Organ dysfunction and death in patients admitted to hospital with COVID-19 in pandemic waves 1 to 3 in British Columbia, Ontario and Quebec, Canada: a cohort study
Bibliographic record
Abstract
BACKGROUND: There have been multiple waves in the COVID-19 pandemic in many countries. We sought to compare mortality and respiratory, cardiovascular and renal dysfunction between waves in 3 Canadian provinces. METHODS: We conducted a substudy of the ARBs CORONA I study, a multicentre Canadian pragmatic observational cohort study that examined the association of pre-existing use of angiotensin receptor blockers with outcomes in adults admitted to hospital with acute COVID-19 up to April 2021 from 9 community and teaching hospitals in 3 Canadian provinces (British Columbia, Ontario and Quebec). We excluded emergency department admissions without hospital admission, readmissions and admissions for another reason. We used logistic and 0-1-inflated β regression models to compare 28-day and in-hospital mortality, and the use of invasive mechanical ventilation, vasopressors and renal replacement therapy (RRT) between the first 3 waves of the COVID-19 pandemic in these provinces. RESULTS: A total of 520, 572 and 245 patients in waves 1, 2 and 3, respectively, were included. Patients in wave 3 were on average younger and had fewer comorbidities than those in waves 1 and 2. The unadjusted 28-day mortality rate was significantly lower in wave 3 (7.8%) than in wave 1 (18.3%) (odds ratio [OR] 0.43, 95% confidence interval [CI] 0.24-0.78) and wave 2 (16.3%) (OR 0.46, 95% CI 0.27-0.79). After adjustment for differences in baseline characteristics, the difference in 28-day mortality remained significant (adjusted OR wave 3 v. wave 1: 0.46, 95% CI 0.26-0.81; wave 3 v. wave 2: 0.52, 95% CI 0.29-0.91). In-hospital mortality findings were similar. Use of invasive mechanical ventilation or vasopressors was less common in waves 2 and 3 than in wave 1, and use of RRT was less common in wave 3 than in wave 1. INTERPRETATION: Severity of illness decreased (lower mortality and less use of organ support) across waves among patients admitted to hospital with acute COVID-19, possibly owing to changes in patient demographic characteristics and management, such as increased use of dexamethasone. Continued application of proven therapies may further improve outcomes. STUDY REGISTRATION: ClinicalTrials.gov, no. NCT04510623.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".