Key result
A novel risk assessment model incorporating neutrophil percentage, age, malignant tumor, and lymphocyte percentage accurately predicted pulmonary embolism in postoperative patients with an AUC of 0.949.
Why the study?
Pulmonary embolism is a leading cause of mortality in postoperative patients, and clinical practice prevention guidelines are not consistently implemented.
Can a novel risk assessment model accurately predict the probability of pulmonary embolism in postoperative patients?
Observational (n=25,926)
No
Can a novel risk assessment model accurately predict the probability of pulmonary embolism in postoperative patients?
Effect estimate: AUC 0.949 (95% CI 0.932-0.966)
A novel 4-variable risk assessment model demonstrated high accuracy (AUC > 0.94) for predicting pulmonary embolism in patients undergoing Grade IV surgery.
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May guide targeted PE prophylaxis in surgical patients; leaves open outcome impact pending prospective validation.
Wang et al. (2021) conducted an observational in Pulmonary embolism in postoperative patients (n=25,926). Novel risk assessment model (neutrophil percentage, age, malignant tumor, lymphocyte percentage) was evaluated on Pulmonary embolism (PE) before discharge (AUC 0.949, 95% CI 0.932-0.966). A novel risk assessment model incorporating neutrophil percentage, age, malignant tumor, and lymphocyte percentage accurately predicted pulmonary embolism in postoperative patients with an AUC of 0.949.
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