Early safety indicators of COVID-19 convalescent plasma in 5000 patients
Bibliographic record
Abstract
BACKGROUNDConvalescent plasma is the only antibody-based therapy currently available for patients with coronavirus disease 2019 (COVID-19). It has robust historical precedence and sound biological plausibility. Although promising, convalescent plasma has not yet been shown to be safe as a treatment for COVID-19.METHODSThus, we analyzed key safety metrics after transfusion of ABO-compatible human COVID-19 convalescent plasma in 5000 hospitalized adults with severe or life-threatening COVID-19, with 66% in the intensive care unit, as part of the US FDA expanded access program for COVID-19 convalescent plasma.RESULTSThe incidence of all serious adverse events (SAEs), including mortality rate (0.3%), in the first 4 hours after transfusion was <1%. Of the 36 reported SAEs, there were 25 reported incidences of related SAEs, including mortality (n = 4), transfusion-associated circulatory overload (n = 7), transfusion-related acute lung injury (n = 11), and severe allergic transfusion reactions (n = 3). However, only 2 of 36 SAEs were judged as definitely related to the convalescent plasma transfusion by the treating physician. The 7-day mortality rate was 14.9%.CONCLUSIONGiven the deadly nature of COVID-19 and the large population of critically ill patients included in these analyses, the mortality rate does not appear excessive. These early indicators suggest that transfusion of convalescent plasma is safe in hospitalized patients with COVID-19.TRIAL REGISTRATIONClinicalTrials.gov NCT04338360.FUNDINGMayo Clinic, Biomedical Advanced Research and Development Authority (75A50120C00096), National Center for Advancing Translational Sciences (UL1TR002377), National Heart, Lung, and Blood Institute (5R35HL139854 and R01 HL059842), National Institute of Diabetes and Digestive and Kidney Diseases (5T32DK07352), Natural Sciences and Engineering Research Council of Canada (PDF-532926-2019), National Institute of Allergy and Infectious Disease (R21 AI145356, R21 AI152318, and AI152078), Schwab Charitable Fund, United Health Group, National Basketball Association, Millennium Pharmaceuticals, and Octapharma USA Inc.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".