Pregnancy as an opportunity to prevent type 2 diabetes mellitus: FIGO Best Practice Advice

Adam, Sheryl; McIntyre, H. David; Tsoi, Kelvin K.F.; Kapur, Anil; Ronald, C.; Dias, Stephanie; Okong, Pius; Hod, Moshe; Poon, Liona C.; Smith, Graeme N.; Bergman, Lina; Algurjia, Esraa; O’Brien, Patrick; Medina, Virna P.; Maxwell, Cynthia; Regan, Lesley; Rosser, Mary; Jacobsson, Bo; Hanson, Mark A.; O’Reilly, Sharleen; McAuliffe, Fionnuala M.

doi:10.1002/ijgo.14537

Cited by 36 publications

(31 citation statements)

References 78 publications

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“…30 Despite this, considerable work is still required to establish follow-up for women following pregnancy with gestational diabetes, to ameliorate the risks of type 2 diabetes. 31 FIGO is committed to improve women's health across the life course and the FIGO Committee on Impact of Pregnancy on Longterm Health will continue to advocate for improved women's health by:…”

Section: Many Healthcare Systems Have Robust Neonatal and Child Follo...mentioning

confidence: 99%

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Impact of pregnancy on long‐term health: Advances in postpregnancy care—An opportunity to improve long‐term maternal health

McAuliffe

2023

Intl J Gynecology & Obste

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Section: Many Healthcare Systems Have Robust Neonatal and Child Follo...mentioning

confidence: 99%

“…To date, lifestyle and pharmacological interventions have been shown to reduce the risk of later type 2 diabetes 30 . Despite this, considerable work is still required to establish follow‐up for women following pregnancy with gestational diabetes, to ameliorate the risks of type 2 diabetes 31 …”

mentioning

confidence: 99%

Impact of pregnancy on long‐term health: Advances in postpregnancy care—An opportunity to improve long‐term maternal health

McAuliffe

2023

Intl J Gynecology & Obste

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“…Despite several professional bodies recommending postpartum assessment and interventions to reduce the risk of long‐term health complications, 1,2,15 maternal compliance with follow‐up appointments remains low. A study indicated that only half of the high‐risk women attended postpartum check‐ups 16 .…”

Section: Figurementioning

confidence: 99%

FIGO pregnancy passport: A useful tool for women and their healthcare providers on health risks following pregnancy complications

Nguyen-Hoang

Smith

Bergman

et al. 2023

Intl J Gynecology & Obste

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“…Accurate prediction of incident GDM may enable prevention. FIGO Best Practice Advice recommends viewing pregnancy as an opportunity to prevent type 2 diabetes mellitus Adam et al (2023).…”

Section: Introductionmentioning

confidence: 99%

Systematic Review of risk score prediction models using maternal characteristics with and without biomarkers for the prediction of GDM

Parkhi,

Sampathkumar,

Weldeselassie

et al. 2023

Preprint

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Background: GDM is associated with adverse maternal and fetal complications. By the time GDM is diagnosed, continuous exposure to the hyperglycaemic intrauterine environment can adversely affect the fetus. Hence, early pregnancy prediction of GDM is important. Aim: To systematically evaluate whether composite risk score prediction models can accurately predict GDM in early pregnancy. Method: Systematic review of observational studies involving pregnant women of <20 weeks of gestation was carried out. The search involved various databases, grey literature, and reference lists till August 2022. The primary outcome was the predictive performance of the models in terms of the AUC, for <14 weeks and 14-20 weeks of gestation. Results: Sixty-seven articles for <14 weeks and 22 for 14-20 weeks of gestation were included (initial search - 4542). The sample size ranged from 42 to 1,160,933. The studies were from Canada, USA, UK, Europe, Israel, Iran, China, Taiwan, South Korea, South Africa, Australia, Singapore, and Thailand. For <14 weeks, the AUC ranges were 0.59-0.88 and 0.53-0.95, respectively for models that used only maternal characteristics and for those that included biomarkers. For 14-20 weeks these AUCs were 0.68-0.71 and 0.65-0.92. Age, ethnicity, BMI, family history of diabetes, and prior GDM were the 5 most commonly used risk factors. The addition of systolic BP improved performance in some models. Triglycerides, PAPP-A, and lipocalin-2, combined with maternal characteristics, have the highest predictive performance. AUC varied according to the population studied. Pooled analyses were not done due to high heterogeneity. Conclusion: Accurate GDM risk prediction may be possible if common risk factors are combined with biomarkers. However, more research is needed in populations of high GDM risk. Artificial Intelligence-based risk prediction models that incorporate fetal biometry data may improve accuracy.

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Pregnancy as an opportunity to prevent type 2 diabetes mellitus: FIGO Best Practice Advice

Cited by 36 publications

References 78 publications

Impact of pregnancy on long‐term health: Advances in postpregnancy care—An opportunity to improve long‐term maternal health

Impact of pregnancy on long‐term health: Advances in postpregnancy care—An opportunity to improve long‐term maternal health

FIGO pregnancy passport: A useful tool for women and their healthcare providers on health risks following pregnancy complications

Systematic Review of risk score prediction models using maternal characteristics with and without biomarkers for the prediction of GDM

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