TY - JOUR
T1 - 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
AU - Belsti, Yitayeh
AU - Moran, Lisa J.
AU - Goldstein, Rebecca
AU - Mousa, Aya
AU - Cooray, Shamil D.
AU - Baker, Susanne
AU - Gupta, Yashdeep
AU - Patel, Anushka
AU - Tandon, Nikhil
AU - Ajanthan, Saumiyah
AU - John, Renu
AU - Naheed, Aliya
AU - Chakma, Nantu
AU - Lakshmi, Josyula K.
AU - Zoungas, Sophia
AU - Billot, Laurent
AU - Desai, Ankush
AU - Bhatla, Neerja
AU - Prabhakaran, Dorairaj
AU - Gupta, Ishita
AU - de Silva, H. Asita
AU - Kapoor, Deksha
AU - Praveen, Devarsetty
AU - Farzana, Noshin
AU - Enticott, Joanne
AU - Teede, Helena
N1 - Funding Information:
The Global Alliance for Chronic Disease from the Indian Council of Medical Research (58/1/1/GACD/NCD-II), the Australian National Health and Medical Research Council (1093171), Sub-studies also received supplementary funding from USV Private and Lupin. HT received NHMRC Fellowship funds.
Funding Information:
The study is funded by Global Alliance for Chronic Disease grants NO.58/1/1/GACD/NCD-II from the Indian Council of Medical Research and 1093171 from the Australian National Health and Medical Research Council. Authors want to thank clinical collaborators.
Publisher Copyright:
© 2024 The Authors
PY - 2024/8
Y1 - 2024/8
N2 - 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.
AB - 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.
KW - Gestational diabetes mellitus
KW - Predictive model
KW - Prognosis
KW - Prognostic model
KW - Type 2 diabetes
UR - http://www.scopus.com/inward/record.url?scp=85196550605&partnerID=8YFLogxK
U2 - 10.1016/j.clnu.2024.06.006
DO - 10.1016/j.clnu.2024.06.006
M3 - Article
AN - SCOPUS:85196550605
SN - 0261-5614
VL - 43
SP - 1728
EP - 1735
JO - Clinical Nutrition
JF - Clinical Nutrition
IS - 8
ER -