Predictors of Infection after Cesarean Delivery.

Am J PerinatolMar 18, 2026 (epub)
Clinical ResearchObstetrics & GynecologyOpen access

Antonio F Saad, Paula L McGee, Samuel Parry et al.

✦ AI-curated · Sources linked

In 30 seconds

This secondary analysis of a multicenter randomized trial developed and evaluated a model predicting infection after scheduled or unscheduled cesarean delivery. Among 10,995 participants, 287 (2.6%) had a surgical site infection, endometritis, or pelvic abscess diagnosed within 6 weeks postpartum. Tobacco use, BMI at delivery ≥ 30 kg/m 2, labor before cesarean, longer surgery, uterine incision extension, and use of uterotonics other than oxytocin were associated with infection. The model’s discrimination was modest, with an AUC of 0.64 (95% CI: 0.61-0.68).

Key findings

  • Infection occurred in 287 of 10,995 participants (2.6%) within 6 weeks postpartum.
  • Tobacco use (OR: 1.67, 95% CI: 1.21-2.31) and labor before cesarean (OR: 1.71, 95% CI: 1.33-2.18) were associated with infection.
  • Other predictors included BMI at delivery ≥ 30 kg/m 2, longer surgical duration, uterine incision extension, and uterotonics other than oxytocin.
  • The predictive model showed modest discrimination: AUC 0.64 (95% CI: 0.61-0.68).

Why it matters

Post-cesarean infection is an important maternal complication, and this analysis identifies perioperative characteristics associated with its occurrence. The findings may help frame risk assessment and future prevention research. However, the model’s modest discrimination means these factors do not yet provide sufficiently accurate individual prediction on their own.

What to keep in mind

The model had modest discrimination (AUC 0.64), and the authors state that further refinement is needed before confident clinical use.

Source

Published in Am J Perinatol. 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 It is not peer reviewed and is not a substitute for the original article.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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