Development and validation of a nomogram to predict massive bleeding requiring intervention in severe acute pancreatitis

Xiao-Yu Guo; Fan Xiao; Jie Hu; Hui Lin; Zi-Jian Huang; Liang Zhang; Long Cheng; Gang Wang

doi:10.1016/j.hbpd.2025.06.004

Development and validation of a nomogram to predict massive bleeding requiring intervention in severe acute pancreatitis

Hepatobiliary Pancreat Dis Int. 2025 Jun 18:S1499-3872(25)00100-6. doi: 10.1016/j.hbpd.2025.06.004. Online ahead of print.

Authors

Xiao-Yu Guo¹, Fan Xiao², Jie Hu³, Hui Lin⁴, Zi-Jian Huang¹, Liang Zhang¹, Long Cheng¹, Gang Wang⁵

Affiliations

¹ Department of Pancreatic and Biliary Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China; Department of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
² Department of Hepatobiliary Surgery, Suining Central Hospital, Suining 629000, China.
³ Central Operating Room, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
⁴ Department of Internal Medicine, The Second Affiliated Hospital of Shanxi Medical University, Taiyuan 030001, China.
⁵ Department of Pancreatic and Biliary Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China; Department of Oncology and Laparoscopy Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China. Electronic address: wgilu79@163.com.

PMID: 40581589
DOI: 10.1016/j.hbpd.2025.06.004

Abstract

Background: Hemorrhage remains a formidable complication of severe acute pancreatitis (SAP), with a high mortality rate. However, there is currently no effective method for identifying SAP patients who are at high risk for massive bleeding. The present study aimed to explore risk factors for predicting massive bleeding in SAP patients and to develop a predictive nomogram, which could facilitate early prediction, and timely appropriate interventions.

Methods: We conducted a multivariate logistic regression analysis to examine the relationship between massive bleeding and variables including patient demographics, disease severity, laboratory indexes and local pancreatic complications. A novel nomogram was constructed based on these factors, and was validated both internally and externally assessing its discrimination, calibration, and clinical applicability.

Results: The study involved 351 patients in the training cohort, 104 patients in the internal validation cohort, and 123 patients in the external validation cohort. Logistic regression analysis identified several independent risk factors for massive bleeding, including computed tomography severity index score above 8 points, Acute Physiology and Chronic Health Evaluation II score greater than 16 points, abdominal compartment syndrome, pancreatic fistula, and sepsis. The nomogram constructed from these factors yielded an area under the receiver operating characteristic curve (AUC) of 0.896 and a coefficient of determination (R²) of 0.093. The Hosmer-Lemeshow test indicated good model fitness (P = 0.654). Furthermore, the nomogram demonstrated reliable performance in both validation cohorts.

Conclusions: The nomogram showed strong predictive capability for massive bleeding and could be a valuable tool for clinicians in identifying SAP patients at high risk for this complication at an early stage.

Keywords: Intervention; Massive bleeding; Prediction model; Severe acute pancreatitis.