Background: Racial inequities for patients with heart failure (HF) have been widely documented. HF patients who receive cardiology care during a hospital admission have better outcomes. It is unknown whether there are differences in admission to a cardiology or general medicine service by race. This study examined the relationship between race and admission service, and its effect on 30-day readmission and mortality Methods: We performed a retrospective cohort study from September 2008 to November 2017 at a single large urban academic referral center of all patients self-referred to the emergency department and admitted to either the cardiology or general medicine service with a principal diagnosis of HF, who self-identified as white, black, or Latinx. We used multivariable generalized estimating equation models to assess the relationship between race and admission to the cardiology service. We used Cox regression to assess the association between race, admission service, and 30-day readmission and mortality. Results: Among 1967 unique patients (66.7% white, 23.6% black, and 9.7% Latinx), black and Latinx patients had lower rates of admission to the cardiology service than white patients (adjusted rate ratio, 0.91; 95% CI, 0.84–0.98, for black; adjusted rate ratio, 0.83; 95% CI, 0.72–0.97 for Latinx). Female sex and age >75 years were also independently associated with lower rates of admission to the cardiology service. Admission to the cardiology service was independently associated with decreased readmission within 30 days, independent of race. Conclusions: Black and Latinx patients were less likely to be admitted to cardiology for HF care. This inequity may, in part, drive racial inequities in HF outcomes.
Next-generation sequencing provides the opportunity to practice predictive medicine based on identified variants. Putative loss-offunction (pLOF) variants are common in genomes and understanding their contribution to disease is critical for predictive medicine. To this end, we characterized the consequences of pLOF variants in an exome cohort by iterative phenotyping. Exome data were generated on 951 participants from the ClinSeq cohort and filtered for pLOF variants in genes likely to cause a phenotype in heterozygotes. 103 of 951 exomes had such a pLOF variant and 79 participants were evaluated. Of those 79, 34 had findings or family histories that could be attributed to the variant (28 variants in 18 genes), 2 had indeterminate findings (2 variants in 2 genes), and 43 had no findings or a negative family history for the trait (34 variants in 28 genes). The presence of a phenotype was correlated with two mutation attributes: prior report of pathogenicity for the variant (p ¼ 0.0001) and prior report of other mutations in the same exon (p ¼ 0.0001). We conclude that 1/30 unselected individuals harbor a pLOF mutation associated with a phenotype either in themselves or their family. This is more common than has been assumed and has implications for the setting of prior probabilities of affection status for predictive medicine.
Background Massively parallel sequencing to identify rare variants is widely practiced in medical research and in the clinic. Genome and exome sequencing can identify the genetic cause of a disease (primary results), but can also identify pathogenic variants underlying diseases that are not being sought (secondary or incidental results). A major controversy has developed surrounding the return of secondary results to research participants. We have piloted a method to analyze exomes to identify participants at-risk for cardiac arrhythmias, cardiomyopathies or sudden death. Methods and Results Exome sequencing was performed on 870 participants not selected for arrhythmia, cardiomyopathy, or a family history of sudden death. Exome data from 22 cardiac arrhythmia and 41 cardiomyopathy-associated genes were analyzed using an algorithm that filtered results on genotype quality, frequency, and database information. We identified 1367 variants in the cardiomyopathy genes and 360 variants in the arrhythmia genes. Six participants had pathogenic variants associated with dilated cardiomyopathy (n=1), hypertrophic cardiomyopathy (n=2), left ventricular noncompaction (n=1) or long QT syndrome (n=2). Two of these participants had evidence of cardiomyopathy and one had left ventricular noncompaction on ECHO. Three participants with likely pathogenic variants had prolonged QTc. Family history included unexplained sudden death among relatives. Conclusions Approximately 0.5% of participants in this study had pathogenic variants in known cardiomyopathy or arrhythmia genes. This high frequency may be due to self-selection, false positives, or underestimation of the prevalence of these conditions. We conclude that clinically important cardiomyopathy and dysrhythmia secondary variants can be identified in unselected exomes.
Health disparities fall along racial lines, in part, due to structural inequalities limiting health care access. The concept of race is often taught in health professions education with a clear biologic underpinning despite the significant debate in the literature as to whether race is a social or biologic construct. The teaching of race as a biologic construct, however, allows for the simplification of race as a risk factor for disease. As health care providers, it is part of our professional responsibility and duty to patients to think and talk about race in a way that is cognizant of broader historical, political, and cultural literature and context. Openly discussing the topic of race in medicine is not only uncomfortable but also difficult given its controversies and complicated context. In response, we provide several evidence-based steps to guide discussions around race in clinical settings, while also hopefully limiting the use of bias and racism in the practice of medicine.
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