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Background: Dilated cardiomyopathy (DCM) contributes significantly to heart failure prevalence, yet supporting epidemiologic data is sparse. This study sought to estimate the period prevalence of DCM and the proportion of idiopathic DCM in the United States using a large, diverse electronic health records (EHR) database. Methods: This retrospective, observational study included 56,812,806 deidentified patients in Optum EHR with visits between 2017 and 2019. Suspected DCM cases were identified using ICD-10 coding. Deidentified clinical notes from 1000 randomly selected cases were manually reviewed to determine the diagnosis of DCM and estimate the proportion of idiopathic DCM. The period prevalence and clinical burden of DCM and idiopathic DCM were estimated. Results: Manual clinical review demonstrated that our definition had a positive predictive value of 92.5% for DCM, with 46.3% estimated as the idiopathic DCM proportion. The estimated period prevalence of DCM between 2017 and 2019 was 118.33 per 100,000. Prevalence increased for adults ≥65 years of age, males, and African Americans. Extrapolation to the 2019 US population led to an overall estimated burden of roughly 388,350 patients. Adjusting for the proportion of cases with idiopathic DCM yielded an idiopathic DCM prevalence of 59.23 per 100,000 and a burden of 194,385 patients. Evidence of clinical genetic testing in this population was scarce, with less than 0.43% of DCM cases reporting a testing code. Conclusions: This study establishes a conservative period prevalence for DCM and idiopathic DCM and demonstrates very low molecular genetic testing for DCM. These findings suggest that the clinical burden of genetic DCM may be underestimated.
RESUMO
BACKGROUND: Wide disparities in health status exist in the United States across race and ethnicity, broadly driven by social determinants of health-most notably race and ethnic group differences in income, education, and occupational status. However, disparities in disease frequency or severity remain underappreciated for many individual diseases whose distribution in the population varies. Such information is not readily accessible, nor emphasized in treatment guidelines or reviews used by practitioners. Specifically, a summary on disease-specific evidence of disparities from population-based studies is lacking. Our goal was to summarize the published evidence for specific disease disparities in the United States so that this knowledge becomes more widely available "at the bedside". We hope this summary stimulates health equity research at the disease level so that these disparities can be addressed effectively. METHODS: A targeted literature review of disorders in Pfizer's current pipeline was conducted. The 38 diseases included metabolic disorders, cancers, inflammatory conditions, dermatologic disorders, rare diseases, and infectious targets of vaccines under development. Online searches in Ovid and Google were performed to identify sources focused on differences in disease rates and severity between non-Hispanic Whites and Black/African Americans, and between non-Hispanic Whites and Hispanics. As a model for how this might be accomplished for all disorders, disparities in disease rates and disease severity were scored to make the results of our review most readily accessible. After primary review of each condition by one author, another undertook an independent review. Differences between reviewers were resolved through discussion. RESULTS: For Black/African Americans, 29 of the 38 disorders revealed a robust excess in incidence, prevalence, or severity. After sickle cell anemia, the largest excesses in frequency were identified for multiple myeloma and hidradenitis suppurativa. For Hispanics, there was evidence of disparity in 19 diseases. Most notable were metabolic disorders, including non-alcoholic steatohepatitis (NASH). CONCLUSIONS: This review summarized recent disease-specific evidence of disparities based on race and ethnicity across multiple diseases, to inform clinicians and health equity research. Our findings may be well known to researchers and specialists in their respective fields but may not be common knowledge to health care providers or public health and policy institutions. Our hope is that this effort spurs research into the causes of the many disease disparities that exist in the United States.