Development of a risk prediction model for postpartum onset of type 2 diabetes mellitus, following gestational diabetes; the lifestyle InterVention in gestational diabetes (LIVING) study
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Date
2024
Authors
Belsti, Y.
Moran, L.J.
Goldstein, R.
Mousa, A.
Cooray, S.D.
Baker, S.
Gupta, Y.
Patel, A.
Tandon, N.
Ajanthan, S.
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Journal article
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Clinical Nutrition, 2024; 43(8):1728-1735
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Yitayeh Belsti, Lisa J. Moran, Rebecca Goldstein, Aya Mousa, Shamil D. Cooray, Susanne Baker, Yashdeep Gupta, Anushka Patel, Nikhil Tandon, Saumiyah Ajanthan, Renu John, Aliya Naheed, Nantu Chakma, Josyula K. Lakshmi, Sophia Zoungas, Laurent Billot, Ankush Desai, Neerja Bhatla, Dorairaj Prabhakaran, Ishita Gupta, H. Asita de Silva Deksha Kapoor, Devarsetty Praveen, Noshin Farzana, Joanne Enticott, Helena Teede
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Abstract
Aims: This study aimed to develop a prediction model for identifying a woman with gestational diabetes mellitus (GDM) at high risk of type 2 diabetes (T2DM) post-birth. Methods: Utilising data from 1299 women in the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, two models were developed: one for pregnancy and another for postpartum. Key predictors included glucose test results, medical history, and biometric indicators. Results: Of the initial cohort, 124 women developed T2DM within three years. The study identified seven predictors for the antenatal T2DM risk prediction model and four for the postnatal one. The models demonstrated good to excellent predictive ability, with Area under the ROC Curve (AUC) values of 0.76 (95% CI: 0.72 to 0.80) and 0.85 (95% CI: 0.81 to 0.88) for the antenatal and postnatal models, respectively. Both models underwent rigorous validation, showing minimal optimism in predictive capability. Antenatal model, considering the Youden index optimal cut-off point of 0.096, sensitivity, specificity, and accuracy were measured as 70.97%, 70.81%, and 70.82%, respectively. For the postnatal model, considering the cut-off point 0.086, sensitivity, specificity, and accuracy were measured as 81.40%, 75.60%, and 76.10%, respectively. Conclusions: These models are effective for predicting T2DM risk in women with GDM, although external validation is recommended before widespread application.
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© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)