Selected article for: "admission prior and logistic regression"

Author: Li, Ang; Kuderer, Nicole M.; Hsu, Chih‐Yuan; Shyr, Yu; Warner, Jeremy L.; Shah, Dimpy P.; Kumar, Vaibhav; Shah, Surbhi; Kulkarni, Amit A.; Fu, Julie; Gulati, Shuchi; Zon, Rebecca L.; Li, Monica; Desai, Aakash; Egan, Pamela C.; Bakouny, Ziad; KC, Devendra; Hwang, Clara; Akpan, Imo J.; McKay, Rana R.; Girard, Jennifer; Schmidt, Andrew L.; Halmos, Balazs; Thompson, Michael A.; Patel, Jaymin M.; Pennell, Nathan A.; Peters, Solange; Elshoury, Amro; de Lima Lopes, Gilbero; Stover, Daniel G.; Grivas, Petros; Rini, Brian I.; Painter, Corrie A.; Mishra, Sanjay; Connors, Jean M.; Lyman, Gary H.; Rosovsky, Rachel P.
Title: The CoVID‐TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID‐19
  • Cord-id: tqkyp9ay
  • Document date: 2021_8_13
  • ID: tqkyp9ay
    Snippet: BACKGROUND: Hospitalized patients with COVID‐19 have increased risks of venous (VTE) and arterial thromboembolism (ATE). Active cancer diagnosis and treatment are well‐known risk factors; however, a risk assessment model (RAM) for VTE in patients with both cancer and COVID‐19 is lacking. OBJECTIVES: To assess the incidence of and risk factors for thrombosis in hospitalized patients with cancer and COVID‐19. METHODS: Among patients with cancer in the COVID‐19 and Cancer Consortium regis
    Document: BACKGROUND: Hospitalized patients with COVID‐19 have increased risks of venous (VTE) and arterial thromboembolism (ATE). Active cancer diagnosis and treatment are well‐known risk factors; however, a risk assessment model (RAM) for VTE in patients with both cancer and COVID‐19 is lacking. OBJECTIVES: To assess the incidence of and risk factors for thrombosis in hospitalized patients with cancer and COVID‐19. METHODS: Among patients with cancer in the COVID‐19 and Cancer Consortium registry (CCC19) cohort study, we assessed the incidence of VTE and ATE within 90 days of COVID‐19–associated hospitalization. A multivariable logistic regression model specifically for VTE was built using a priori determined clinical risk factors. A simplified RAM was derived and internally validated using bootstrap. RESULTS: From March 17, 2020 to November 30, 2020, 2804 hospitalized patients were analyzed. The incidence of VTE and ATE was 7.6% and 3.9%, respectively. The incidence of VTE, but not ATE, was higher in patients receiving recent anti‐cancer therapy. A simplified RAM for VTE was derived and named CoVID‐TE (Cancer subtype high to very‐high risk by original Khorana score +1, VTE history +2, ICU admission +2, D‐dimer elevation +1, recent systemic anti‐cancer Therapy +1, and non‐Hispanic Ethnicity +1). The RAM stratified patients into two cohorts (low‐risk, 0–2 points, n = 1423 vs. high‐risk, 3+ points, n = 1034) where VTE occurred in 4.1% low‐risk and 11.3% high‐risk patients (c statistic 0.67, 95% confidence interval 0.63–0.71). The RAM performed similarly well in subgroups of patients not on anticoagulant prior to admission and moderately ill patients not requiring direct ICU admission. CONCLUSIONS: Hospitalized patients with cancer and COVID‐19 have elevated thrombotic risks. The CoVID‐TE RAM for VTE prediction may help real‐time data‐driven decisions in this vulnerable population.

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