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OBJECTIVE To examine whether diabetes genetic risk testing and counseling can improve diabetes prevention behaviors. RESEARCH DESIGN AND METHODS We conducted a randomized trial of diabetes genetic risk counseling among overweight patients at increased phenotypic risk for type 2 diabetes. Participants were randomly allocated to genetic testing versus no(More)
W ith the exception of rare mono-genic disorders, most type 2 diabetes results from the interaction of genetic variation at multiple different chromosomal sites with environmental exposures experienced throughout the lifespan (1). This complex genetic architecture has important consequences for understanding the pathophysiology of type 2 diabetes, both for(More)
Advances in genetic epidemiology have increased understanding of common, polygenic preventable diseases such as type 2 diabetes. As genetic risk testing based on this knowledge moves into clinical practice, we propose that genetic counselors will need to expand their roles and adapt traditional counseling techniques for this new patient set. In this paper,(More)
Patient experience was assessed by survey as part of a large, randomized controlled trial of a secure, practice-linked personal health record called Patient Gateway at Partners HealthCare in Boston, MA. The subjects were patients with Type 2 diabetes who prepared for their upcoming primary care visit using a previsit electronic journal. The journal(More)
OBJECTIVE To test if knowledge of type 2 diabetes genetic variants improves disease prediction. RESEARCH DESIGN AND METHODS We tested 40 single nucleotide polymorphisms (SNPs) associated with diabetes in 3,471 Framingham Offspring Study subjects followed over 34 years using pooled logistic regression models stratified by age (<50 years, diabetes cases =(More)
OBJECTIVE The appropriateness and effectiveness of the outpatient medical management of cardiac risk factors for patients with diabetes who had a diagnosis of schizophrenia or a related psychotic syndrome were examined. METHODS In a cross-sectional analysis of 4,236 patients with diabetes, ICD-9 billing codes were used to identify 214 patients with(More)
OBJECTIVE Rapid advances in diabetes genetic epidemiology may lead to a new era of "personalized medicine" based on individual genetic risk assessment. There is minimal experience to guide how best to clinically implement such testing so that results (e.g., "higher" or "lower" relative genetic risk) improve rather than reduce patient motivation for behavior(More)
OBJECTIVE To assess the ability to identify potential association(s) of diabetes medications with myocardial infarction using usual care clinical data obtained from the electronic medical record. RESEARCH DESIGN AND METHODS We defined a retrospective cohort of patients (n = 34,253) treated with a sulfonylurea, metformin, rosiglitazone, or pioglitazone in a(More)
BACKGROUND Prevention of diabetes and coronary heart disease (CHD) is possible but identification of at-risk patients for targeting interventions is a challenge in primary care. METHODS We analyzed electronic health record (EHR) data for 122,715 patients from 12 primary care practices. We defined patients with risk factor clustering using metabolic(More)