes in patients with paralytic intestinal obstruction based on large-scale public databases, which can be used to help physicians to risk stratify different types of patients.\u003c/p\u003e\u003cp\u003eOur study showed an OR of 1.14 (1.07\u0026ndash;1.21, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) for 28-day mortality per 1-mmol/l increase in lactate in the adjusted final model.The analysis of K-M curves for the cumulative risk of 28-day mortality in patients with different lactate levels also showed that the higher the lactate level, the higher the risk of 28-day mortality in patients with paralytic bowel obstruction. Our study suggests that in patients with paralytic bowel obstruction, physicians should pay more attention to actively measuring and monitoring his lactate level, because lactate level can reflect the patient's prognosis to some extent.\u003c/p\u003e\u003cp\u003eThe strength of this study is that physicians can risk stratify patients with paralytic bowel obstruction according to different lactate levels based on our results. However, our study has some limitations, firstly, it is a study based on a public database in the United States, and due to the lack of some data, some interventions or medications that may affect the prognosis were not included in the study, which may cause some bias. Secondly, this study is a single-center study, and the conclusions drawn may not be generally applicable to patients in other countries or regions.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eTrough analysis of the MIMIC database,In patients with paralytic intestinal obstruction, a non-linear positive relationship was discovered between serum lactate and 28-day mortality. Physicians should be alert to lactate assessment at admission and pay more attention to those patients with higher levels of lactate. More research is needed to explore further the relationship between the two.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding:\u003c/p\u003e\n\u003cp\u003eThe author(s) declare financial support was received for the research, authorship, and/or ublication of this article. This work was supported by: Research on New MALDI Source Mass Spectrometry Imaging Technology in Surgical Specimens(ZC2025004916).Research and Innovation Team Project for Scientific Breakthroughs at Shanxi Bethune Hospital (2024ZHANCHI07).Shanxi Province Basic Research Program (Free Exploration) Surface Project (Grant No: 202303021221189).Science and research fund of Shanxi Health Commission (Grant No. 2019059, 2022042, 2022043).Shanxi Scholarship Council of China (Grant No. 2021-165). Shanxi Province Science Foundation for Distinguished Young Scholar (Grant No. 201901D211547). \u0026nbsp;Shanxi Province\u0026nbsp;“136 Revitalization Medical Project Construction Funds”. National Natural Science Foundation of China for Young Scholars (Grant No. 81201810). The doctor project of Shanxi Cancer Hospital, China (2017A06). Natural Science Foundation of Guangdong Province, China (2015A030313057).\u003c/p\u003e\n\u003cp\u003eAuthor Contributions:\u003c/p\u003e\n\u003cp\u003eYH: Writing– original draft. ZW: Writing– review \u0026amp; editing. YD: Writing– review \u0026amp; editing. YPZ: Writing– review \u0026amp; editing. YW: Writing– review \u0026amp; editing. QD: Writing– review \u0026amp; editing.RG: Writing– review \u0026amp; editing. GL: Writing– review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eDisclosures:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll the authors have nothing to disclose.\u003c/p\u003e\n\u003cp\u003eCompliance with Ethics Guidelines:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments. MIMIC-IV is an anonymized public database. The project was approved by the institutional review boards of the Massachusetts Institute of Technology (MIT) and Beth Israel Deaconess Medical Center (BIDMC) and was given a waiver of informed consent.\u003c/p\u003e\n\u003cp\u003eData Availability:\u003c/p\u003e\n\u003cp\u003eThe data utilized in this investigation was sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV), which is accessible at the following link: https://mimic-iv.mit.edu. To gain access to the data, one must be an authenticated user, complete the required training, and adhere to the project’s data usage agreement. To apply for access to the database, the author (Y.H.) passed the Protecting Human Research Participants exam (No. 69397162). However, The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cstrong\u003eWattchow D, Heitmann P, Smolilo D, et al. Postoperative ileus-An ongoing conundrum. \u003cem\u003eNeurogastroenterol Motil\u003c/em\u003e. 2021;33(5):e14046. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eVather R, O\u0026apos;Grady G, Bissett IP, Dinning PG. Postoperative ileus: mechanisms and future directions for research. Clin Exp Pharmacol Physiol. 2014;41(5):358-370.