Rapid identification of myocardial infarction risk associated with diabetes medications using electronic medical records.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 20009093.
- Also identified by DOI 10.2337/dc09-1506 and PMC identifier 2827502.
- Licence recorded as CC BY-NC-ND.
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Abstract
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 single academic health care network. All patients were aged >18 years with at least one prescription for one of the medications between 1 January 2000 and 31 December 2006. The study outcome was acute myocardial infarction requiring hospitalization. We used a cumulative temporal approach to ascertain the calendar date for earliest identifiable risk associated with rosiglitazone compared with that for other therapies. RESULTS Sulfonylurea, metformin, rosiglitazone, or pioglitazone therapy was prescribed for 11,200, 12,490, 1,879, and 806 patients, respectively. A total of 1,343 myocardial infarctions were identified. After adjustment for potential myocardial infarction risk factors, the relative risk for myocardial infarction with rosiglitazone was 1.3 (95% CI 1.1-1.6) compared with sulfonylurea, 2.2 (1.6-3.1) compared with metformin, and 2.2 (1.5-3.4) compared with pioglitazone. Prospective surveillance using these data would have identified increased risk for myocardial infarction with rosiglitazone compared with metformin within 18 months of its introduction with a risk ratio of 2.1 (95% CI 1.2-3.8). CONCLUSIONS Our results are consistent with a relative adverse cardiovascular risk profile for rosiglitazone. Our use of usual care electronic data sources from a large hospital network represents an innovative approach to rapid safety signal detection that may enable more effective postmarketing drug surveillance.
Medical subject headings
- Diabetes Mellitus
- Electronic Health Records
- Hypoglycemic Agents
- Mass Screening
- Myocardial Infarction