Objective:To explore the early predictive value of the triglyceride-glucose (TyG) index and the controlling nutritional status (CONUT) score for severe acute pancreatitis (SAP).Methods:Clinical data from 1 050 hospitalized patients with acute pancreatitis (AP) at the General Hospital of Central Theater Command between January 2019 and December 2023 were retrospectively analyzed. Patients were categorized into mild acute pancreatitis (MAP) group ( n=606), moderately severe acute pancreatitis (MSAP) group ( n=320), and SAP group ( n=124) based on AP severity. General clinical data, laboratory parameters, modified computed tomography severity index (MCTSI), bedside index for severity in acute pancreatitis (BISAP), TyG index, and CONUT score were compared among the three groups. Spearman correlation analysis was used to evaluate the relationship between TyG index, CONUT score and AP severity. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for AP severity. Receiver operating characteristic curves (ROC) were plotted to calculate the area under the curve (AUC), sensitivity, and specificity for evaluating the predictive efficacy of TyG index, CONUT score, and their combination for SAP. Results:Significant differences on TyG index and CONUT score were observed among AP patients with varying severity (all P value <0.001). Spearman correlation analysis further revealed positive correlations of TyG index ( r=0.174), CONUT score ( r=0.306) with AP severity (both P<0.001). Multivariate logistic regression identified neutrophil count ( OR=1.076, 95% CI 1.027-1.125), MCTSI ( OR=2.565, 95% CI 2.250-2.921), BISAP ( OR=3.522, 95% CI 2.726-4.549), TyG index ( OR=1.859, 95% CI 1.276-2.707), and CONUT score ( OR=1.155, 95% CI 1.035-1.288) as independent risk factors for AP severity. The combined predictive model equation was: -7.342+0.76×TyG+0.439×CONUT. ROC analysis showed that the AUC values of the TyG index, CONUT score, and the combined index (TyG index+CONUT score) were 0.583 (95% CI 0.529-0.637), 0.701 (95% CI 0.652-0.75), and 0.755 (95% CI 0.710-0.801), with sensitivities of 0.706, 0.677, and 0.742, and specificities of 0.884, 0.629, and 0.657, respectively (all P value <0.05). Conclusions:TyG index and CONUT score are positively correlated with AP severity and may serve as reliable predictors for SAP. Their combination could enhance the predictive accuracy for AP.

Objective:To explore the early predictive value of the triglyceride-glucose (TyG) index and the controlling nutritional status (CONUT) score for severe acute pancreatitis (SAP).Methods:Clinical data from 1 050 hospitalized patients with acute pancreatitis (AP) at the General Hospital of Central Theater Command between January 2019 and December 2023 were retrospectively analyzed. Patients were categorized into mild acute pancreatitis (MAP) group ( n=606), moderately severe acute pancreatitis (MSAP) group ( n=320), and SAP group ( n=124) based on AP severity. General clinical data, laboratory parameters, modified computed tomography severity index (MCTSI), bedside index for severity in acute pancreatitis (BISAP), TyG index, and CONUT score were compared among the three groups. Spearman correlation analysis was used to evaluate the relationship between TyG index, CONUT score and AP severity. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for AP severity. Receiver operating characteristic curves (ROC) were plotted to calculate the area under the curve (AUC), sensitivity, and specificity for evaluating the predictive efficacy of TyG index, CONUT score, and their combination for SAP. Results:Significant differences on TyG index and CONUT score were observed among AP patients with varying severity (all P value <0.001). Spearman correlation analysis further revealed positive correlations of TyG index ( r=0.174), CONUT score ( r=0.306) with AP severity (both P<0.001). Multivariate logistic regression identified neutrophil count ( OR=1.076, 95% CI 1.027-1.125), MCTSI ( OR=2.565, 95% CI 2.250-2.921), BISAP ( OR=3.522, 95% CI 2.726-4.549), TyG index ( OR=1.859, 95% CI 1.276-2.707), and CONUT score ( OR=1.155, 95% CI 1.035-1.288) as independent risk factors for AP severity. The combined predictive model equation was: -7.342+0.76×TyG+0.439×CONUT. ROC analysis showed that the AUC values of the TyG index, CONUT score, and the combined index (TyG index+CONUT score) were 0.583 (95% CI 0.529-0.637), 0.701 (95% CI 0.652-0.75), and 0.755 (95% CI 0.710-0.801), with sensitivities of 0.706, 0.677, and 0.742, and specificities of 0.884, 0.629, and 0.657, respectively (all P value <0.05). Conclusions:TyG index and CONUT score are positively correlated with AP severity and may serve as reliable predictors for SAP. Their combination could enhance the predictive accuracy for AP.

Objective To investigate the correlation between atherogenic index of plasma (AIP) and the severity of hypertriglyceridemic acute pancreatitis (HTG-AP) and the value of AIP combined with Bedside Index for Severity in Acute Pancreatitis (BISAP) score in the early prediction of severe HTG-AP (sHTG-AP). Methods A retrospective analysis was performed for the clinical data of 170 patients with HTG-AP who were hospitalized in The General Hospital of Central Theater Command from January 2017 to December 2021, and according to related guidelines, they were divided into the sHTG-AP group with 28 patients and non-sHTG-AP group with 142 patients. Peripheral blood samples were collected from all patients within 24 hours after admission, and the two groups were compared in terms of sex, age, laboratory test results, AIP, BISAP score, and modified CT severity index (MCTSI) score. The chi-square test or the Fisher's exact test was used for comparison of categorical data between groups; the Mann-Whitney U test was used for comparison of continuous data between groups. The Spearman rank correlation test was used to investigate the correlation between each factor and the severity of HTG-AP, and the binary logistic regression analysis were used to investigate the independent risk factors for sHTG-AP. The receiver operating characteristic (ROC) curve was plotted to assess the predictive efficacy of each indicator. Results There were significant differences between the two groups in the medical history of diabetes, lymphocyte count, albumin, Ca 2+ , triglyceride, high-density lipoprotein cholesterol, AIP, BISAP score, MCTSI score, length of hospital stay, and hospital costs (all P < 0.05). The sHTG-AP group had a longer length of hospital stay, higher hospital costs, and a higher AIP value. AIP (odds ratio [ OR ]=1.244, 95% confidence interval [ CI ]: 1.062-1.458, P =0.007), BISAP score ( OR =5.525, 95% CI : 1.646-18.543, P =0.006), and MCTSI score ( OR =2.029, 95% CI : 1.245-3.305, P =0.004) were risk factors for sHTG-AP. AIP, BISAP score, and MCTSI score were positively correlated with the severity of HTG-AP ( r =0.291, 0.631, and 0.649, all P < 0.001), and AIP was positively correlated with BISAP score and MCTSI score ( r =0.190 and 0.215, both P < 0.05). AIP had an optimal cut-off value of 1.095 in predicting sHTG-AP, and AIP, BISAP score, and AIP combined with BISAP score had an area under the ROC curve of 0.759, 0.887, 0.925, respectively, a sensitivity of 0.821, 0.857, and 0.786, respectively, and a specificity of 0.627, 0.817, and 0.937, respectively (all P < 0.001). Conclusion AIP is a risk factor for sHTG-AP and is correlated with disease severity, and AIP combined with BISAP score has a relatively high value in the early prediction of sHTG-AP.