A randomized double-blind controlled trial of convalescent plasma in adults with severe COVID-19
Bibliographic record
Abstract
BACKGROUNDAlthough convalescent plasma has been widely used to treat severe coronavirus disease 2019 (COVID-19), data from randomized controlled trials that support its efficacy are limited.METHODSWe conducted a randomized, double-blind, controlled trial among adults hospitalized with severe and critical COVID-19 at 5 sites in New York City (USA) and Rio de Janeiro (Brazil). Patients were randomized 2:1 to receive a single transfusion of either convalescent plasma or normal control plasma. The primary outcome was clinical status at 28 days following randomization, measured using an ordinal scale and analyzed using a proportional odds model in the intention-to-treat population.RESULTSOf 223 participants enrolled, 150 were randomized to receive convalescent plasma and 73 to receive normal control plasma. At 28 days, no significant improvement in the clinical scale was observed in participants randomized to convalescent plasma (OR 1.50, 95% confidence interval [CI] 0.83-2.68, P = 0.180). However, 28-day mortality was significantly lower in participants randomized to convalescent plasma versus control plasma (19/150 [12.6%] versus 18/73 [24.6%], OR 0.44, 95% CI 0.22-0.91, P = 0.034). The median titer of anti-SARS-CoV-2 neutralizing antibody in infused convalescent plasma units was 1:160 (IQR 1:80-1:320). In a subset of nasopharyngeal swab samples from Brazil that underwent genomic sequencing, no evidence of neutralization-escape mutants was detected.CONCLUSIONIn adults hospitalized with severe COVID-19, use of convalescent plasma was not associated with significant improvement in day 28 clinical status. However, convalescent plasma was associated with significantly improved survival. A possible explanation is that survivors remained hospitalized at their baseline clinical status.TRIAL REGISTRATIONClinicalTrials.gov, NCT04359810.FUNDINGAmazon Foundation, Skoll Foundation.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".