Abstract 9009: Management of Renin-Angiotensin-Aldosterone System Blockade in Patients Admitted in Hospital With Confirmed Coronavirus Disease (COVID-19) Infection: The McGill RAAS-COVID-19 Randomized Controlled Trial
Bibliographic record
Abstract
Background: More data is needed on the cardiovascular impact of discontinuing versus continuing renin-angiotensin aldosterone system inhibitors (RAASi) among patients hospitalized with a severe acute respiratory syndrome coronavirus 2 infection (COVID-19). Methods: The McGill RAAS-COVID-19 trial was a randomized, open label trial in adult patients hospitalized with COVID-19, who were previously treated with RAASi (angiotensin converting enzyme inhibitors [ACEi]/angiotensin receptor blocker [ARB]) (NCT04508985; 10/2020-03/2021). Participants were randomized 1:1 to discontinue or continue RAASi. The primary outcome was a global rank score calculated from baseline to day 7 (or discharge) incorporating clinical events and biomarker changes. Global rank scores were compared between groups using the Wilcoxon test statistic and the negative binomial test (using incident rate ratio [IRR]). All analyses were conducted using the intention-to-treat principle. Results: Overall, 21 participants were randomized to discontinue RAASi and 25 to continue. Patients’ mean age was 71.5 years and 43.5% were female. Discontinuation of RAASi, versus continuation, resulted in a similar mean global rank score (discontinuation 6 [standard deviation [SD] 6.3] vs continuation 3.8 (SD 2.5); p= 0.60), but the negative binomial analysis identified that discontinuation increased the risk of adverse outcomes (IRR 1.7 [95% CI 1.1 to 2.6]; p=0.03). Particularly, RAASi discontinuation increased brain natriuretic peptide (BNP) levels (% change from baseline: +16.7% vs. -27.5%; p= 0.02) and increased the incidence of acute heart failure (33% vs. 4.2%, p=0.03). Conclusion: Discontinuation of RAASi increased BNP levels and risk of acute heart failure in participants hospitalized with COVID-19; where possible, RAASi should be continued.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".