Correlates of In-Hospital COVID-19 Deaths: A Competing Risks Survival Time Analysis of Retrospective Mortality Data. (25th October 2022)

• Record Type: Journal Article
• Authors: Goel, Ashish; Raizada, Alpana; Agrawal, Ananya; Bansal, Kamakshi; Uniyal, Saurabh; Prasad, Pratima; Yadav, Anil; Tyagi, Asha; Rautela, RS
• Is Part Of: Disaster medicine and public health preparedness. Volume 16:Number 5(2022)
• Page Start: 1889
• Page End: 1896
• Publication Date: 2022-10-25
• Subjects: mortality -- death -- COVID-19 -- competing risks -- recovery; Disaster medicine -- Periodicals; Emergency management -- Planning -- Periodicals; Public health -- Periodicals; 363.34
• DOI: 10.1017/dmp.2021.85
• Languages: English
• ISSNs: 1935-7893

Abstract

Abstract: Introduction: Several aspects of the coronavirus disease 2019 (COVID-19) pandemic remain ambiguous, including its transmission, severity, geographic, and racial differences in mortality. These variations merit elaboration of local patterns to inform wider national policies. Methods: In a retrospective analysis, data of patients treated at a dedicated COVID hospital with moderate and severe illness during 8 wk of the pandemic were reviewed with attention to mortality in a competing risks framework. Results: A total of 1147 patients were hospitalized, and 312 (27.2%) died in hospital. Those who died were older (56.5 vs 47.6 y; P < 0.0001). Of these, 885 (77.2%) had tested positive on reverse transcriptase polymerase chain reaction (RT-PCR), with 219 (24.2%) deaths (incidence rate, 1.9 per 100 person-days). Median time from onset of symptoms to death was 11 days. A competing risks analysis for in-hospital death revealed an adjusted cause-specific hazard ratio of 1.4 for each decade increase in age. Conclusions: This retrospective analysis provides broad patterns of disease presentation and mortality. Even COVID test-negative patients will receive treatment at dedicated facilities, and 33% presenting cases may die within the first 72 h, most with comorbid illness. This should be considered while planning distribution of services for effective health-care delivery