Can Common Clinical Parameters Be Used to Identify Patients Who Will Need Insulin Treatment in Gestational Diabetes Mellitus?

• Published in: Diabetes care Vol. 34; no. 10; pp. 2214 - 2216
• Main Authors: Pertot, Tania, Molyneaux, Lynda, Tan, Kris, Ross, Glynis P, Yue, Dennis K, Wong, Jencia
• Format: Journal Article
• Language: English
• Published: Alexandria, VA American Diabetes Association 01.10.2011
• Subjects: Adult; Biological and medical sciences; Blood Glucose - metabolism; Body Mass Index; Care and treatment; compliance; Dextrose; Diabetes; Diabetes in pregnancy; Diabetes therapy; Diabetes, Gestational - blood; Diabetes, Gestational - diagnosis; Diabetes, Gestational - drug therapy; Diabetes, Gestational - metabolism; Diabetes. Impaired glucose tolerance; Diabetics; Diagnosis; Endocrine pancreas. Apud cells (diseases); Endocrinopathies; fasting; Female; gestational diabetes; Glucose; glucose tolerance; Glucose Tolerance Test; Glucose tolerance tests; Glycated Hemoglobin A - metabolism; Humans; Hyperglycemia; Insulin; Insulin - therapeutic use; Insulin resistance; Life Style; lifestyle; Medical sciences; Metabolic diseases; Miscellaneous; nationalities and ethnic groups; Original Research; Patient Compliance; patients; Pregnancy; Public health. Hygiene; Public health. Hygiene-occupational medicine; regression analysis; risk; Risk factors; Studies; women; Human; Pancreatic hormone; Nutrition; Indication; Use; Patient; Metabolic diseases; Maternal diseases; Insulin; Pregnancy; Need; Treatment; Gestational diabetes; Endocrinology
• ISSN: 0149-5992; 1935-5548
• DOI: 10.2337/dc11-0499

OBJECTIVE: To identify patients with gestational diabetes mellitus (GDM) who will need antenatal insulin treatment (AIT) by using a risk-prediction tool based on maternal clinical and biochemical characteristics at diagnosis. RESEARCH DESIGN AND METHODS: Data from 3,009 women attending the Royal Prince Alfred Hospital GDM Clinic, Australia, between 1995 and 2010 were studied. A risk engine was developed from significant factors identified for AIT using a logistic regression model. RESULTS: A total of 51% of GDM patients required AIT. Ethnicity, gestation at diagnosis, HbA1c, fasting and 60-min glucose at oral glucose tolerance test, BMI, and diabetes family history were significant independent determinants of AIT. Notably, only 9% of the attributable risk for AIT can be explained by the clinical factors studied. A modeled risk-scoring system was therefore a poor predictor of AIT. CONCLUSIONS: Baseline maternal characteristics including HbA1c alone cannot predict the need for AIT in GDM. Lifestyle, compliance, or as yet unmeasured influences play a greater role in determining AIT.