Long‐term red cell transfusion vs no transfusion: Stroke
- Population
- individuals with sickle cell disease who are at risk of a primary stroke who have not had previous long‐term red cell transfusions
- Intervention
- Long‐term red cell transfusion
- Comparison
- no transfusion
- Outcome
- Stroke
Long‐term red cell transfusion probably leads to lower clinical stroke compared with no transfusion (moderate certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Long‐term red cell transfusion vs no transfusion Clinical stroke · individuals with sickle cell disease who are at risk of a primary stroke who have not had previous long‐term red cell… Long‐term red cell transfusion probably leads to lower clinical stroke compared with no transfusion (moderate certainty). Blood transfusion for preventing primary and secondary stroke in people with sickle cell disease (2020) · Cochrane Headline outcomes only | RR 0.12 [0.03, 0.49] | 2 studies · 326 participants | Moderate |
Long‐term red cell transfusion vs no transfusion Clinical stroke · individuals with sickle cell disease who are at risk of a primary stroke who have not had previous long‐term red cell… Long‐term red cell transfusion probably leads to lower clinical stroke compared with no transfusion (moderate certainty). Blood transfusion for preventing primary and secondary stroke in people with sickle cell disease (2017) · Cochrane Headline outcomes onlyearlier version CD003146.PUB3, superseded | RR 0.12 [0.03, 0.49] | 2 studies · 326 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Blood transfusion for preventing primary and secondary stroke in people with sickle cell disease 2020 · Cochrane Headline outcomes only | Not reported | Not extracted | Not assessed |
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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.