109906
论文已发表
注册即可获取德孚的最新动态
IF 收录期刊
- 3.4 Breast Cancer (Dove Med Press)
- 3.2 Clin Epidemiol
- 2.6 Cancer Manag Res
- 2.9 Infect Drug Resist
- 3.7 Clin Interv Aging
- 5.1 Drug Des Dev Ther
- 3.1 Int J Chronic Obstr
- 6.6 Int J Nanomed
- 2.6 Int J Women's Health
- 2.9 Neuropsych Dis Treat
- 2.8 OncoTargets Ther
- 2.0 Patient Prefer Adher
- 2.2 Ther Clin Risk Manag
- 2.5 J Pain Res
- 3.0 Diabet Metab Synd Ob
- 3.2 Psychol Res Behav Ma
- 3.4 Nat Sci Sleep
- 1.8 Pharmgenomics Pers Med
- 2.0 Risk Manag Healthc Policy
- 4.1 J Inflamm Res
- 2.0 Int J Gen Med
- 3.4 J Hepatocell Carcinoma
- 3.0 J Asthma Allergy
- 2.2 Clin Cosmet Investig Dermatol
- 2.4 J Multidiscip Healthc
已发表论文
胸外科手术术后肺栓塞的手术及凝血危险因素整合预测：一项多中心回顾性研究
Authors Li J, Wang X, Mei L, Liu Q, Dai F, Zhou J, Chen J
Received 13 July 2025
Accepted for publication 21 October 2025
Published 8 November 2025 Volume 2025:18 Pages 6821—6832
DOI https://doi.org/10.2147/IJGM.S548989
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Woon-Man Kung
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 China
Correspondence: 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.com
Introduction: 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
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 China
Correspondence: 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.com
Introduction: 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