ArticleJournal of thoracic disease2023
Risk assessment for postoperative venous thromboembolism using the modified Caprini risk assessment model in lung cancer.
Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 4 of them syntheses that pooled it.
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Who cites it
6 citing papers in PubMed, 4 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Risk prediction models for venous thromboembolism in lung cancer patients after surgery: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Postoperative venous thromboembolism risk following lung cancer surgery: a systematic review and meta-analysis.Journal of thrombosis and thrombolysis · 2025Pooled it
- Impact of extended reality on robot-assisted surgery training: a systematic review and meta-analysis.Journal of robotic surgery · 2025Pooled it
- Risk factors for postoperative venous thromboembolism in patients with lung cancer: a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Combined assessment of Caprini score, D-dimer, and thromboelastography for predicting deep venous thrombosis in lung cancer patients.American journal of cancer research · 2025Article
- Integrating D-Dimer Thresholds into the Revised Caprini Risk Stratification to Predict Deep Vein Thrombosis Risk in Preoperative Knee Osteoarthritis Patients.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
Corrections and comments
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Authors and funding
14 authors at 6 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Postoperative venous thromboembolism (VTE) is a well-documented cause of morbidity and mortality in lung cancer patients. However, risk identification remains limited. In this study, we sought to analyze the risk factors for VTE and verify the predictive value of the modified Caprini risk assessment model (RAM). Methods: This prospective single-center study included patients with resectable lung cancer who underwent resection between October 2019 and March 2021. The incidence of VTE was estimated. Logistic regression was used to analyze the risk factors for VTE. Receiver operating characteristic (ROC) curve analysis was performed to test the ability of the modified Caprini RAM to predict VTE. Results: The VTE incidence was 10.5%. Several variables, including age, D-dimer, hemoglobin (Hb), bleeding, and patient confinement to bed were significantly associated with VTE after surgery. The difference between the VTE and non-VTE groups in the high-risk levels was statistically significant (P<0.001), while the low and moderate risk levels showed no significant difference. The combined use of the modified Caprini score and the Hb and D-dimer levels showed an area under the curve (AUC) was 0.822 [95% confidence interval (CI): 0.760-0.855. P<0.001]. Conclusions: The risk-stratification approach of the modified Caprini RAM is not particularly valid after lung resection in our population. The use of the modified Caprini RAM combined with Hb and D-dimer levels shows a good diagnostic performance for VTE prediction in patients with lung cancer undergoing resection.
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