Convalescent Plasma in Critically ill Patients with Covid-19
Bibliographic record
Abstract
Abstract BACKGROUND The evidence for benefit of convalescent plasma for critically ill patients with Covid-19 is inconsistent. We hypothesized that convalescent plasma would improve outcomes for critically ill adult patients with Covid-19. METHODS In an ongoing adaptive platform trial, critically ill patients with confirmed Covid-19, defined as receiving intensive care-level organ support, were randomized to open-label convalescent plasma or not (i.e., control group). The primary end point was organ support-free days (i.e., days alive and free of ICU-based organ support) up to day 21. The primary analysis was a Bayesian cumulative logistic model with predefined criteria for superiority or futility. An odds ratio greater than 1 represented improved survival, more organ support–free days, or both. RESULTS The convalescent plasma intervention was stopped after pre-specified criteria for futility were met. At that time, 1084 participants had been randomized to convalescent plasma and 916 to no convalescent plasma (control). The median organ support-free days were 0 (interquartile range, -1 to 16) for the convalescent plasma group and 3 (interquartile range, -1 to 16) days for the control group. The median adjusted odds ratio (OR) was 0.97 (95% credible interval 0.83 to 1.15) and posterior probability of futility (OR < 1.2) was 99.4% for convalescent plasma compared to control. In-hospital mortality was 37.3% (401/1075) in convalescent plasma group, and 38.4% (347/904) in controls. The observed treatment effects were consistent across primary and secondary outcomes. CONCLUSIONS In critically ill adults with confirmed Covid-19, treatment with convalescent plasma, did not improve clinical outcomes. Clinicaltrials.gov: NCT02735707
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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 | 0.229 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".