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Unplanned cesarean sections in advanced maternal age: A predictive model.

Joyce Veenstra1, Zoë Cohen2, Fleurisca J Korteweg3

  • 1Department of Obstetrics and Gynecology, Flevoziekenhuis, Almere, the Netherlands.

Acta Obstetricia Et Gynecologica Scandinavica
|January 13, 2024
PubMed
Summary

Older maternal age increases the risk of unplanned cesarean sections. A predictive model using factors like BMI and previous delivery history can forecast these outcomes in advanced maternal age pregnancies.

Keywords:
advanced maternal agematernal outcomeunplanned cesarean sectionvery advanced maternal age

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Area of Science:

  • Obstetrics and Gynecology
  • Maternal-Fetal Medicine
  • Reproductive Health

Background:

  • Global rise in maternal age necessitates identification of prognostic factors for older women.
  • Advanced maternal age (40+) is associated with increased obstetric risks.
  • Need for predictive tools to manage pregnancies in women aged 40 years and older.

Purpose of the Study:

  • To identify prognostic factors for maternal and perinatal outcomes in women aged 40 years and older.
  • To develop a predictive model for unplanned cesarean sections in advanced maternal age pregnancies.
  • To compare outcomes between women aged 40-44 and those 45+ years.

Main Methods:

  • Retrospective cohort study of 1660 women aged 40+ years (2016-2019).
  • Comparison of outcomes between advanced maternal age (40-44) and very advanced maternal age (45+).
  • Multivariate regression analysis to identify predictors of unplanned cesarean sections; model construction.

Main Results:

  • Unplanned cesarean sections occurred in 21.1% (40-44) and 29.1% (45+) of deliveries.
  • Predictive factors for unplanned cesarean section included higher BMI, no prior vaginal delivery, and longer cervical priming duration.
  • A predictive model achieved an AUC of 0.75; spontaneous labor onset was protective.

Conclusions:

  • Women of advanced and very advanced maternal age face a higher likelihood of unplanned cesarean sections.
  • A validated predictive model can forecast unplanned cesarean sections in this population.
  • Key risk factors include BMI, prior delivery history, and cervical priming; spontaneous labor is protective.