Selected article for: "data set and hazard ratio"

Author: Berry, Donald A.; Ip, Andrew; Lewis, Brett E.; Berry, Scott M.; Berry, Nicholas S.; MrKulic, Mary; Gadalla, Virginia; Sat, Burcu; Wright, Kristen; Serna, Michelle; Unawane, Rashmi; Trpeski, Katerina; Koropsak, Michael; Kaur, Puneet; Sica, Zachary; McConnell, Andrew; Bednarz, Urszula; Marafelias, Michael; Goy, Andre H.; Pecora, Andrew L.; Sawczuk, Ihor S.; Goldberg, Stuart L.
Title: Development and validation of a prognostic 40-day mortality risk model among hospitalized patients with COVID-19
  • Cord-id: gyx27xko
  • Document date: 2021_7_30
  • ID: gyx27xko
    Snippet: OBJECTIVES: The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations. METHODS: We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With dea
    Document: OBJECTIVES: The development of a prognostic mortality risk model for hospitalized COVID-19 patients may facilitate patient treatment planning, comparisons of therapeutic strategies, and public health preparations. METHODS: We retrospectively reviewed the electronic health records of patients hospitalized within a 13-hospital New Jersey USA network between March 1, 2020 and April 22, 2020 with positive polymerase chain reaction results for SARS-CoV-2, with follow-up through May 29, 2020. With death or hospital discharge by day 40 as the primary endpoint, we used univariate followed by stepwise multivariate proportional hazard models to develop a risk score on one-half the data set, validated on the remainder, and converted the risk score into a patient-level predictive probability of 40-day mortality based on the combined dataset. RESULTS: The study population consisted of 3123 hospitalized COVID-19 patients; median age 63 years; 60% were men; 42% had >3 coexisting conditions. 713 (23%) patients died within 40 days of hospitalization for COVID-19. From 22 potential candidate factors 6 were found to be independent predictors of mortality and were included in the risk score model: age, respiratory rate ≥25/minute upon hospital presentation, oxygenation <94% on hospital presentation, and pre-hospital comorbidities of hypertension, coronary artery disease, or chronic renal disease. The risk score was highly prognostic of mortality in a training set and confirmatory set yielding in the combined dataset a hazard ratio of 1.80 (95% CI, 1.72, 1.87) for one unit increases. Using observed mortality within 20 equally sized bins of risk scores, a predictive model for an individual’s 40-day risk of mortality was generated as -14.258 + 13.460*RS + 1.585*(RS–2.524)^2–0.403*(RS–2.524)^3. An online calculator of this 40-day COVID-19 mortality risk score is available at www.HackensackMeridianHealth.org/CovidRS. CONCLUSIONS: A risk score using six variables is able to prognosticate mortality within 40-days of hospitalization for COVID-19. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT04347993.

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