Published: 2022-09-22

Predictors of mortality among COVID-19 patients admitted in a dedicated COVID hospital during the pandemic in Himachal Pradesh, India

Anita Thakur, Durgesh K. Thakur, Chitvan Thakur


Background: The outcome of COVID-19 disease is variable. Mostly patients have mild to moderate disease and get recovered; some patients have severe disease leading to mortality. Hence it is essential to find out the factors affecting the outcome in the COVID-19 patients. The aim of this study was to identify predictors of mortality among hospitalized patients of COVID-19 and to estimate their prevalence among these patients.

Methods: This was an observational study, longitudinal in design, carried out among 790 COVID-19 patients hospitalized in a tertiary care dedicated COVID hospital in Himachal, during the second wave of COVID.

Results: Overall 26.2% of the hospitalized patients were having one or more co morbidities. DM (17.6%) and delayed hospitalization (42.7%) were highly prevalent risk factors among hospitalized patients with high mortality 39.6% and 49% respectively. Overall mortality rate among study participants was 29.7%. Patients having malignancy and other immuno-compromising diseases had highest mortality rate 68.4%. Median time gap between onset of symptoms and hospitalization was 9 days among those who died and 5 days among those who recovered. On multivariate logistic regression analysis higher age (>60 years) AOR 5.392 (3.435-8.463), delayed hospital admission AOR 8.204 (5.522-12.188), diabetes mellitus AOR 1.888 (CI-1.199-2.972), malignancy and other immune compromising diseases AOR 9.108 (2.934-28.270) and chronic kidney disease AOR 7.524 (CI=2.289-27.735) were the significant predictors of mortality.

Conclusions: We observed the higher COVID-19 mortality among the patients having higher age, DM, CKD, immunocompromising diseases and delay in hospitalization. DM and delayed hospitalization were two most prevalent risk factors present among these patients.


COVID-19 mortality, Comorbidities, Pandemic, Predictors, Delayed hospitalization

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