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Predictive model for macrosomia using maternal parameters without sonography information.

Daisuke Shigemi1,2, Satoru Yamaguchi1, Shotaro Aso2

  • 1a Yamaguchi Women's Hospital , Chiba , Japan.

The Journal of Maternal-Fetal & Neonatal Medicine : the Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
|June 2, 2018
PubMed
Summary
This summary is machine-generated.

This study developed a simple scoring system using maternal physical data to effectively exclude fetal macrosomia. This method avoids the need for ultrasound, offering a practical screening tool for pregnant women.

Keywords:
Machine learningmacrosomic infantrandom forestscoring systemscreening

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Area of Science:

  • Obstetrics and Gynecology
  • Maternal-Fetal Medicine
  • Predictive Modeling in Healthcare

Background:

  • Fetal macrosomia poses risks during pregnancy and delivery.
  • Current diagnostic methods often rely on sonographic examination.
  • There is a need for accessible methods to predict and exclude macrosomia.

Purpose of the Study:

  • To develop predictive models for excluding fetal macrosomia using only maternal physical parameters.
  • To create an integer risk scoring system for macrosomia prediction.
  • To evaluate the efficacy of machine learning models in predicting macrosomia.

Main Methods:

  • Retrospective analysis of medical records from 15,263 pregnant women delivering singleton infants at term.
  • Logistic regression analysis to identify significant predictors of macrosomia.
  • Development of an integer risk scoring system and a random forest machine learning model.

Main Results:

  • 203 cases of macrosomia were identified among the eligible population.
  • The developed scoring system demonstrated a very high negative predictive value (0.996-1.000) for excluding macrosomia.
  • The random forest model showed a comparable negative predictive value (0.99).

Conclusions:

  • An integer scoring system based on maternal physical parameters is a useful and simple tool for excluding macrosomia.
  • This method offers a practical alternative to sonographic examination for routine screening.
  • The findings support the use of non-ultrasound based models for efficient macrosomia risk assessment.