BACKGROUND/ OBJECTIVE: The diagnosis of gestational diabetes mellitus on oral glucose tolerance test (OGTT) is used to identify risk of both neonatal large-for-gestational-age (LGA) and maternal postpartum prediabetes/diabetes. An assumption inherent in this practice, however, is that the glucose values that define gestational diabetes mellitus on the OGTT relate to both of these outcomes in the same way. Thus, to test this assumption, we sought to evaluate the predictive capacity of each glucose value on antepartum OGTT in relation to LGA and postpartum prediabetes/diabetes. DESIGN/SETTING/PARTICIPANTS: A total of 412 women representing the full spectrum of antepartum glucose tolerance underwent 3-h OGTT in pregnancy, assessment of obstetrical outcome at delivery, and 2-h OGTT at 3 months postpartum. RESULTS: Of the four glucose values (fasting, 1h, 2 h, 3 h) on antepartum OGTT, only the fasting measure was a significant predictor of LGA [odds ratio (OR) 2.00 per mmol/liter, 95% confidence interval (CI) 1.20-3.34] (P = 0.0076). In contrast, all three postload glucose values were significant predictors of postpartum prediabetes/diabetes (1 h glucose: OR 1.37, 95% CI 1.17-1.61, P < 0.0001; 2 h glucose: OR 1.55, 95% CI 1.32-1.83, P < 0.0001; 3 h glucose: OR 1.30, 95% CI 1.10-1.53, P = 0.002), whereas fasting glucose was not. Furthermore, whereas fasting glucose had the highest area under the receiver operating characteristic curve for predicting LGA (0.62), the 1- and 2-h glucose measures had the highest area under the receiver operating characteristic curve values for postpartum prediabetes/diabetes (0.68 and 0.72, respectively). CONCLUSIONS: On antepartum OGTT, the fasting glucose value best predicts LGA risk, whereas postload glucose values predict postpartum prediabetes/diabetes. These relationships may have implications for the glycemic thresholds that define obstetrical and metabolic risk.
BACKGROUND/ OBJECTIVE: The diagnosis of gestational diabetes mellitus on oral glucose tolerance test (OGTT) is used to identify risk of both neonatal large-for-gestational-age (LGA) and maternal postpartum prediabetes/diabetes. An assumption inherent in this practice, however, is that the glucose values that define gestational diabetes mellitus on the OGTT relate to both of these outcomes in the same way. Thus, to test this assumption, we sought to evaluate the predictive capacity of each glucose value on antepartum OGTT in relation to LGA and postpartum prediabetes/diabetes. DESIGN/SETTING/PARTICIPANTS: A total of 412 women representing the full spectrum of antepartum glucose tolerance underwent 3-h OGTT in pregnancy, assessment of obstetrical outcome at delivery, and 2-h OGTT at 3 months postpartum. RESULTS: Of the four glucose values (fasting, 1h, 2 h, 3 h) on antepartum OGTT, only the fasting measure was a significant predictor of LGA [odds ratio (OR) 2.00 per mmol/liter, 95% confidence interval (CI) 1.20-3.34] (P = 0.0076). In contrast, all three postload glucose values were significant predictors of postpartum prediabetes/diabetes (1 h glucose: OR 1.37, 95% CI 1.17-1.61, P < 0.0001; 2 h glucose: OR 1.55, 95% CI 1.32-1.83, P < 0.0001; 3 h glucose: OR 1.30, 95% CI 1.10-1.53, P = 0.002), whereas fasting glucose was not. Furthermore, whereas fasting glucose had the highest area under the receiver operating characteristic curve for predicting LGA (0.62), the 1- and 2-h glucose measures had the highest area under the receiver operating characteristic curve values for postpartum prediabetes/diabetes (0.68 and 0.72, respectively). CONCLUSIONS: On antepartum OGTT, the fasting glucose value best predicts LGA risk, whereas postload glucose values predict postpartum prediabetes/diabetes. These relationships may have implications for the glycemic thresholds that define obstetrical and metabolic risk.
Authors: Ravi Retnakaran; Ying Qi; Mathew Sermer; Philip W Connelly; Anthony J G Hanley; Bernard Zinman Journal: Diabetes Care Date: 2008-07-15 Impact factor: 19.112
Authors: A Tosun; S Duzguner; E Ozkaya; V Korkmaz; S Acar; B Gultekin; O Altinboga; I N Duzguner; T Kucukozkan Journal: Ir J Med Sci Date: 2014-06-08 Impact factor: 1.568
Authors: Ravi Retnakaran; Ying Qi; Philip W Connelly; Mathew Sermer; Bernard Zinman; Anthony J G Hanley Journal: J Clin Endocrinol Metab Date: 2009-11-19 Impact factor: 5.958
Authors: Sylvia H Ley; Deborah L O'Connor; Ravi Retnakaran; Jill K Hamilton; Mathew Sermer; Bernard Zinman; Anthony J Hanley Journal: BMC Public Health Date: 2010-10-06 Impact factor: 3.295
Authors: Simone Kew; Chang Ye; Mathew Sermer; Philip W Connelly; Anthony J G Hanley; Bernard Zinman; Ravi Retnakaran Journal: Diabetes Care Date: 2011-10-04 Impact factor: 19.112