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Derivation and External Validation of a Risk Assessment Model of Venous Thromboembolism in Hospitalized Chinese Patients

Clin Appl Thromb Hemost. 2023 Jan-Dec;29:10760296221151164. doi: 10.1177/10760296221151164.

ABSTRACT

AIM: To develop and validate a risk assessment model (RAM) of venous thromboembolism (VTE) in hospitalized Chinese patients.

METHODS: We reviewed data from 300 patients with VTE and 300 non-VTE patients at Beijing Shijitan Hospital. The risk factors related to VTE were analyzed, and the VTE RAM (Shijitan (SJT) version) was developed according to the weight of each risk factor. A total of 407 patients with VTE and 533 non-VTE patients were enrolled for external validation. The sensitivity, specificity, Youden index, receiver operating curve (ROC), and area under the ROC curve (AUC) were used to evaluate the performance of VTE RAM (SJT version) compared with Caprini RAM and Padua RAM.

RESULTS: The VTE RAM (SJT version) contained six risk factors (age >60 years, lower limb edema, chronic obstructive pulmonary disease (COPD), central venous catheterization (CVC), VTE history, and D dimer). In the external validation group, for medical patients, the AUC value of SJT RAM (0.82 ± 0.03) is significantly higher than Caprini RAM (0.76 ± 0.04; P < 0.05), SJT RAM has a higher sensitivity, specificity, and Youden index than Caprini RAM (P < 0.05), which means that the SJT RAM has a much better predictive value than Caprini RAM. While SJT RAM and Padua RAM have the similar predictive value for medical patients (P > 0.05). For surgical patients, the AUC value of SJT RAM (0.72 ± 0.04) is significantly higher than the value of Padua RAM (0.66 ± 0.04; P < 0.05), SJT RAM has a higher sensitivity, specificity, and Youden index than Padua RAM (P < 0.05), which shows that the VTE RAM has better predictive value than Padua RAM. While SJT RAM and Caprini RAM have the similar predictive value for surgical patients (P > 0.05).

CONCLUSION: The SJT RAM derived from general hospitalized Chinese patients will be time-saving for physicians and has a better predictive ability for patients at risk of VTE.

PMID:36650933 | DOI:10.1177/10760296221151164

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