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Use of an electronic health record to identify prevalent and incident cardiovascular disease in type 2 diabetes according to treatment strategy
  1. Mary T Korytkowski1,
  2. Esra Karslioglu French2,
  3. Maria Brooks3,
  4. Dilhari DeAlmeida4,
  5. Justin Kanter5,
  6. Manuel Lombardero6,
  7. Vasudev Magaji7,
  8. Trevor Orchard3,
  9. Linda Siminerio8
  1. 1Division of Endocrinology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  2. 2Department of Medicine, NYU Langone Trinity Center, New York, New York, USA
  3. 3University of Pittsburgh, Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
  4. 4Department of Health Information Management, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  5. 5University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, USA
  6. 6Department of Epidemiology, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, Pennsylvania, USA
  7. 7Lehigh Valley Health Network, Diabetes and Endocrinology, Lehigh Valley, Pennsylvania, USA
  8. 8Division of Endocrinology and Metabolism, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  1. Correspondence to Dr Mary T Korytkowski; mtk7{at}


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.

  • Cardiovacsular Disease(s)
  • Electronic Medical Records
  • Hypoglycemic Agents
  • Type 2 Diabetes

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