Accuracy of preinduction transvaginal sonography (TVS) and bishop scores in predicting successful labor induction: a global systematic review and meta-analysis.

J Matern Fetal Neonatal MedJan 4, 2026 (epub)
Clinical ResearchObstetrics & Gynecology

Esther Namutosi, Prosper Akankwasa, Idrissa A Suleiman et al.

✦ AI-curated · Sources linked

In 30 seconds

This systematic review and meta-analysis compared preinduction transvaginal sonography (TVS) with the Bishop score for predicting successful induction in term pregnancies (≥37 weeks). It included 10 observational studies involving 1,612 patients. TVS had a pooled odds ratio of 2.1726 (95% CI: 0.9493-4.9706, p = 0.0662) relative to the Bishop score, indicating a possible but statistically non-significant advantage. Reported success rates were 60.2% for TVS and 48.7% for the Bishop score, with substantial between-study heterogeneity.

Key findings

  • The pooled OR was 2.1726 (95% CI: 0.9493-4.9706, p = 0.0662), so the apparent TVS advantage was not statistically significant.
  • Reported success rates were 60.2% for TVS versus 48.7% for the Bishop score, an absolute difference of 11.5%.
  • Heterogeneity was high (I 2 = 73.12%, p < 0.001); TVS performed better in primigravida and prostaglandin induction settings.

Why it matters

Cervical assessment informs expectations about induction outcomes. These pooled findings suggest TVS may offer useful predictive information alongside the traditional Bishop score, but the non-significant comparison and substantial heterogeneity mean its relative performance is not established consistently across settings. The results also highlight the need for standardized assessment protocols and further evaluation of combined approaches.

What to keep in mind

The evidence came from observational studies, and high heterogeneity (I 2 = 73.12%) limits confidence that performance is consistent across settings.

Source

Published in J Matern Fetal Neonatal Med. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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