Summary of findings table ‐ Convalescent plasma vs placebo or usual care: All‐cause mortality at up to day 28
It is very uncertain whether summary of findings table ‐ Convalescent plasma changes all‐cause mortality at up to day 28 compared with placebo or standard care alone (very low certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Summary of findings table ‐ Convalescent plasma vs placebo or standard care alone All‐cause mortality at up to day 28 · outpatients withmild disease It is very uncertain whether summary of findings table ‐ Convalescent plasma changes all‐cause mortality at up to day 28 compared with placebo or standard care alone (very low certainty). Convalescent plasma for people with COVID‐19: a living systematic review (2023) · Cochrane Headline outcomes onlyearlier version CD013600.PUB5, superseded | OR 0.36 [0.09, 1.46] | 2 studies · 536 participants | Very low |
Summary of findings table ‐ Convalescent plasma vs placebo or standard care alone All‐cause mortality at up to day 28 · outpatients withmild disease It is very uncertain whether summary of findings table ‐ Convalescent plasma changes all‐cause mortality at up to day 28 compared with placebo or standard care alone (very low certainty). Convalescent plasma for people with COVID‐19: a living systematic review (2023) · Cochrane Headline outcomes only | OR 0.36 [0.09, 1.46] | 2 studies · 536 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Convalescent plasma for people with COVID‐19: a living systematic review 2023 · Cochrane Headline outcomes only | Not reported | list not extracted yet | Not assessed |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.