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eMao H, Milne TG, O\u0026rsquo;Grady G, Vather R, Edlin R, Bissett I. Prolonged postoperative ileus significantly increases the cost of inpatient stay for patients undergoing elective colorectal surgery: results of a multivariate analysis of prospective data at a single institution. Dis Colon Rectum. 2019;62(5):631-637.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eA. H. Daniels, S. A. Ritterman, and L. E. Rubin, \u0026ldquo;Paralytic ileus in the orthopaedic patient,\u0026rdquo; J AM ACAD ORTHOP SUR, vol. 23, no. 6, pp. 365\u0026ndash;372, 2015.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eDeBerardinis RJ, et al. Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc Natl Acad Sci U S A. 2007;104(49):19345\u0026ndash;50. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eYoon S, Choi B, Eun S, Bae G, Koo C, Kim M. Using the lactate-to-albumin ratio to predict mortality in patients with sepsis or septic shock: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci. 2022;26(5):1743\u0026ndash;52.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eJouffroy R, Vivien B. Initial antimicrobial management of sepsis: increased prehospital blood lactate levels for identifying sicker patients who may\u003c/strong\u003e\u003cstrong\u003ebenefit from prehospital antibiotic therapy initiation. Crit Care. 2021;25(1):377.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eDe Backer D. Lactic acidosis. Intensive Care Med. 2003;29:699\u0026ndash;702.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eDe Backer D. Lactic acidosis. Minerva Anestesiol. \u003c/strong\u003e\u003cstrong\u003e2003;69:281\u0026ndash;284.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eNichol AD, Egi M, Pettila V, Bellomo R, French C, Hart G, Davies A, Stachowski E, Reade MC, Bailey M, Cooper DJ. Relative hyperlactatemia and hospital mortality in critically ill patients: a retrospective multi-centre study. Crit Care. 2010;14(1):R25. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eHusain FA, Martin MJ, Mullenix PS, Steele SR, Elliott DC. Serum lactate and base deficit as predictors of mortality and morbidity. Am J Surg. 2003;185:485\u0026ndash;491. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eJansen TC, van Bommel J, Woodward R, Mulder PG, Bakker J. Association between blood lactate levels, Sequential Organ Failure Assessment subscores, and 28-day mortality during early and late intensive care unit stay: a retrospective observational study. Crit Care Med. 2009;37:2369\u0026ndash;2374. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eKhosravani H, Shahpori R, Stelfox HT, Kirkpatrick AW, Laupland KB. Occurrence and adverse effect on outcome of hyperlactatemia in the critically ill. Crit Care. 2009;13:R90.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eHe L, Yang D, Ding Q, Su Y, Ding N. Association Between Lactate and 28-Day Mortality in Elderly Patients with Sepsis: Results from MIMIC-IV Database. \u003cem\u003eInfect Dis Ther\u003c/em\u003e. 2023;12(2):459-472. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eZhang M, Zhang Q, Yu Y, An L, Qi Z, Li C. Effects of early hemodynamics, oxygen metabolism, and lactate dynamics on prognosis of post-cardiac arrest syndrome. Chin Med J. 2021;135(3):344\u0026ndash;6.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGao Y, Zhang H, Zhong H, Yang S, Wang Q. Lactate and blood ammonia on admission as biomarkers to predict the prognosis of patients with acute mushroom poisoning and liver failure: a retrospective study. Toxicol Res. 2021;10(4):850\u0026ndash;5.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eJohnson A, Stone D, Celi L, Pollard T. The MIMIC code repository: enabling reproducibility in critical care research. J Am Med Inf Assoc. 2018;25(1):32\u0026ndash;9.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAustin PC, White IR, Lee DS, van Buuren S. Missing Data in Clinical Research: A Tutorial on Multiple Imputation. \u003cem\u003eCan J Cardiol\u003c/em\u003e. 2021;37(9):1322-1331. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eBauer AJ, Boeckxstaens GE. Mechanisms of postoperative ileus. Neurogastroenterol Motil. 2004;16(Suppl 2):54-60.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWu Z, Boersema GS, Dereci A, Menon AG, Jeekel J, Lange JF. Clinical endpoint, early detection, and differential diagnosis of postoperative ileus: a systematic review of the literature. \u003cem\u003eEur Surg Res\u003c/em\u003e. 2015;54(3-4):127-138. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eZhao X, Wan X, Gu C, et al. Association between Red Blood Cell Distribution Width and Short-Term Mortality in Patients with Paralytic Intestinal Obstruction: Retrospective Data Analysis Based on the MIMIC-III Database. \u003cem\u003eEmerg Med Int\u003c/em\u003e. 2023;2023:6739136. Published 2023 Oct 23. \u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eJ. C. Kalf, T. M. Carlos, W. H. Schraut, T. R. Billiar, R. L. Simmons, and A. J. Bauer, \u0026ldquo;Surgically induced leukocytic infltrates within the rat intestinal muscularis mediate postoperative ileus,\u0026rdquo; Gastroenterology, vol. 117, no. 2, pp. 378\u0026ndash;387, 1999.