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Developing a Core Outcome Set for Cesarean Delivery Maternal Infectious Morbidity Outcomes
Kristin E Briscoe1, David M Haas1
1Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, Indiana.
American Journal of Perinatology
|March 1, 2019
Summary
A core outcome set for cesarean delivery trials was developed to standardize reporting of infectious morbidity. This standardized approach will improve data synthesis for meta-analyses.
Area of Science:
- Obstetrics and Gynecology
- Infectious Diseases
- Clinical Trial Methodology
Background:
- Cesarean deliveries are associated with significant infectious morbidity.
- Current studies on cesarean deliveries lack standardized primary outcome reporting.
- Harmonizing outcome measures is crucial for reliable data synthesis.
Purpose of the Study:
- To develop a core outcome set for primary outcomes in cesarean delivery studies focusing on infectious morbidity.
- To establish a consensus-based set of essential outcomes for cesarean section research.
Main Methods:
- Systematic review of primary outcomes from 11 Cochrane and 12 other systematic reviews, plus 327 randomized controlled trials (RCTs).
- Condensation of reported outcomes into 20 primary outcome groups.
- Modified Delphi technique involving expert authors to achieve consensus on key outcomes.
Main Results:
- The most frequent outcomes reported in RCTs were composite infectious outcomes (24%) and endometritis (12%).
- Wound infection (21%) and endometritis (16%) were most common in systematic reviews.
- The Delphi survey identified maternal mortality, wound infection, wound complications, and postpartum endometritis as highly endorsed outcomes.
- The proposed core outcome set includes endometritis, maternal mortality, wound infection, wound complications, febrile morbidity, and neonatal morbidity.
Conclusions:
- A standardized core outcome set for cesarean delivery trials is proposed.
- Implementation of this core outcome set will harmonize trial reporting.
- This standardization will facilitate robust data synthesis for meta-analyses.
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