Key result
Multifactorial risk model predicts postoperative PE in thoracic surgery with an AUC of ~0.97.
Why the study?
Postoperative pulmonary embolism is a severe complication after thoracic surgery, but existing prediction methods often lack accuracy and timeliness.
Cohort (n=977)
Yes
Effect estimate: AUC 0.97 (95% CI 0.95-0.99)
A multifactorial prediction model integrating surgical characteristics and coagulation biomarkers (D-dimer and fibrinogen) accurately predicts the risk of postoperative pulmonary embolism in patients undergoing thoracic surgery.
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May support risk stratification in thoracic surgery; leaves open prospective validation before clinical adoption.
Li et al. (2025) conducted a cohort in Postoperative pulmonary embolism (n=977). Multifactorial prediction model (nomogram) was evaluated on Prediction of postoperative pulmonary embolism (Training set) (AUC 0.97, 95% CI 0.95-0.99). A multifactorial prediction model integrating surgical and coagulation risk factors accurately predicted postoperative pulmonary embolism in thoracic surgery patients, achieving an AUC of 0.97 in the training set and 0.94 in external validation.
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