Genetically-guided algorithm development and sample size optimization for age-related macular degeneration cases and controls in electronic health records from the VA Million Veteran Program.

Electronic health records (EHRs) linked to extensive biorepositories and supplemented with lifestyle, behavioral, and environmental exposure data, have enormous potential to contribute to genomic discovery, a necessary step in the pathway towards translational or precision medicine. A major bottleneck in incorporating EHRs into genomic studies is the extraction of research-grade variables for analysis, particularly when gold-standard measurements are not available or accessible. Here we develop algorithms for age-related macular degeneration (AMD), a common cause of blindness among the elderly, and controls free of AMD.

Lower A1c among adolescents with lower perceived A1c goal: a cross-sectional survey.

Background: The International Society for Pediatric and Adolescent Diabetes (ISPAD) and the American Diabetes Association (ADA) have established a hemoglobin A1c (A1c) target of less than 7.5% for adolescents with type 1 diabetes (T1D). However, many adolescents are unaware of their A1c target, and little data exist on how knowledge of this A1c target affects the actual A1c they achieve.