Role of HbA1c and 50g GCT in early detection and prediction of gestational diabetes and associated maternal and fetal complications in Thailand
Gestational diabetes mellitus (GDM) is one of the commonest maternal medical conditions, and if untreated, can cause maternal and fetal complications. Diagnosis is made between 24-28 weeks of pregnancy using the oral glucose tolerance test (OGTT). However, by then some harm may have occurred. Universal screening is backed by many guidelines but is not uniformly followed. Selective screening based on risk factors (age, BMI, etc.) can miss up to 50% of women with GDM. In lower middle income countries, it may be difficult to do OGTTs, which require access to laboratory facilities.
In Thailand, women at high risk for GDM are supposed to be screened at the first antenatal visit with the 50g Glucose Challenge Test (GCT) but the rate of screening for GDM in Thailand varies from none at all in rural areas to 78% in urban areas.
An alternative is to screen with HbA1c at first antenatal clinic visit. The HbA1c is a one-step test, can be done at point of care and patients do not need to fast. However, the relationship of HbA1c levels in early pregnancy and outcomes of pregnancy (including the development of GDM) is not known in Thai women.
The study aims to determine whether HbA1c and 50g GCT testing at first antenatal clinic visit can predict the development of GDM and outcomes, whether baseline HbA1c and 50g GCT levels can rule out later GDM and whether universal or selective screening is more cost-effective. Cost effectiveness analyses will also be performed to identify what levels of HbA1c and 50g GCT should require treatment in Thailand. Finally, the study will evaluate whether diet/lifestyle interventions, can prevent GDM.
The project will recruit women at <= 20 weeks gestation (n=4264). Those with HbA1c 5.7-6.4% and/or 50g GCT 140-199mg/dL will be randomised to interventions (50%), or to standard care (50%); both will have OGTT at 28 weeks (being treated if GDM develops). Economic analyses will enable policy makers to make informed decisions based on local data.
|
Funded by: |
MRC |
|
Research team members: |
Professor Paramjit Gill, Professor Ponnusamy Saravanan, Professor Nigel Stallard, Professor Norman Waugh |
|
Collaborators: |
Mahidol University, Thailand; University of Leicester |
|
Dates – from and to: |
2020 -2022 |