Introduction:
Electronic medical records (EMR) contain a wealth of phenotypic information with high potential to replace costly traditional epidemiological methods for purposes such as determining disease risk factors. EMRs designed for clinical and billing applications frequently do not meet the standardization and quality of data essential for biomedical research.
Hypothesis:
Using abdominal aortic aneurysm (AAA) as a model, we assessed the hypothesis that utilizing EMR in a retrospective study is comparable to traditional epidemiologic methods for risk factor assessment of a complex disease.
Methods:
The Geisinger Health System is the main health provider serving a highly stable population in central and northeastern Pennsylvania. Clinical and diagnostic data from January 2004 to December 2009 were extracted from the Geisinger EMR. The study population consisted of cases diagnosed with AAA (
n
=964) and controls without AAA from the Geisinger MyCode
®
biobanking repository (
n
=14,555). The de-identified dataset was cleaned and formatted for research purposes. Data were analyzed unmatched, then cases were matched to controls on the confounders of sex, age, body mass index and smoking status. Matching was performed randomly, by propensity score and by group-frequency procedures. Bootstrap replication procedures (with and without replacement) confirmed the reproducibility of the results.
Results:
We replicated the direction and magnitude of several risk factors commonly noted in traditional epidemiologic AAA studies. Type 2 diabetes was associated with a decreased risk (OR=0.61, 95%CI 0.40–0.93). Peripheral artery disease (OR=2.94, 95%CI 1.81–4.78), kidney disease (OR=2.78, 95%CI 1.68–4.61), coronary occlusive disease (OR=2.64, 95%CI 1.79–3.88), cranial artery occlusive disease (OR=4.82, 95%CI 2.84–8.16), and pulmonary disease (OR=2.14, 95%CI 1.44–3.20) were all associated with an increased risk of AAA. In our population, the diagnosis of benign neoplasms was significantly inversely associated with AAA, a novel finding (OR=0.55, 95%CI 0.38–0.80). Pulse pressure was the most significant measure of hypertension associated with AAA (OR of 1.25 per 10 mmHg).
Conclusions:
This study demonstrated that EMR data can be feasibly used to assess risk factors and identify new associations. These findings could serve to enhance the current AAA screening guidelines to more efficiently target patients and increase screening utilization.
Abdominal Aortic Aneurysm and Aortic Occlusive Disease: a Comparison of Risk Factors and Inflammatory Response
