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Integration of Surgical and Coagulation Risk Factors for Predicting Postoperative Pulmonary Embolism in Thoracic Surgery: A Multi-Center Retrospective Study

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Title: Integration of Surgical and Coagulation Risk Factors for Predicting Postoperative Pulmonary Embolism in Thoracic Surgery: A Multi-Center Retrospective Study
Authors: Li J, Wang X, Mei L, Liu Q, Dai F, Zhou J, Chen J
Source: International Journal of General Medicine, Vol 18, Iss Issue 1, Pp 6821-6832 (2025)
Publisher Information: Dove Medical Press, 2025.
Publication Year: 2025
Collection: LCC:Medicine (General)
Subject Terms: postoperative pulmonary embolism, risk predictive model, pulmonary resection, coagulation biomarkers, multi-center study, Medicine (General), R5-920
Description: Jianfeng Li,1 Xintian Wang,2 Longyong Mei,2 Qingsong Liu,2 Fuqiang Dai,2 Jie Zhou,3 Junying Chen2 1Department of Cardiothoracic Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Department of Thoracic Surgery, Daping Hospital, Army Medical University, Chongqing, People’s Republic of China; 3Department of General Surgery, the Traditional Chinese Medicine Hospital of Shizhu, Chongqing, People’s Republic of ChinaCorrespondence: Junying Chen, Department of Thoracic Surgery, Daping Hospital, Army Medical University, Chongqing, 400042, People’s Republic of China, Email chenjunyingdp@163.com Jie Zhou, Department of General Surgery, the Traditional Chinese Medicine Hospital of Shizhu, Chongqing, 409100, People’s Republic of China, Email mfksoldyl@163.comIntroduction: Postoperative pulmonary embolism (PE) is a severe and potentially fatal complication following thoracic surgery. Existing prediction methods often lack accuracy and timeliness. This study aimed to develop an early and reliable multifactorial prediction model for PE using multicenter data to identify high-risk patients.Methods: We retrospectively analyzed data from 977 patients who underwent pulmonary surgery at three medical centers. Independent risk factors for PE were identified, and a logistic regression model was constructed and validated both internally and externally.Results: Significant predictors included older age, upper lobe lesions, open thoracic surgery, longer surgical duration, greater intraoperative blood loss, and elevated D-dimer and fibrinogen levels. The model demonstrated excellent discrimination, with AUC values of 0.97, 0.95, and 0.94 in the training, internal validation, and external validation sets, respectively. Calibration curves showed strong consistency between predicted and observed outcomes (p > 0.05). In the external validation cohort, risk stratification based on the 85th percentile of estimated risk effectively distinguished between high-risk and low-risk groups.Conclusion: This predictive model, integrating surgical and coagulation related factors, shows strong potential for early PE detection and clinical utility. Further prospective studies are warranted to confirm its effectiveness in improving patient outcomes.Keywords: postoperative pulmonary embolism, risk predictive model, pulmonary resection, coagulation biomarkers, multi-center study
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1178-7074
Relation: https://www.dovepress.com/integration-of-surgical-and-coagulation-risk-factors-for-predicting-po-peer-reviewed-fulltext-article-IJGM; https://doaj.org/toc/1178-7074
Access URL: https://doaj.org/article/52f33d76615940f0b94acb22fa40a1b5
Accession Number: edsdoj.52f33d76615940f0b94acb22fa40a1b5
Database: Directory of Open Access Journals
Description
Abstract:Jianfeng Li,1 Xintian Wang,2 Longyong Mei,2 Qingsong Liu,2 Fuqiang Dai,2 Jie Zhou,3 Junying Chen2 1Department of Cardiothoracic Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Department of Thoracic Surgery, Daping Hospital, Army Medical University, Chongqing, People’s Republic of China; 3Department of General Surgery, the Traditional Chinese Medicine Hospital of Shizhu, Chongqing, People’s Republic of ChinaCorrespondence: Junying Chen, Department of Thoracic Surgery, Daping Hospital, Army Medical University, Chongqing, 400042, People’s Republic of China, Email chenjunyingdp@163.com Jie Zhou, Department of General Surgery, the Traditional Chinese Medicine Hospital of Shizhu, Chongqing, 409100, People’s Republic of China, Email mfksoldyl@163.comIntroduction: Postoperative pulmonary embolism (PE) is a severe and potentially fatal complication following thoracic surgery. Existing prediction methods often lack accuracy and timeliness. This study aimed to develop an early and reliable multifactorial prediction model for PE using multicenter data to identify high-risk patients.Methods: We retrospectively analyzed data from 977 patients who underwent pulmonary surgery at three medical centers. Independent risk factors for PE were identified, and a logistic regression model was constructed and validated both internally and externally.Results: Significant predictors included older age, upper lobe lesions, open thoracic surgery, longer surgical duration, greater intraoperative blood loss, and elevated D-dimer and fibrinogen levels. The model demonstrated excellent discrimination, with AUC values of 0.97, 0.95, and 0.94 in the training, internal validation, and external validation sets, respectively. Calibration curves showed strong consistency between predicted and observed outcomes (p > 0.05). In the external validation cohort, risk stratification based on the 85th percentile of estimated risk effectively distinguished between high-risk and low-risk groups.Conclusion: This predictive model, integrating surgical and coagulation related factors, shows strong potential for early PE detection and clinical utility. Further prospective studies are warranted to confirm its effectiveness in improving patient outcomes.Keywords: postoperative pulmonary embolism, risk predictive model, pulmonary resection, coagulation biomarkers, multi-center study
ISSN:11787074