Time-Varying Risk of Death After SARS-CoV-2-Infection in Long-Term Care Facility Residents: A Matched Cohort Study

  1. Marcel Ballin
  2. John P.A. Ioannidis
  3. Jonathan Bergman
  4. Miia Kivipelto
  5. Anna Nordström
  6. Peter Nordström

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

SARS-CoV-2 confers high risk of short-term death in residents of long-term care (LTC) facilities, but longer-term risk among survivors is unclear.

Methods

We extended the follow-up period of a previous, propensity score-matched retrospective cohort study based on the Swedish Senior Alert register. N=3731 LTC residents with documented SARS-CoV-2 until 15 September 2020 were matched to 3731 uninfected controls using time-dependent propensity scores on age, sex, health status, comorbidities, and prescription medications. In a sensitivity analysis, matching included also geographical region and Senior Alert registration time. The outcome was all-cause mortality over 8 months (until October 24, 2020). The absolute risk of death was examined using Kaplan-Meier plots. Hazard ratios (HR) for death over time were estimated using flexible parametric models with restricted cubic splines. Cox regression was used to estimate HRs and 95% confidence intervals (CIs) in 30-day intervals of follow-up until 210 days.

Results

The median age was 87 years and 65% were women. Excess mortality was highest 5 days after documented infection (HR 19.1, 95% CI, 14.6-24.8), after which excess mortality decreased. From the second month onwards, mortality rate became lower in infected residents than controls. The HR for death during days 61-210 of follow-up was 0.41 in the main analysis (95% CI, 0.34-0.50) and 0.76 (95% CI, 0.62-0.93) in the sensitivity analysis. Median survival of uninfected controls was 1.6 years, which was much lower than the national life expectancy in Sweden at age 87 (5.05 years in men, 6.07 years in women).

Conclusions

No excess mortality was observed in LTC residents who survived the acute SARS-CoV-2 infection. Life expectancy of uninfected residents was much lower than that of the general population of the same age and sex. This suggests that LTC resident status should be accounted for in years-of-life-lost estimates for COVID-19 burden of disease calculations.

Impact statement

We certify that this work is novel. This research adds to the literature by showing there was no excess mortality observed in long-term care facility residents who survived the acute SARS-CoV-2 infection, and that life expectancy of uninfected residents was much lower than that of the general population of same age and sex. This has major repercussions for estimation of years of life lost in infected long term care facility residents.

Key points

  • SARS-CoV-2 infection sharply increased mortality risk among residents of long-term care (LTC) facilities in the first month.

  • After the first month, the mortality risk in infected residents rapidly returned to baseline and dropped below the mortality risk of uninfected controls, where it remained lower for 8 months of follow-up.

  • Median survival of uninfected controls was 1.6 years, which was much lower than national life expectancy in Sweden at age 87.

Why does this matter?

  • Whereas LTC residents who recover from SARS-CoV-2 infection may be concerned about having residual debilitation caused by the infection, we found no excess mortality was in those who survived the acute infection.

  • Because life expectancy of uninfected residents was much lower than that of the general population of same age and sex, LTC resident status should be accounted for in estimations of years of life lost.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2022.03.10.22272097: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsConsent: The study was approved by the Swedish Ethical Review Authority, which waived the informed consent requirement (no. 2020-02552).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses were performed using Stata MP version 16.1 for Mac (StataCorp, College Station, TX).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Some caveats should be discussed. Our data pertain to fatalities during the first wave of COVID-19 and until the fall of 2020. The first wave was the most devastating in most high-income countries, with a few exceptions (e.g. Australia).15,16 The relatively lower proportion of fatalities in LTC residents in subsequent waves may reflect a combination of multiple factors: high levels of prior infection (seroprevalence studies have found 5-10 times higher infection rates in LTC facilities than in the general population in the first wave),17-19 better protection of nursing homes, more extensive testing, widespread use of vaccination in 2021,16 and the possibility that the sickest individuals were the first to succumb.20 Moreover, the significantly lower risk of death after the first month post-infection versus the uninfected controls should not be interpreted as a sign that SARS-CoV-2 infection causally decreases the risk of death during long-term follow-up, as it probably reflects mostly a selection process (residents who died in the first month were probably more sick and debilitated before infection, while those surviving probably had better life expectancy). Allowing for these caveats, the major strength of our study is that it uses on large databases with nationwide coverage. Even so, similar analyses should also be performed in other countries because the health status of LTC residents may be different. This will allow to obtain more solid evidence on both the years-of-life...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2022.03.10.22272097 on medRxiv