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What risk factors are associated with SARS-CoV-2 infections, hospitalization, and mortality among nursing home residents?
In this cohort study among 482 323 long-stay residents, risk of SARS-CoV-2 infections were associated with geographic area and the specific facility, not by characteristics of the residents. Among residents diagnosed with SARS-CoV-2 infections, the risk of hospitalization associated with individual resident characteristics differed from the risk of death.
These findings suggest that decisions on hospitalization of nursing home residents with SARS-CoV-2 were inconsistently associated with risk of death.
Nursing home residents account for approximately 40% of deaths from SARS-CoV-2.
To identify risk factors for SARS-CoV-2 incidence, hospitalization, and mortality among nursing home residents in the US.
Design, Setting, and Participants
This retrospective longitudinal cohort study was conducted in long-stay residents aged 65 years or older with fee-for-service Medicare residing in 15 038 US nursing homes from April 1, 2020, to September 30, 2020. Data were analyzed from November 22, 2020, to February 10, 2021.
Main Outcomes and Measures
The main outcome was risk of diagnosis with SARS-CoV-2 (per International Statistical Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] codes) by September 30 and hospitalization or death within 30 days after diagnosis. Three-level (resident, facility, and county) logistic regression models and competing risk models conditioned on nursing home facility were used to determine association of patient characteristics with outcomes.
Among 482 323 long-stay residents included, the mean (SD) age was 82.7 (9.2) years, with 326 861 (67.8%) women, and 383 838 residents (79.6%) identifying as White. Among 137 119 residents (28.4%) diagnosed with SARS-CoV-2 during follow up, 29 204 residents (21.3%) were hospitalized, and 26 384 residents (19.2%) died within 30 days. Nursing homes explained 37.2% of the variation in risk of infection, while county explained 23.4%. Risk of infection increased with increasing body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) (eg, BMI>45 vs BMI 18.5-25: adjusted hazard ratio [aHR], 1.19; 95% CI, 1.15-1.24) but varied little by other resident characteristics. Risk of hospitalization after SARS-CoV-2 increased with increasing BMI (eg, BMI>45 vs BMI 18.5-25: aHR, 1.40; 95% CI, 1.28-1.52); male sex (aHR, 1.32; 95% CI, 1.29-1.35); Black (aHR, 1.28; 95% CI, 1.24-1.32), Hispanic (aHR, 1.20; 95% CI, 1.15-1.26), or Asian (aHR, 1.46; 95% CI, 1.36-1.57) race/ethnicity; impaired functional status (eg, severely impaired vs not impaired: aHR, 1.15; 95% CI, 1.10-1.22); and increasing comorbidities, such as renal disease (aHR, 1.21; 95% CI, 1.18-1.24) and diabetes (aHR, 1.16; 95% CI, 1.13-1.18). Risk of mortality increased with age (eg, age >90 years vs 65-70 years: aHR, 2.55; 95% CI, 2.44-2.67), impaired cognition (eg, severely impaired vs not impaired: aHR, 1.79; 95% CI, 1.71-1.86), and functional impairment (eg, severely impaired vs not impaired: aHR, 1.94; 1.83-2.05).
Conclusions and Relevance
These findings suggest that among long-stay nursing home residents, risk of SARS-CoV-2 infection was associated with county and facility of residence, while risk of hospitalization and death after SARS-CoV-2 infection was associated with facility and individual resident characteristics. For many resident characteristics, there were substantial differences in risk of hospitalization vs mortality. This may represent resident preferences, triaging decisions, or inadequate recognition of risk of death.
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Accepted for Publication: February 25, 2021.
Published: March 31, 2021. doi:10.1001/jamanetworkopen.2021.6315
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Mehta HB et al. JAMA Network Open.
Corresponding Author: James S. Goodwin, MD, Sealy Center on Aging, Department of Internal Medicine, University of Texas Medical Branch, 301 University Blvd, Galveston, TX 77555-0177 (email@example.com).
Author Contributions: Dr Li had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Mehta, Goodwin.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Mehta, Goodwin.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Mehta, Li.
Obtained funding: Goodwin.
Conflict of Interest Disclosures: None reported.
Funding/Support: This work was supported by grant No. K05-CA134923 from the National Cancer Institute, grant No. P30-AG024832-12 from the Claude D. Pepper Older Americans Independence Center, and Clinical and Translational Science Award No. UL1TR001439.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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