Early antenatal prediction of gestational diabetes in obese women:Development of prediction tools for targeted intervention
| العنوان: | Early antenatal prediction of gestational diabetes in obese women:Development of prediction tools for targeted intervention |
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| المؤلفون: | White, Sara L., Lawlor, Debbie A., Briley, Annette L., Godfrey, Keith M., Nelson, Scott M., Oteng-Ntim, Eugene, Robson, Stephen C., Sattar, Naveed, Seed, Paul T., Vieira, Matias C., Welsh, Paul, Whitworth, Melissa, Poston, Lucilla, Pasupathy, Dharmintra, Shennan, Andrew, Singh, Claire, Sandall, Jane, Sanders, Thomas, Patel, Nashita, Flynn, Angela, Badger, Shirlene, Barr, Suzanne, Holmes, Bridget, Goff, Louise, Hunt, Clare, Filmer, Judy, Fetherstone, Jeni, Scholtz, Laura, Tarft, Hayley, Lucas, Anna, Tekletdadik, Tsigerada, Ricketts, Deborah, Gill, Carolyn, Ignatian, Alex Seroge, Boylen, Catherine, Adegoke, Funso, Lawley, Elodie, Butler, James, Maitland, Rahat, Khazaezadeh, Nina, Demilew, Jill, O'Connor, Sile, Evans, Yvonne, O'Donnell, Susan, De La Llera, Ari, Gutzwiller, Georgina, Hagg, Linda, Bell, Ruth, Hayes, Louise, Ritson, Sarah |
| المصدر: | White, S L, Lawlor, D A, Briley, A L, Godfrey, K M, Nelson, S M, Oteng-Ntim, E, Robson, S C, Sattar, N, Seed, P T, Vieira, M C, Welsh, P, Whitworth, M, Poston, L, Pasupathy, D, Shennan, A, Singh, C, Sandall, J, Sanders, T, Patel, N, Flynn, A, Badger, S, Barr, S, Holmes, B, Goff, L, Hunt, C, Filmer, J, Fetherstone, J, Scholtz, L, Tarft, H, Lucas, A, Tekletdadik, T, Ricketts, D, Gill, C, Ignatian, A S, Boylen, C, Adegoke, F, Lawley, E, Butler, J, Maitland, R, Khazaezadeh, N, Demilew, J, O'Connor, S, Evans, Y, O'Donnell, S, De La Llera, A, Gutzwiller, G, Hagg, L, Bell, R, Hayes, L, Ritson, S & UPBEAT Consortium 2016, ' Early antenatal prediction of gestational diabetes in obese women : Development of prediction tools for targeted intervention ', PLoS ONE, vol. 11, no. 12, e0167846 . https://doi.org/10.1371/journal.pone.0167846Test PLoS ONE PLoS ONE, Vol 11, Iss 12, p e0167846 (2016) |
| سنة النشر: | 2016 |
| مصطلحات موضوعية: | endocrine system diseases, Physiology, Maternal Health, lcsh:Medicine, Type 2 diabetes, Biochemistry, chemistry.chemical_compound, 0302 clinical medicine, Endocrinology, Glucose Metabolism, Pregnancy, Medicine and Health Sciences, Diabetes diagnosis and management, 030212 general & internal medicine, Prospective Studies, lcsh:Science, Medicine(all), Multidisciplinary, Agricultural and Biological Sciences(all), Obstetrics, Obstetrics and Gynecology, 3. Good health, Gestational diabetes, Fructosamine, Physiological Parameters, Carbohydrate Metabolism, Female, Research Article, Adult, medicine.medical_specialty, HbA1c, Endocrine Disorders, General Science & Technology, 030209 endocrinology & metabolism, 03 medical and health sciences, Insulin resistance, Internal medicine, Diabetes mellitus, medicine, Diabetes Mellitus, Metabolomics, Humans, Hemoglobin, Obesity, Management of High-Risk Pregnancies, Adiponectin, business.industry, Biochemistry, Genetics and Molecular Biology(all), lcsh:R, Body Weight, Biology and Life Sciences, Proteins, nutritional and metabolic diseases, medicine.disease, Diagnostic medicine, Diabetes, Gestational, Metabolism, chemistry, Metabolic Disorders, Women's Health, lcsh:Q, business, Biomarkers |
| الوصف: | All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 1518 weeks' gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95% CI 0.68-0.74). This increased to 0.77 (95%CI 0.73-0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74-0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most. |
| وصف الملف: | Electronic-eCollection; application/pdf; text |
| اللغة: | English |
| تدمد: | 1932-6203 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9331d175c2f6f0c41ff7632f4af98a0Test https://doi.org/10.1371/journal.pone.0167846Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....b9331d175c2f6f0c41ff7632f4af98a0 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19326203 |
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