Back

Risk factors for COVID-19 hospitalization or death during the first Omicron surge in adults: a large population-based case-control study

Lo, T.; Usman, H.; Sikdar, K. C.; Strong, D.; James, S.; Ross, J.; Saxinger, L.

2022-08-12 infectious diseases
10.1101/2022.08.11.22278682 medRxiv
Show abstract

BackgroundDescription of risk factors of severe acute COVID-19 outcomes with the consideration of vaccination status in the era of the Omicron variant of concern are limited. ObjectivesTo examine the association of age, sex, underlying medical conditions, and COVID-19 vaccination with hospitalization, intensive-care unit (ICU) admission, or death due to the disease, using data from a period when Omicron was the dominant strain. MethodsA population-based case-control study based on administrative health data, that included confirmed COVID-19 patients during January (2022) in Alberta, Canada. Patients who were non-residents, without the provincial healthcare insurance coverage, or [≤]18 years of age were excluded. Patients with any severe outcome were the cases; and those without any hospitalization, ICU admission, or death were controls. Adjusted odds ratios, of the explanatory factors of a severe outcome, were estimated using a logistic regression model. ResultsThere were 90,989 COVID-19 patients included in the analysis; 2% had severe outcomes and 98% were included in the control group. Overall, more COVID patients were found in the younger age-groups (72.0% [≤]49 years old), females (56.5%), with no underlying conditions (59.5%), and fully vaccinated patients (90.4%). However, the adjusted odds ratios were highest in the 70-79 age group (28.32; 95% CI 20.6-38.9) or among [≥]80 years old (29.8; 21.6-41.0), males (1.4; 1.3-1.6); unvaccinated (16.1; 13.8-18.8), or patients with [≥]3 underlying conditions (13.1; 10.9-15.8). ConclusionHigher risk of severe acute COVID-19 outcomes were associated with older age, the male sex, and increased number of underlying medical conditions. Unvaccination or undervaccination remained as the greatest modifiable risk factor in prevention of severe COVID outcomes. These findings help inform medical decisions and allocation of scarce healthcare resources.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.