Effects of Losartan on Patients Hospitalized for Acute COVID-19: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) down-regulates angiotensin-converting enzyme 2, potentially increasing angiotensin II. We hypothesized that losartan compared to usual care decreases mortality and is safe in patients hospitalized with coronavirus disease 2019 (COVID-19). We aimed to evaluate the effect of losartan versus usual care on 28-day mortality in patients hospitalized for acute COVID-19. METHODS: Eligibility criteria included adults admitted for acute COVID-19. Exclusion criteria were hypotension, hyperkalemia, acute kidney injury, and use of angiotensin receptor blockers (ARBs) or angiotensin-converting enzyme inhibitors within 7 days. Participants were randomized to losartan 25-100 mg/day orally for the hospital duration or 3 months or the control arm (usual care) in 29 hospitals in Canada and France. The primary outcome was 28-day mortality. Secondary outcomes were hospital mortality, organ support, and serious adverse events (SAEs). RESULTS: The trial was stopped early because of a serious safety concern with losartan. In 341 patients, any SAE and hypotension were significantly higher in the losartan versus usual care groups (any SAE: 39.8% vs 27.2%, respectively, P = .01; hypotension: 30.4% vs 15.3%, respectively, P < .001) in both ward and intensive care patients. The 28-day mortality did not differ between losartan (6.5%) versus usual care (5.9%) (odds ratio, 1.11 [95% confidence interval, .47-2.64]; P = .81), nor did organ dysfunction or secondary outcomes. CONCLUSIONS: Caution is needed in deciding which patients to start or continue using ARBs in patients hospitalized with pneumonia to mitigate risk of hypotension, acute kidney injury, and other side effects. ARBs should not be added to care of patients hospitalized for acute COVID-19. CLINICAL TRIALS REGISTRATION: NCT04606563.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".