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eY. Sun, H. Shi, Z. Hong, and P. Chi, \u0026ldquo;Inhibition of JAK1 mitigates postoperative ileus in mice,\u0026rdquo; Surgery, vol. 166, no. 6, pp. 1048\u0026ndash;1054, 2019.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWeinberger J, Klompas M, Rhee C. What is the utility of measuring lactate levels in patients with sepsis and septic shock? Sem Respir Crit Care Med. 2021;42(5):650\u0026ndash;61.\u003c/strong\u003e\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":"Lactate, Mortality, Paralytic Intestinal Obstruction, MIMIC-IV","lastPublishedDoi":"10.21203/rs.3.rs-7867124/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7867124/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction:\u003c/p\u003e\n\u003cp\u003eThe aim of this study was to investigate the relationship between serum lactate and clinical outcomes in patients with paralytic intestinal obstruction based on data from the MIMIC-IV database. Currently, elevated serum lactate levels have been reported to be associated with mortality in diseases such as sepsis and liver failure. However, there is a lack of evidence on the relationship between lactate and paralytic bowel obstruction, therefore, the aim of this paper is to investigate the relationship between lactate and 28-day mortality in patients with paralytic bowel obstruction.\u003c/p\u003e\n\u003cp\u003eMethods:\u003c/p\u003e\n\u003cp\u003eThis was a single-center retrospective study. Based on specific screening criteria, 1472 patients with paralytic bowel obstruction were selected from the Medical Information Marketplace in Critical Care IV (MIMIC-IV) database. Inclusion criteria: ICD diagnosis codes=k56,k560,k567,5601. exclusion criteria: 1.days of survival on admission≤1 day; 2. various malignant tumors; 3. age≤18; 4. not the first ICU admission; 5. length of ICU stay≤1 day; 6. missing lactate data. Different models were constructed to explore the relationship between lactate and 28 d mortality.\u003c/p\u003e\n\u003cp\u003eResults:\u003c/p\u003e\n\u003cp\u003eA total of 1472 patients with paralytic bowel obstruction were included. 28-day mortality was 16.85% (n = 248). After screening the variables using Lasso regression, all the variables obtained were included in a logistic regression model, and a one-way logistic regression showed that the ratio of the odds ratios (OR) for 28-day mortality per 1 mmol/l increase in lactate was 1.21 (95% CI 1.14-1.28, p \u0026lt; 0.001). Significant variables obtained from univariate logistic regression were incorporated into multivariate logistic regression, and the final model showed that lactate was an independent risk factor for predicting 28-day mortality, with an odds ratio (OR) of 1.14 (95% CI 1.07-1.21, P \u0026lt; 0.001) for each 1 mmol/l increase in lactate. The area under the ROC curve (AUC) was 0.65 for lactate and 0.792 for the final model.The RCS model and the smoothed fitted curves showed a nonlinear positive correlation between lactate and 28-day mortality.The K-M curves showed that the group with higher values of LAC had a lower survival rate.\u003c/p\u003e\n\u003cp\u003eConclusion:\u003c/p\u003e\n\u003cp\u003eElevated LAC is associated with increased 28-day mortality in ICU paralytic bowel obstruction. This study helps to further explore the relationship between LAC and mortality in patients with paralytic bowel obstruction.\u003c/p\u003e","manuscriptTitle":"Higher Lactate Levels Increased Risk Of 28-Day Mortality In Patients With Paralytic Intestinal Obstruction: A Retrospective Data Analysis Based On MIMIC-Ⅳ Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 08:14:25","doi":"10.21203/rs.3.rs-7867124/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"208072335196518333875439318840231588855","date":"2025-11-22T12:48:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283963786202600324635004092593613945260","date":"2025-11-19T12:41:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90760378878724407581036261227223892600","date":"2025-11-17T19:08:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-10T20:15:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-19T18:54:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-17T02:58:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-17T02:55:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-10-15T10:27:05+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":"ee30ed46-299e-4fe3-ae77-7472e8d5e3d2","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-20T08:14:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 08:14:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7867124","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7867124","identity":"rs-7867124","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}