Yang DJ, Li M, Yue C, Hu WM, Lu HM. Development and validation of a prediction model for deep vein thrombosis in older non-mild acute pancreatitis patients. World J Gastrointest Surg 2021; 13(10): 1258-1266 [PMID: 34754393 DOI: 10.4240/wjgs.v13.i10.1258]
Corresponding Author of This Article
Hui-Min Lu, PhD, Professor, Department of Pancreatic Surgery, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, Sichuan Province, China. hm.lu@scu.edu.cn
Research Domain of This Article
Peripheral Vascular Disease
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastrointest Surg. Oct 27, 2021; 13(10): 1258-1266 Published online Oct 27, 2021. doi: 10.4240/wjgs.v13.i10.1258
Development and validation of a prediction model for deep vein thrombosis in older non-mild acute pancreatitis patients
Du-Jiang Yang, Mao Li, Chao Yue, Wei-Ming Hu, Hui-Min Lu
Du-Jiang Yang, Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Mao Li, Chao Yue, Wei-Ming Hu, Hui-Min Lu, Department of Pancreatic Surgery, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Author contributions: Yang DJ, Li M, and Lu HM contributed to conception and design; Yang DJ, Li M, Yue C, and Hu WM contributed to collection and analysis data; Yang DJ wrote the manuscript; Lu HM revised the manuscript.
Supported byThe Sichuan Provincial Department of Science and Technology Supporting Project, No. 2018SZ0381; and 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University, No. ZYJC18027.
Institutional review board statement: This study was reviewed and approved by the Institutional Ethics Committee of the West China Hospital.
Informed consent statement: For retrospective study, informed consent was waived according to our institutional guideline.
Conflict-of-interest statement: There are no conflicts of interest to disclose.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hui-Min Lu, PhD, Professor, Department of Pancreatic Surgery, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, Sichuan Province, China. hm.lu@scu.edu.cn
Received: May 20, 2021 Peer-review started: May 20, 2021 First decision: June 22, 2021 Revised: July 1, 2021 Accepted: September 19, 2021 Article in press: September 19, 2021 Published online: October 27, 2021 Processing time: 158 Days and 20.1 Hours
ARTICLE HIGHLIGHTS
Research background
Deep 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.
Research motivation
There is a lack of a scoring model for predicting the development of DVT in NMAP patients.
Research objectives
We aimed to develop a prediction model for DVT in old NMAP patients.
Research methods
Univariate and multivariate logistic regression analyses were used to select independent risk factors associated with DVT. The selected risk factors were included in the nomogram. A validation set was constructed using bootstrapping with 100 resamplings. The accuracy and utility of the nomogram were evaluated by calibration curve and decision curve analysis, respectively.
Research results
Eighty DVT patients and 140 non-DVT patients were included in this study. Eight factors including age, sex, surgery times, D-dimer, neutrophils, any organ failure, blood culture, and classification constitute the prediction model. 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 set, respectively.
Research conclusions
A reliable and effective nomogram model that can predict DVT in old patients with NMAP was constructed.
Research perspectives
The usability of the new model needs further validation by other center data.
