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Vaginal Birth After Cesarean Section (VBAC) Model using Fuzzy Analytic Hierarch Process.

Stavroula Barbounaki1, Kleanthi Gourounti2, Antigoni Sarantaki2

  • 1PhD, Electrical and Computer Engineer, Consultant.

Acta Informatica Medica : AIM : Journal of the Society for Medical Informatics of Bosnia & Herzegovina : Casopis Drustva Za Medicinsku Informatiku Bih
|February 24, 2022
PubMed
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This study developed fuzzy logic models to help doctors decide between vaginal birth after cesarean (VBAC) and repeat cesarean delivery (CS). The models identify key factors influencing the decision, aiding in personalized birth recommendations.

Area of Science:

  • Obstetrics and Gynecology
  • Medical Decision Making
  • Fuzzy Logic Applications

Background:

  • Rising Cesarean Delivery (CS) rates necessitate strategies for Vaginal Birth After Cesarean (VBAC).
  • Previous VBAC attempts faced challenges like uterine rupture, leading to increased CS.
  • Despite WHO initiatives, CS rates remain high globally.

Purpose of the Study:

  • To develop two fuzzy models: one for VBAC and one for CS.
  • To assess pregnant women's medical profiles for optimal delivery recommendations.
  • To provide a data-driven approach for delivery method selection.

Main Methods:

  • Literature review to identify factors influencing VBAC/CS.
  • Semi-structured interviews with 29 obstetricians to refine factors.
Keywords:
Cesarean SectionFuzzy multi-criteria analysisVBACdecision making

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  • Fuzzy Analytic Hierarchy Process (FAHP) to create multicriteria decision models.

    • Main Results:

    • Identified 36 critical factors for delivery decisions.
    • 27 factors favor CS, including contraindications, prior uterine rupture, and uterine surgery.
    • 9 factors favor VBAC, emphasizing maternal request, provider recommendations, and prior VBAC success.

    Conclusions:

    • The fuzzy logic approach effectively handles the complexity of delivery method selection.
    • Enables clinicians to integrate expertise and intuition for informed intrapartum care decisions.
    • Supports personalized assessment for pregnant women considering VBAC or CS.