Question · asked by 1 review
Balanced protein and energy supplementation vs no intervention or control intervention (control): Preterm birth
- Population
- pregnant women
- Intervention
- Balanced protein and energy supplementation
- Comparison
- no intervention or control intervention (control)
- Outcome
- Preterm birth
Balanced protein and energy supplementation showed no clear difference in preterm birth compared with control or no intervention (moderate certainty).
What each review found
Current versions onlyNo studies found 0 · 0%GRADE not reported 0 · 0%Very low 0 · 0%Low 0 · 0%Moderate 2 · 100%High 0 · 0%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Balanced protein and energy supplementation vs control or no intervention Preterm birth · pregnant women Balanced protein and energy supplementation showed no clear difference in preterm birth compared with control or no intervention (moderate certainty). Antenatal dietary education and supplementation to increase energy and protein intake (2015) · Cochrane Headline outcomes only | RR 0.96 [0.8, 1.16] | 5 studies · 3384 participants | Moderate |
Balanced protein and energy supplementation vs control or no intervention Preterm birth · Pregnant women Balanced protein and energy supplementation showed no clear difference in preterm birth compared with control or no intervention (moderate certainty). Antenatal dietary education and supplementation to increase energy and protein intake (2012) · Cochrane Headline outcomes onlyearlier version CD000032.PUB2, superseded | RR 0.96 [0.8, 1.16] | 5 studies · 3384 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Antenatal dietary education and supplementation to increase energy and protein intake 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.