Data synthesis and statistical analysis
We conducted the statistical analyses in accordance with Cochrane guidelines.19
We estimated odds ratio (OR) for dichotomous outcomes and mean difference (MD) for continuous outcomes, along with their 95% confidence intervals (CI) trough pairwise meta-analysis for direct comparisons. Heterogeneity was quantified with the I2statistic20 (30-60% was considered ’moderate’ heterogeneity). We used a random-effects model and tested subgroup differences (P< 0.05 or I² > 30%).
We performed a Bayesian random-effects NMA to estimate treatment effects and 95% credible intervals (CrI), if the between-study homogeneity, transitivity and coherence assumption across treatment comparisons were judged to be justifiable.21,22,23,24We explored the network geometry and connectivity using network diagrams.
We assessed the statistical heterogeneity of the entire network by the heterogeneity variance (τ2) considering the empirical distribution.25
Our prespecified subgroup analyses included gestational age at trial entry (24-28 , 29-34 , 35-37 weeks); intact vs ruptured membranes and country income level: LMIC vs HIC26. We performed sensitivity analysis by low-moderate overall quality of the studies and by using masked treatments.  We performed network meta-regression based on gestational age at entry, GNI per capita and the year of publication.
We assessed small-study effects and publication bias,27 We estimated SUCRA values with their CrIs28,29in a rank-heat plot.30NMA were conducted in OpenBugs (version 3.2.3)31 and pairwise meta-analysis in RevMan 5.3.32.
We assessed the confidence in the estimates by outcome using the GRADE approach and specific criteria for intransitivity (based on potential effect modifiers) and incoherence (based on the statistical consistency).33,34Two authors (AC, IDF) independently graded the certainty of the evidence (CE), and differences were resolved by consensus.
Additionally, we conducted a focus group to reflect patients’ perspectives in the discussion (Appendix S3 ).