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BRIEF RESEARCH ARTICLE
Year : 2020  |  Volume : 64  |  Issue : 6  |  Page : 221-224

COVID-19-Hospitalized Patients in Karnataka: Survival and Stay Characteristics


1 MPH Scholar, Department of Epidemiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
2 PhD Scholar, Department of Biostatistics, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
3 Additional Professor, Department of Epidemiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
4 Professor and Head, Department of Epidemiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India

Correspondence Address:
Senthil Amudhan
212, Department of Epidemiology, Dr. MVG Building, National Institute of Mental Health and Neurosciences, Bengaluru - 560 029, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.IJPH_486_20

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The information on the clinical course of coronavirus disease 2019 (COVID-19) and its correlates which are essential to assess the hospital care needs of the population are currently limited. We investigated the factors associated with hospital stay and death for COVID-19 patients for the entire state of Karnataka, India. A retrospective-cohort analysis was conducted on 445 COVID-19 patients that were reported in the publicly available media-bulletin from March 9, 2020, to April 23, 2020, for the Karnataka state. This fixed cohort was followed till 14 days (May 8, 2020) for definitive outcomes (death/discharge). The median length of hospital stay was 17 days (interquartile range: 15–20) for COVID-19 patients. Having severe disease at the time of admission (adjusted-hazard-ratio: 9.3 (3.2–27.3);P < 0.001) and being aged ≥ 60 years (adjusted-hazard-ratio: 11.9 (3.5–40.6);P < 0.001) were the significant predictors of COVID-19 mortality. By moving beyond descriptive (which provide only crude information) to survival analyses, information on the local hospital-related characteristics will be crucial to model bed-occupancy demands for contingency planning during COVID-19 pandemic.


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