Saul Blecker

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OBJECTIVEdTo examine the association between diabetes, glycemic control, and risk of fracture-related hospitalization in the Atherosclerosis Risk in Communities (ARIC) Study. We calculated the incidence rate of fracture-related hospitalization by age and used Cox proportional hazards models to investigate the association of diabetes with risk of fracture(More)
OBJECTIVE This study sought to investigate an association of HbA1c (A1C) with incident heart failure among individuals without diabetes and compare it to fasting glucose. RESEARCH DESIGN AND METHODS We studied 11,057 participants of the Atherosclerosis Risk in Communities (ARIC) Study without heart failure or diabetes at baseline and estimated hazard(More)
Early detection of Type 2 diabetes poses challenges to both the machine learning and medical communities. Current clinical practices focus on narrow patient-specific courses of action whereas electronic health records and insurance claims data give us the ability to generalize that knowledge across large sets of populations. Advances in population health(More)
BACKGROUND Exercise testing with echocardiography or myocardial perfusion imaging is widely used to risk-stratify patients with suspected coronary artery disease. However, reports of diagnostic performance rarely adjust for referral bias, and this practice may adversely influence patient care. Therefore, we evaluated the potential impact of referral bias on(More)
BACKGROUND Appropriate use criteria (AUC) for cardiac stress tests address concerns about utilization growth and patient safety. We systematically reviewed studies of appropriateness, including within physician specialties; evaluated trends over time and in response to AUC updates; and characterized leading indications for inappropriate/rarely appropriate(More)
We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative(More)
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