The coronavirus disease 2019 (COVID-19) pandemic, caused by the rapid outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has put immense pressure on healthcare systems worldwide. It is important to identify individuals at the highest risk to devise prompt decisions and treatment strategies. This is particularly important when dealing with novel respiratory viruses. Identification of shared and divergent determinants of clinical severity across respiratory viruses is also crucial while dealing with novel or re-emergent respiratory pathogens.
In a new study available on the medRxiv* preprint server, researchers performed a retrospective cohort study to identify predictors of mortality following hospitalization with influenza, respiratory syncytial virus, or SARS-CoV-2. Population-based health administrative data from Ontario, Canada, were used for this analysis.
Previous research has compared the determinants (shared and divergent) of severe disease outcomes in patients with influenza and respiratory syncytial virus (RSV). However, not many papers have addressed the issue of comparing predictors of severity across influenza, RSV, and SARS-CoV-2.
Given that countries are gradually returning to pre-pandemic contact and exposure patterns, the risk of respiratory infections could rise. There is also a possibility that only a fraction of hospitalized patients with viral respiratory illness will receive laboratory-confirmed diagnoses. Therefore, identifying shared predictors of disease could help reduce morbidity and mortality and prepare healthcare settings, which should require greater resources based on the prevalence of the identified predictors.
A new study
In the present study, scientists conducted an observational study using extensive health administrative data from Ontario, Canada. They aimed to identify the direction and magnitude of shared and divergent predictors of 30- day all-cause mortality.
Researchers focussed on patients hospitalized with influenza, RSV, or SARS-CoV-2. The sample included 45,749 influenza patients hospitalized between September 2011 and May 2019, 24,345 RSV patients hospitalized between September 2011 and April 2019, and 8,988 SARS-CoV-2 patients, hospitalized between March 2020 and December 2020 (pre-vaccine).
Associations between potential predictors and mortality were evaluated using the multivariable modified Poisson regression technique. The direction, magnitude, and confidence intervals of risk ratios were compared to identify shared and divergent predictors of mortality.
The common predictors of 30-day all-cause mortality following hospitalization included old age, male sex, residence in a long-term care home (LTCH), and chronic kidney disease. Across all respiratory cohorts, old age and male sex were predictive of increased mortality, especially in patients with SARS-CoV-2. This emphasizes the need to prioritize age and sex in clinical practice and consider them to guide targeted COVID-19 preventions and therapeutics.
Apart from age and sex, LTCH residence was also a common predictor of 30-day all-cause mortality. In this case, the associations were weaker among SARS-CoV-2 patients. These differences could be driven by selection bias. To illustrate further, consider that during the first wave of the pandemic in Ontario, 24.3% of COVID-19-positive LTCH residents were hospitalized before death, compared to 79.3% of SARS-CoV-2-infected community residents. Limited resources could have led to less frequent hospitalization of COVID-19 patients.
Chronic kidney disease was found to increase the risk of 30-day all-cause mortality. The magnitudes were similar for influenza, RSV, and SARS-CoV-2 patients. Other comorbidities were found to predict mortality among patients with influenza or RSV, but not SARS-CoV-2, probably owing to smaller sample size in case of SARS-CoV-2, greater hospitalization of less severe SARS-CoV-2 patients with comorbidities, and/or clinical differences between patients requiring hospitalization with SARS-CoV-2 versus seasonal influenza or RSV.
Researchers did not observe associations between mortality and local social determinants of health for all three viruses. They stated that this result could be driven by misclassification of neighborhood-level social determinants of health, ecological fallacy, etc.
The present study has some limitations, including the potential misclassification of influenza and RSV cases. Patients were not identified using their diagnostic test results, which could lead to such misclassification. Researchers, however, mentioned that misclassification should be rare because case definitions were validated against a population of hospitalized patients. A second limitation was the lack of data on the other predictors of disease severity, such as pregnancy and obesity. These limitations must be considered while using the results to prioritize services or develop clinical prediction tools.
In the present study, the authors identified common predictors of 30-day all-cause mortality following hospitalization with SARS-CoV-2, influenza, or RSV. This work is important because common predictors could help identify patients at the greatest risk of developing severe disease and prioritize preventions and therapeutics during viral epidemics.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.