Development and validation of a prediction model for deep vein thrombosis in older non-mild acute pancreatitis patients

• Published in: World journal of gastrointestinal surgery Vol. 13; no. 10; pp. 1258 - 1266
• Main Authors: Yang, Du-Jiang, Li, Mao, Yue, Chao, Hu, Wei-Ming, Lu, Hui-Min
• Format: Journal Article
• Language: English
• Published: Baishideng Publishing Group Inc 27.10.2021
• Subjects: Retrospective Study
• ISSN: 1948-9366; 1948-9366
• DOI: 10.4240/wjgs.v13.i10.1258

BACKGROUNDDeep vein thrombosis (DVT) may cause pulmonary embolus, leading to late deaths. The systemic inflammatory and hypercoagulable state of moderate and severe acute pancreatitis (non-mild acute pancreatitis, NMAP) patients may contribute to the development of venous thromboembolism. Accurate prediction of DVT is conducive to clinical decisions. AIMTo develop and validate a potential new prediction nomogram model for the occurrence of DVT in NMAP. METHODSNMAP patient admission between 2013.1.1 and 2018.12.31 at the West China Hospital of Sichuan University was collected. A total of 220 patients formed the training set for nomogram development, and a validation set was constructed using bootstrapping with 100 resamplings. Univariate and multivariate logistic regression analyses were used to estimate independent risk factors associated with DVT. The independent risk factors were included in the nomogram. The accuracy and utility of the nomogram were evaluated by calibration curve and decision curve analysis, respectively. RESULTSA total of 220 NMAP patients over 60 years old were enrolled for this analysis. DVT was detected in 80 (36.4%) patients. The final nomogram included age, sex, surgery times, D-dimer, neutrophils, any organ failure, blood culture, and classification. This model achieved good concordance indexes of 0.827 (95%CI: 0.769-0.885) and 0.803 (95%CI: 0.743-0.860) in the training and validation sets, respectively. CONCLUSIONWe developed and validated a prediction nomogram model for DVT in older patients with NMAP. This may help guide doctors in making sound decisions regarding the administration of DVT prophylaxis.