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Practices for predicting and preventing preterm birth in Ireland: a national survey

V Smith1, D Devane, S Higgins

  • 1School of Nursing and Midwifery, Trinity College Dublin, The University of Dublin, 24 D'Olier Street, Dublin 2, Ireland. vasmith@tcd.ie

Irish Journal of Medical Science
|October 19, 2010
PubMed

Insights

This study analyzed preterm birth prediction and prevention practices in Ireland. Findings indicate that while some methods align with evidence-based practices, others, like routine cervical assessments and tocolytic use, are prevalent.

Area of Science:

  • Obstetrics and Gynecology
  • Neonatal Health
  • Public Health

Background:

  • Preterm birth poses significant risks to neonates and families.
  • Accurate prediction and prevention of preterm birth are critical public health priorities.
  • This study examines current Irish practices in preterm birth management.

Purpose of the Study:

  • To describe and critically analyze the practices used for predicting preterm birth in Ireland.
  • To describe and critically analyze the practices used for preventing preterm birth in Ireland.

Main Methods:

  • A national survey of consultant obstetricians in Ireland was conducted.
  • Questionnaires were distributed in February 2006 to gather data on prediction and prevention strategies.
  • Data on specific interventions and screening methods were collected.

Main Results:

  • Most respondents (97%) did not use fetal fibronectin testing for prediction.
  • Routine second and third-trimester cervical assessments (71%) and genital tract infection screening (75%) were common.
  • Interventions for prevention included bed rest (62%), antibiotics (24%), cervical cerclage (14%), and tocolytics (61%).

Conclusions:

  • The surveyed practices largely align with the existing evidence base.
  • Findings reflect international trends and established best practice recommendations for preterm birth management.
  • The study provides insights into the adoption of evidence-based strategies in Irish obstetrics.
Abstract

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