Use of an electronic health record to identify prevalent and incident cardiovascular disease in type 2 diabetes according to treatment strategy. Issue 1 (26th May 2016) - Korytkowski, Mary T; Karslioglu French, Esra; Brooks, Maria; DeAlmeida, Dilhari; Kanter, Justin; Lombardero, Manuel; Magaji, Vasudev; Orchard, Trevor; Siminerio, Linda
Abstract : Background: The increasing use of electronic health records (EHRs) in clinical practice offers the potential to investigate cardiovascular outcomes over time in patients with type 2 diabetes (T2D). Objective: To develop a methodology for identifying prevalent and incident cardiovascular disease (CVD) in patients with T2D who are candidates for therapeutic intensification of glucose-lowering therapy. Methods: Patients with glycated hemoglobin (HbA1c) ≥7% (53 mmol/mol) while receiving 1–2 oral diabetes medications (ODMs) were identified from an EHR (2005–2011) and grouped according to intensification with insulin (INS) (n=372), a different class of ODM (n=833), a glucagon-like peptide receptor 1 agonist (GLP-1RA) (n=59), or no additional therapy (NAT) (n=2017). Baseline prevalence of CVD was defined by documented International Classification of Diseases Ninth Edition (ICD-9) codes for coronary artery disease, cerebrovascular disease, or other CVD with first HbA1c ≥7% (53 mmol/mol). Incident CVD was defined as a new ICD-9 code different from existing codes over 4 years of follow-up. ICD-9 codes were validated by a chart review in a subset of patients. Results: Sensitivity of ICD-9 codes for CVD ranged from 0.83 to 0.89 and specificity from 0.90 to 0.96. Baseline prevalent (INS vs ODM vs GLP-1RA vs NAT: 65% vs 39% vs 54% vs 59%, p<0.001) and incident CVD (Kaplan-Meier estimates: 58%, 31%, 52%, and 54%, p=0.002) were greater in INS group after controlling for differences in baseline HbA1c (9.2±2.0% vs 8.3±1.2% vs 8.2±1.3% vs 7.7±1.1% (77 vs 67 vs 66 vs 61 mmol/mol), p<0.001) and creatinine (1.15±0.96 vs 1.10±0.36 vs 1.01±0.35 vs 1.07±0.45 mg/dL, p=0.001). Conclusions: An EHR can be an effective method for identifying prevalent and incident CVD in patients with T2D.