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Li, Jun‐Ying; Wang, Hong‐Fei; Yin, Ping; Li, Di; Wang, Di‐Le; Peng, Peng; Wang, Wei‐Hua; Wang, Lan; Yuan, Xiao‐Wei; Xie, Jin‐Yuan; Zhou, Fan; Xiong, Nian; Shao, Feng; Wang, Chun‐Xiu; Tong, Xiang; Ye, Hao; Wan, Wen‐Jun; Liu, Ben‐De; Li, Wen‐Zhu; Li, Qian; Tang, Liang V.; Hu, Yu; Lip, Gregory Y. H.
Journal of thrombosis and haemostasis, April 2021, Volume: 19, Issue: 4Journal Article
Background High incidence of asymptomatic venous thromboembolism (VTE) has been observed in severe COVID‐19 patients, but the characteristics of symptomatic VTE in general COVID‐19 patients have not been described. Objectives To comprehensively explore the prevalence and reliable risk prediction for VTE in COVID‐19 patients. Methods/Results This retrospective study enrolled all COVID‐19 patients with a subsequent VTE in 16 centers in China from January 1 to March 31, 2020. A total of 2779 patients were confirmed with COVID‐19. In comparison to 23,434 non‐COVID‐19 medical inpatients, the odds ratios (ORs) for developing symptomatic VTE in severe and non‐severe hospitalized COVID‐19 patients were 5.94 (95% confidence interval CI 3.91–10.09) and 2.79 (95% CI 1.43–5.60), respectively. When 104 VTE cases and 208 non‐VTE cases were compared, pulmonary embolism cases had a higher rate for in‐hospital death (OR 6.74, 95% CI 2.18–20.81). VTE developed at a median of 21 days (interquartile range 13.25–31) since onset. Independent factors for VTE were advancing age, cancer, longer interval from symptom onset to admission, lower fibrinogen and higher D‐dimer on admission, and D‐dimer increment (DI) ≥1.5‐fold; of these, DI ≥1.5‐fold had the most significant association (OR 14.18, 95% CI 6.25–32.18, p = 2.23 × 10−10). A novel model consisting of three simple coagulation variables (fibrinogen and D‐dimer levels on admission, and DI ≥1.5‐fold) showed good prediction for symptomatic VTE (area under the curve 0.865, 95% CI 0.822–0.907, sensitivity 0.930, specificity 0.710). Conclusions There is an excess risk of VTE in hospitalized COVID‐19 patients. This novel model can aid early identification of patients who are at high risk for VTE.
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