Establishment and diagnostic value analysis of an early prediction model for acute pancreatitis complicated with acute kidney injury based on triglyceride-glucose index and procalcitonin
10.3760/cma.j.issn.1671-0282.2024.09.005
- VernacularTitle:基于甘油三酯-葡萄糖指数和降钙素原的急性胰腺炎并发急性肾损伤早期预测模型的建立及诊断价值分析
- Author:
Cheng CHI
1
;
Yong MA
;
Xiaojing SONG
;
Chunyu WANG
;
Jihong ZHU
Author Information
1. 北京大学人民医院急诊科，北京 100044
- Keywords:
Acute pancreatitis;
Acute kidney injury;
Triglyceride-glucose index;
Prediction model;
Diagnostic value
- From:
Chinese Journal of Emergency Medicine
2024;33(9):1242-1248
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish an early prediction model based on triglyceride glucose index (TyG) and procalcitonin (PCT) for patients of acute pancreatitis (AP) complicated with acute kidney injury (AKI), and evaluate the diagnostic value of prediction model.Methods:This study was a single center prospective study. AP patients were recruited from the Emergency Department at Peking University People’s Hospital from January to December 2022. The observation endpoint was 14 days after the diagnosis of acute pancreatitis, patients were divided into AKI and control (no AKI) groups according to the observation endpoint. The general characteristics, clinical laboratory examinations, complications, and clinical scores were compared. The risk for AKI development was determined using logistic analyses to establish a risk prediction model. The receiver operating characteristic curve was drawn and the area under the curve (AUC) was calculated. The diagnostic sensitivity and specificity of the model were calculated, and the diagnostic value of the model was compared with that of Ranson score, APACHEⅡ score and BISAP score.Results:A total of 258 patients were selected for this study, including 79 in the AKI group and 179 in the control group. There was no significant difference in serum creatinine and blood urea nitrogen levels between the two groups. Compared with the control group, the AKI group had a higher proportion of males, older age, and had a higher proportion of hypertension. The ratio of neutrophil/lymphocyte ratio, PCT, and TyG were significantly increased. The Ranson score, APACHE Ⅱ score, and BISAP score were higher, and more patients had ARDS and serous fluid accumulation in the later period. Multivariate logistic regression showed that age ( OR=1.071, 95% CI: 1.020-1.125, P=0.006), increased TyG index ( OR=2.632, 95% CI: 1.423-4.866, P=0.002), and elevated PCT ( OR=1.275, 95% CI: 1.067-1.524, P=0.008) were risk factors for AKI in AP patients. According to the risk factors, forecast the AP patients complicated with AKI risk assessment model is established: Logistic (AKI/AP) = -16.697+0.069×age+ 0.968×TyG+0.243×PCT. The sensitivity and specificity of the model for predicting AKI in AP were 79.75% and 96.65%, respectively, and the AUC was 0.856 (95% CI: 0.790-0.922). The predictive ability was better than that of Ranson score, BISAP score and APACHE Ⅱ score (AUC: 0.856 vs. 0.691 vs. 0.745 vs. 0.705, P=0.041). Conclusion:The prediction model based on age, TyG and PCT was valuable for the prediction of AP concurrent AKI in early stage.
