Blood biomarkers for the diagnosis of chorioamnionitis following preterm premature rupture of membranes: a systematic review and meta-analysis of studies since 2020.

Crit Rev Clin Lab SciMay 28, 2026 (epub)

Antoine Puravet, Samy Kahouadji, Denis Gallot et al.

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In 30 seconds

This systematic review and meta-analysis assessed maternal blood biomarkers for predicting histological or clinical chorioamnionitis in women with preterm premature rupture of membranes (PPROM). Nine studies were included from 631 screened articles. Pooled sensitivity was highest for procalcitonin (83%), while neutrophil-lymphocyte ratio had the highest pooled specificity (82%); overall diagnostic performance was modest, with area under the curve values of 73%–77%. No single biomarker appeared sufficiently accurate for prediction, and recent biomarkers lacked enough studies for meta-analysis.

Key findings

  • Pooled sensitivity was 71% for CRP, 73% for white blood cell count, 83% for procalcitonin, and 75% for neutrophil-lymphocyte ratio.
  • Pooled specificity was 75% for CRP, 61% for white blood cell count, 41% for procalcitonin, and 82% for neutrophil-lymphocyte ratio.
  • Area under the ROC curve ranged from 73% for white blood cell count to 77% for CRP and neutrophil-lymphocyte ratio.

Why it matters

Chorioamnionitis is an important infection risk when deciding between delivery and expectant management after PPROM, and is associated with serious maternal and fetal complications. These pooled results indicate that commonly assessed blood markers offer only modest diagnostic performance, underscoring the difficulty of relying on any one marker to identify affected patients.

What to keep in mind

Only nine studies were included, and no new biomarker had been evaluated frequently enough to permit meta-analysis of its diagnostic accuracy.

Source

Published in Crit Rev Clin Lab Sci. 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 It is not peer reviewed and is not a substitute for the original article.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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