Predictors of Mortality Among Long-term Care Residents With SARS-CoV-2 Infection

Douglas S. Lee MD, PhD; Shihao Ma BASc; Anna Chu MHSc; Chloe X. Wang BSc; Xuesong Wang MSc; Peter C. Austin PhD; Finlay A. McAlister MD, MSc; Sunil V. Kalmady PhD; Moira K. Kapral MD, MSc; Padma Kaul PhD; Dennis T. Ko MD, MSc; Paula A. Rochon MD, MPH; Michael J. Schull MD, MSc; Barry B. Rubin MD, PhD; Bo Wang PhD


J Am Geriatr Soc. 2021;69(12):3377-3388. 

In This Article

Abstract and Introduction


Background: While individuals living in long-term care (LTC) homes have experienced adverse outcomes of SARS-CoV-2 infection, few studies have examined a broad range of predictors of 30-day mortality in this population.

Methods: We studied residents living in LTC homes in Ontario, Canada, who underwent PCR testing for SARS-CoV-2 infection from January 1 to August 31, 2020, and examined predictors of all-cause death within 30 days after a positive test for SARS-CoV-2. We examined a broad range of risk factor categories including demographics, comorbidities, functional status, laboratory tests, and characteristics of the LTC facility and surrounding community were examined. In total, 304 potential predictors were evaluated for their association with mortality using machine learning (Random Forest).

Results: A total of 64,733 residents of LTC, median age 86 (78, 91) years (31.8% men), underwent SARS-CoV-2 testing, of whom 5029 (7.8%) tested positive. Thirty-day mortality rates were 28.7% (1442 deaths) after a positive test. Of 59,702 residents who tested negative, 2652 (4.4%) died within 30 days of testing. Predictors of mortality after SARS-CoV-2 infection included age, functional status (e.g., activity of daily living score and pressure ulcer risk), male sex, undernutrition, dehydration risk, prior hospital contacts for respiratory illness, and duration of comorbidities (e.g., heart failure, COPD). Lower GFR, hemoglobin concentration, lymphocyte count, and serum albumin were associated with higher mortality. After combining all covariates to generate a risk index, mortality rate in the highest risk quartile was 48.3% compared with 7% in the first quartile (odds ratio 12.42, 95%CI: 6.67, 22.80, p < 0.001). Deaths continued to increase rapidly for 15 days after the positive test.

Conclusions: LTC residents, particularly those with reduced functional status, comorbidities, and abnormalities on routine laboratory tests, are at high risk for mortality after SARS-CoV-2 infection. Recognizing high-risk residents in LTC may enhance institution of appropriate preventative measures.


Death from SARS-CoV-2 infection has disproportionately affected residents of long-term care (LTC) homes.[1] LTC homes are designed for adults requiring access to nursing care 24 h of the day, frequent assistance with activities of daily living, and monitoring for safety or well-being.[2] Residents in long-term care were found to have 13 times greater mortality than community-dwelling adults older than 69 years of age in Ontario, Canada and similarly high rates of death have been reported among LTC residents in other countries world-wide.[1,3,4]

Although many reports have examined prognostic factors in the overall population, few studies have specifically examined predictors of mortality in residents of LTC with SARS-CoV-2 infection exclusively. Since residents of LTC homes are at a substantially elevated risk for SARS-CoV-2 infection, predictors of risk for the general population may not be applicable to this special group. LTC homes in Ontario are similar to long-stay nursing homes in the United States, as the latter are similar to the Canadian provision of complex continuing care. LTC homes house a potentially vulnerable population since over half of residents (55%) are aged 85 years and over.[5] LTC homes are not skilled nursing facilities, as the latter is similar to complex continuing care.

To better understand the contributions to mortality among SARS-CoV-2 infected residents in LTC homes, we undertook a detailed analysis including demographic, comorbid conditions, functional measures, laboratory test results, and LTC facility and community characteristics. Our objective was to determine predictors associated with 30-day mortality after a positive SARS-CoV-2 test in residents in LTC using machine-learning techniques because of the ability to examine numerous potential variables from multiple types of data sources of varying complexity and interrelatedness.[6]