Temporal Variations in the Intensity of Care Provided to Community and Nursing Home Residents Who Died of COVID-19 in Ontario, Canada
Bibliographic record
Abstract
Introduction - Worldwide, nursing home residents have experienced disproportionately high COVID-19 mortality due to the intersection of congregate living, multimorbidity, and advanced age. Among 12 OECD countries, Canada has had the highest proportion of COVID-19 deaths in nursing home residents (78%), raising concerns about a skewed pandemic response that averted much transmission and mortality in community-dwelling residents, but did not adequately protect those in nursing homes. To investigate this, we measured temporal variations in hospitalizations among community and nursing home-dwelling decedents with COVID-19 during the first and second waves of the pandemic. Methods - We conducted a population-based cohort study of residents of Ontario, Canada with COVID-19 who died between March 11, 2020 (first COVID-19 death in Ontario) and October 28, 2020. We examined hospitalization prior to death as a function of 4 factors: community (defined as all non-nursing home residents) vs. nursing home residence, age in years (<70, 70-79, 80-89, ≥90), gender, and month of death (1st wave: March-April [peak], May, June-July 2020 [nadir], 2nd wave: August-October 2020). Results - A total of 3,114 people with confirmed COVID-19 died in Ontario from March to October, 2020 (Table 1), of whom 1,354 (43.5%) were hospitalized prior to death (median: 9 days before death, interquartile range: 4-19). Among nursing home decedents (N=2000), 22.4% were admitted to hospital prior to death, but this varied substantially from a low of 15.5% in March-April (peak of wave 1) to a high of 41.2% in June-July (nadir of wave 1). Among community-dwelling decedents (N=1,114), admission to acute care was higher (81.4%) and remained relatively stable throughout the first and second waves. Similar temporal trends for nursing home versus community decedents were apparent in age-stratified analyses (Figure 1). Women who died were less likely to have been hospitalized compared to men in both community (80% women vs 84% men) and nursing home (21% women vs 24% men) settings. Discussion - Only a minority of Ontario nursing home residents who died of COVID-19 were hospitalized prior to death, and that there were substantial temporal variations, with hospitalizations reaching their lowest point when overall COVID-19 incidence peaked in mid-April, 2020. While many nursing home residents had pre-pandemic advance directives precluding hospitalization, the low admission rate observed in March-April 2020 (15.5%) was inconsistent with both higher admission rates in subsequent months (>30%), and comparatively stable rates among community-dwelling adults. Our findings substantiate reports suggesting that hospitalizations for nursing home residents with COVID-19 were low during the peak of the pandemic’s first wave in Canada, which may have contributed to the particularly high concentration of COVID-19 mortality in Ontario’s nursing homes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".