Visceral fat mass as a novel risk factor for predicting gestational diabetes in obese pregnant women

Date published

2018-03-14

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Journal Title

Journal ISSN

Volume Title

Publisher

SAGE

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Type

Article

ISSN

1753-495X

Format

Citation

Balani J, Hyer SL, Shehata H, Mohareb F, Visceral fat mass as a novel risk factor for predicting gestational diabetes in obese pregnant women, Obstetric Medicine, Obstetric Medicine, Volume: 11, issue: 3, September 2018, pp121-125

Abstract

Objective

To develop a model to predict gestational diabetes mellitus incorporating classical and a novel risk factor, visceral fat mass.

Methods

Three hundred two obese non-diabetic pregnant women underwent body composition analysis at booking by bioimpedance analysis. Of this cohort, 72 (24%) developed gestational diabetes mellitus. Principal component analysis was initially performed to identify possible clustering of the gestational diabetes mellitus and non-GDM groups. A machine learning algorithm was then applied to develop a GDM predictive model utilising random forest and decision tree modelling.

Results

The predictive model was trained on 227 samples and validated using an independent testing subset of 75 samples where the model achieved a validation prediction accuracy of 77.53%. According to the decision tree developed, visceral fat mass emerged as the most important variable in determining the risk of gestational diabetes mellitus.

Conclusions

We present a model incorporating visceral fat mass, which is a novel risk factor in predicting gestational diabetes mellitus in obese pregnant women

Description

Software Description

Software Language

Github

Keywords

Gestational diabetes, Obesity, Visceral fat mass, Predictive model, Principle component analysis, Machine learning

DOI

Rights

© The Authors. The final, definitive version of this article has been published in the Journal: Obstetric Medicine. ©SAGE Publications Ltd, Journals Online: http://online.sagepub.com/

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