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Derivation a novel risk assessment model of venous thromboembolism in hospitalized patients: the Weng Score

internal-medicine
nursing

Abstract

Background: Venous thromboembolism (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE), significantly contributes to morbidity and mortality among hospitalized patients. Despite the existence of various VTE risk assessment models (RAMs), their performance in accuracy, sensitivity, and specificity remains suboptimal, highlighting opportunities to improve predictive accuracy for clinical decision-making.

Methods: We conducted a retrospective multicenter study involving three hospitals, which included patients with VTE from January 1, 2021, to December 30, 2023. A novel RAM (Weng score) was developed through three different strategies: clinical knowledge-driven model (Model A), data-driven model (Model B), and decision tree-based model (Model C). The primary outcome was in-hospital DVT and PE. Model performance was evaluated through discrimination, calibration, precision, and decision curve analysis (DCA).

Results: A total of 1,791 patients were analyzed, with 680 VTE events recorded during hospitalization. The Weng score, derived from Model A, demonstrated superior predictive performance for VTE and PE compared to existing RAMs, with an AUROC of 0.895 (95%CI: 0.880-0.909) for VTE and 0.877 (95%CI: 0.851-0.903) for PE. This score was also found to have excellent calibration and discrimination, outperforming the Caprini, Padua, Wells, Geneva, and Autar scores in hospitalized patients. The Weng score's clinical utility was further supported by DCA, showing a higher net benefit in predicting VTE and PE than existing RAMs.

Conclusions: We developed and internally validated the Weng score using retrospective data from Chinese hospitals. While it demonstrated better calibration and discrimination than existing RAMs in our cohort, external validation in diverse settings and prospective studies accounting for anticoagulation management are essential before clinical adoption. If validated, this model may offer a refined approach to VTE risk stratification.

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