Objective Early prediction of the severity of acute pancreatitis (AP) is crucial for clinical decision-making and for improving patient outcomes. In this study, readily available laboratory data and Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to select key variables and construct a nomogram for accurate severity prediction in AP patients.
Methods We retrospectively analyzed the clinical data of 965 adult AP patients hospitalized at a hospital between January 2017 and December 2019. LASSO regression was used to identify significant predictors of severe acute pancreatitis (SAP), and a nomogram prediction model was constructed. The performance of the nomogram was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, the calibration curve, and the decision curve analysis (DCA).
Results Among the 965 patients, the incidence of SAP was 15.96% (n = 154). Eight independent predictors were identified: C-reactive protein, lactate dehydrogenase, hematocrit, monocyte percentage, prothrombin time, D-dimer, glucose, and total cholesterol. These predictive factors were incorporated into a nomogram model, which demonstrated favorable discriminative ability, with AUC values of 0.809 in the training cohort and 0.768 in the validation cohort. The clinical utility of the model was further supported by satisfactory calibration and positive net benefits of DCA.
Conclusion The proposed nomogram was highly discriminative in predicting AP severity, indicating its potential clinical value for risk stratification.
| [1] |
Petrov MS, Yadav D. Global epidemiology and holistic prevention of pancreatitis. Nat Rev Gastroenterol Hepatol., 2019, 16(3): 175-184
|
| [2] |
Trikudanathan G, Wolbrink DRJ, van Santvoort HC, et al. . Current concepts in severe acute and necrotizing pancreatitis: an evidence-based approach. Gastroenterology., 2019, 156(7): 1994-2007.e3
|
| [3] |
Yang K, Song Y, Su Y, et al. . Establishment and validation of an early predictive model for severe acute pancreatitis. J Inflamm Res., 2024, 17: 3551-3561
|
| [4] |
Chen Y, Liu J, Ge Q, et al. . A risk nomogram for 30-day mortality in Chinese patients with acute pancreatitis using LASSO-logistic regression. Sci Rep., 2025, 15: 17097
|
| [5] |
Li R, Zhang Y, Li R, et al. . Establishment and validation of a prediction model for the severity of acute pancreatitis. Chin J Dig., 2021, 41(08): 554-560
|
| [6] |
Leppäniemi A, Tolonen M, Tarasconi A, et al. . 2019 WSES guidelines for the management of severe acute pancreatitis. World J Emerg Surg., 2019, 14(1): 27
|
| [7] |
Cui J, Xiong J, Zhang Y, et al. . Serum lactate dehydrogenase is predictive of persistent organ failure in acute pancreatitis. J Crit Care., 2017, 41: 161-165
|
| [8] |
Yi S, Zeng H, Lin X, et al. . Establishment and validation of early prediction model for hypertriglyceridemic severe acute pancreatitis. Lipids Health Dis., 2023, 22(1): 218
|
| [9] |
Tian F, Li H, Wang L, et al. . The diagnostic value of serum C-reactive protein, procalcitonin, interleukin-6 and lactate dehydrogenase in patients with severe acute pancreatitis. Clin Chim Acta., 2020, 510: 665-670
|
| [10] |
Song YX, Chen ST, Zhao YT, et al. . Nomogram for the prediction of infected pancreatic necrosis in moderately severe and severe acute pancreatitis. J Dig Dis., 2024, 25(4): 238-247
|
| [11] |
Hayakawa M, Seki Y, Ikezoe T, et al. . Correction: Clinical practice guidelines for management of disseminated intravascular coagulation in Japan 2024: part 4—trauma, burn, obstetrics, acute pancreatitis/liver failure, and others. Int J Hematol., 2025, 121(5): 718-719
|
| [12] |
Zheng J, Fan J, Huang C, et al. . Dynamic detection of monocyte subsets in peripheral blood of patients with acute hypertriglyceridemic pancreatitis. Gastroenterol Res Pract., 2019, 2019: 5705782
|
| [13] |
Zhang ML, Jiang YF, Wang XR, et al. . Different phenotypes of monocytes in patients with new-onset mild acute pancreatitis. World J Gastroenterol., 2017, 23(8): 1477-1488
|
| [14] |
Deng H, Yu X, Gao K, et al. . Dynamic nomogram for predicting thrombocytopenia in adults with acute pancreatitis. J Inflamm Res., 2021, 14: 6657-6667
|
| [15] |
Gao X, Xu J, Xu M, et al. . Nomogram and web calculator based on lasso-logistic regression for predicting persistent organ failure in acute pancreatitis patients. J Inflamm Res., 2024, 17: 823-836
|
| [16] |
Zhou CL, Zhang CH, Zhao XY, et al. . Early prediction of persistent organ failure by serum apolipoprotein A-I and high-density lipoprotein cholesterol in patients with acute pancreatitis. Clin Chim Acta., 2018, 476: 139-145
|
| [17] |
Zhang Y, Guo F, Li S, et al. . Decreased high density lipoprotein cholesterol is an independent predictor for persistent organ failure, pancreatic necrosis and mortality in acute pancreatitis. Sci Rep., 2017, 7(1): 8064
|
| [18] |
Hong W, Lin S, Zippi M, et al. . High-density lipoprotein cholesterol, blood urea nitrogen, and serum creatinine can predict severe acute pancreatitis. Biomed Res Int., 2017, 2017: 1648385
|
| [19] |
Hong W, Zimmer V, Basharat Z, et al. . Association of total cholesterol with severe acute pancreatitis: a U-shaped relationship. Clin Nutr., 2020, 39(1): 250-257
|
| [20] |
Chen Y, Li Q, Ma L, et al. . Development and internal validation of a practical model to predict 30 days mortality of severe acute pancreatitis patients. Ann Med., 2023, 55(1): 2236648
|
| [21] |
Dunn FL. Hyperlipidemia and diabetes. Med Clin N Am., 1982, 66(6): 1347-1360
|
| [22] |
Liu Y, Qin S, Dai S, et al. . The effect of blood glucose levels on serum triglyceride clearance in patients with hyperlipidemic acute pancreatitis. Sci Rep., 2025, 15: 2647
|
Funding
Jiangsu Province Association of Maternal and Child Health(FYX202303)
Jiangsu women and children health hospital (FYRC202017)
RIGHTS & PERMISSIONS
The Author(s), under exclusive licence to the Huazhong University of Science and Technology
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