Outcomes and clinical practice in patients with COVID-19 admitted to the intensive care unit in Montréal, Canada: a descriptive analysis
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is responsible for millions of infections worldwide, and a substantial number of these patients will be admitted to the intensive care unit (ICU). Our objective was to describe the characteristics, outcomes and management of critically ill patients with COVID-19 pneumonia at a single designated pandemic centre in Montréal, Canada. METHODS: A descriptive analysis was performed on consecutive critically ill patients with COVID-19 pneumonia admitted to the ICU at the Jewish General Hospital, a designated pandemic centre in Montréal, between Mar. 5 and May 21, 2020. Complete follow-up data corresponding to death or discharge from hospital health records were included to Aug. 4, 2020. We summarized baseline characteristics, management and outcomes, including mortality. RESULTS: A total of 106 patients were included in this study. Twenty-one patients (19.8%) died during their hospital stay, and the ICU mortality was 17.0% (18/106); all patients were discharged home or died, except for 4 patients (2 awaiting a rehabilitation bed and 2 awaiting long-term care). Twelve of 65 patients (18.5%) requiring mechanical ventilation died. Prone positioning was used in 29 patients (27.4%), including in 10 patients who were spontaneously breathing; no patient was placed on extracorporeal membrane oxygenation. High-flow nasal cannula was used in 51 patients (48.1%). Acute kidney injury was the most common complication, seen in 20 patients (18.9%), and 12 patients (11.3%) required renal replacement therapy. A total of 53 patients (50.0%) received corticosteroids. INTERPRETATION: Our cohort of critically ill patients with COVID-19 had lower mortality than that previously described in other jurisdictions. These findings may help guide critical care decision-making in similar health care systems in further COVID-19 surges.
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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 | 0.001 | 0.291 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".