Claire L Meek1,2, Diana Tundidor3,4, Denice S Feig5, Jennifer M Yamamoto6,7, Eleanor M Scott8, Diane D Ma9, Jose A Halperin9, Helen R Murphy10,11, Rosa Corcoy. 1. Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, U.K. clm70@cam.ac.uk corcoy@santpau.cat. 2. Cambridge Universities NHS Foundation Trust, Cambridge, U.K. 3. Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. 4. Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain. 5. Mount Sinai Hospital, Sinai Health System, Department of Medicine, University of Toronto, Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada. 6. Department of Internal Medicine, University of Manitoba, Winnipeg, Manitoba, Canada. 7. Department of Medicine, University of Calgary, Calgary, Alberta, Canada. 8. Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Centre for Diabetes and Endocrinology, University of Leeds, Leeds, U.K. 9. Laboratory for Translational Research, Harvard Medical School, Brigham and Women's Hospital, Boston, MA. 10. Norwich Medical School, University of East Anglia, Norwich, U.K. 11. School of Life Course Sciences, King's College London, London, U.K.
Abstract
OBJECTIVE: The optimal method of monitoring glycemia in pregnant women with type 1 diabetes remains controversial. This study aimed to assess the predictive performance of HbA1c, continuous glucose monitoring (CGM) metrics, and alternative biochemical markers of glycemia to predict obstetric and neonatal outcomes. RESEARCH DESIGN AND METHODS: One hundred fifty-seven women from the Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) were included in this prespecified secondary analysis. HbA1c, CGM data, and alternative biochemical markers (glycated CD59, 1,5-anhydroglucitol, fructosamine, glycated albumin) were compared at ∼12, 24, and 34 weeks' gestation using logistic regression and receiver operating characteristic (ROC) curves to predict pregnancy complications (preeclampsia, preterm delivery, large for gestational age, neonatal hypoglycemia, admission to neonatal intensive care unit). RESULTS: HbA1c, CGM metrics, and alternative laboratory markers were all significantly associated with obstetric and neonatal outcomes at 24 weeks' gestation. More outcomes were associated with CGM metrics during the first trimester and with laboratory markers (area under the ROC curve generally <0.7) during the third trimester. Time in range (TIR) (63-140 mg/dL [3.5-7.8 mmol/L]) and time above range (TAR) (>140 mg/dL [>7.8 mmol/L]) were the most consistently predictive CGM metrics. HbA1c was also a consistent predictor of suboptimal pregnancy outcomes. Some alternative laboratory markers showed promise, but overall, they had lower predictive ability than HbA1c. CONCLUSIONS: HbA1c is still an important biomarker for obstetric and neonatal outcomes in type 1 diabetes pregnancy. Alternative biochemical markers of glycemia and other CGM metrics did not substantially increase the prediction of pregnancy outcomes compared with widely available HbA1c and increasingly available CGM metrics (TIR and TAR).
OBJECTIVE: The optimal method of monitoring glycemia in pregnant women with type 1 diabetes remains controversial. This study aimed to assess the predictive performance of HbA1c, continuous glucose monitoring (CGM) metrics, and alternative biochemical markers of glycemia to predict obstetric and neonatal outcomes. RESEARCH DESIGN AND METHODS: One hundred fifty-seven women from the Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) were included in this prespecified secondary analysis. HbA1c, CGM data, and alternative biochemical markers (glycated CD59, 1,5-anhydroglucitol, fructosamine, glycated albumin) were compared at ∼12, 24, and 34 weeks' gestation using logistic regression and receiver operating characteristic (ROC) curves to predict pregnancy complications (preeclampsia, preterm delivery, large for gestational age, neonatal hypoglycemia, admission to neonatal intensive care unit). RESULTS: HbA1c, CGM metrics, and alternative laboratory markers were all significantly associated with obstetric and neonatal outcomes at 24 weeks' gestation. More outcomes were associated with CGM metrics during the first trimester and with laboratory markers (area under the ROC curve generally <0.7) during the third trimester. Time in range (TIR) (63-140 mg/dL [3.5-7.8 mmol/L]) and time above range (TAR) (>140 mg/dL [>7.8 mmol/L]) were the most consistently predictive CGM metrics. HbA1c was also a consistent predictor of suboptimal pregnancy outcomes. Some alternative laboratory markers showed promise, but overall, they had lower predictive ability than HbA1c. CONCLUSIONS: HbA1c is still an important biomarker for obstetric and neonatal outcomes in type 1 diabetes pregnancy. Alternative biochemical markers of glycemia and other CGM metrics did not substantially increase the prediction of pregnancy outcomes compared with widely available HbA1c and increasingly available CGM metrics (TIR and TAR).
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