Interventions for vs no intervention: Number of deaths due to SUDEP: Nocturnal supervision compared to no supervision
It is very uncertain whether interventions for changes number of deaths due to SUDEP: additional nocturnal supervision… compared with no intervention (very low certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Interventions for vs no intervention Number of deaths due to SUDEP: nocturnal supervision compared to no supervision · cases of SUDEP and matched controls (number of deaths due to SUDEP) and consecutive people with epilepsy from a… Treatments for the prevention of Sudden Unexpected Death in Epilepsy (SUDEP) (2020) · Cochrane Headline outcomes only | no estimate extracted | 203 participants | Very low |
Interventions for vs no intervention Number of deaths due to SUDEP: additional nocturnal supervision compared to no additional supervision · cases of SUDEP and matched controls (number of deaths due to SUDEP) and consecutive people with epilepsy from a… It is very uncertain whether interventions for changes number of deaths due to SUDEP: additional nocturnal supervision… compared with no intervention (very low certainty). Treatments for the prevention of Sudden Unexpected Death in Epilepsy (SUDEP) (2020) · Cochrane Headline outcomes only | OR 0.76 [0.4, 1.46] | 48 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Treatments for the prevention of Sudden Unexpected Death in Epilepsy (SUDEP) 2020 · 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.