Comparison of hospitalized patients with COVID-19 who did and did not live in residential care facilities in Montréal: a retrospective case series
Bibliographic record
Abstract
BACKGROUND: As in other jurisdictions, the demographics of people infected with SARS-CoV-2 changed in Quebec over the course of the first COVID-19 pandemic wave, and affected those living in residential care facilities (RCFs) disproportionately. We evaluated the association between clinical characteristics and outcomes of hospitalized patients with COVID-19, comparing those did or did not live in RCFs. METHODS: We conducted a retrospective case series of all consecutive adults (≥ 18 yr) admitted to the Jewish General Hospital in Montréal with laboratory-confirmed SARS-CoV-2 infection from Mar. 4 to June 30, 2020, with in-hospital follow-up until Aug. 6, 2020. We collected patient demographics, comorbidities and outcomes (i.e., admission to the intensive care unit, mechanical ventilation and death) from medical and laboratory records and compared patients who did or did not live in public and private RCFs. We evaluated factors associated with the risk of in-hospital death with a Cox proportional hazard model. RESULTS: In total, 656 patients were hospitalized between March and June 2020, including 303 patients who lived in RCFs and 353 patients who did not. The mean age was 72.9 (standard deviation 18.3) years (range 21 to 106 yr); 349 (53.2%) were female and 118 (18.0%) were admitted to the intensive care unit. The overall mortality rate was 23.8% (156/656), but was higher among patients living in RCFs (36.6% [111/303]) compared with those not living in RCFs (12.7% [45/353]). Increased risk of death was associated with age 80 years and older (hazard ratio [HR] 2.39, 95% confidence interval [CI] 1.35-4.24), male sex (HR 1.74, 95% CI 1.25-2.41), the presence of 4 or more comorbidities (HR 2.01, 95% CI 1.18-3.42) and living in an RCF (HR 1.62, 95% CI 1.09-2.39). INTERPRETATION: During the first wave of the COVID-19 epidemic in Montréal, more than one-third of RCF residents hospitalized with SARS-CoV-2 infection died during hospitalization. Policies and practices that prevent future outbreaks of SARS-CoV-2 infection in this setting must be implemented to prevent high mortality in this vulnerable population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".