Question · asked by 1 review
Tinzaparin vs placebo: Adverse events associated with the use of anticoagulants (e.g. bleeding)
- Population
- people with sickle cell disease
- Intervention
- Tinzaparin
- Comparison
- placebo
- Outcome
- Adverse events associated with the use of anticoagulants (e.g. bleeding)
Tinzaparin showed no clear difference in adverse events associated with the use of anticoagulants (e.g.… compared with placebo (low certainty).
What each review found
Current versions onlyNo studies found 0 · 0%GRADE not reported 0 · 0%Very low 0 · 0%Low 1 · 50%Moderate 0 · 0%High 1 · 50%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Tinzaparin vs placebo Adverse events associated with the use of anticoagulants (e.g. bleeding) · people with sickle cell disease Tinzaparin showed no clear difference in adverse events associated with the use of anticoagulants (e.g.… compared with placebo (low certainty). Low‐molecular‐weight heparins for managing vaso‐occlusive crises in people with sickle cell disease (2015) · Cochrane Headline outcomes only | RR 4.96 [0.24, 102.31] | 1 study · 253 participants | Low |
Tinzaparin vs placebo adverse events associated with the use of anticoagulants (e.g. bleeding) · people with sickle cell disease Tinzaparin showed no clear difference in adverse events associated with the use of anticoagulants (e.g.… compared with placebo (high certainty). Low‐molecular‐weight heparins for managing vaso‐occlusive crises in people with sickle cell disease (2013) · Cochrane Headline outcomes onlyearlier version CD010155.PUB2, superseded | RR 4.96 [0.24, 102.31] | 1 study · 253 participants | High |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Low‐molecular‐weight heparins for managing vaso‐occlusive crises in people with sickle cell disease 2015 · Cochrane Headline outcomes only | Not reported | Not extracted | Not assessed |
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.