Cardiologists from Yale University have released a ResearchKit app, Yale Cardiomyopathy Index, to engage patients with cardiomyopathy in a longitudinal study of their health and quality of life.
The Yale Cardiomyopathy Index app aims to collect data on patients with really any kind of cardiomyopathy. It was developed by Drs. E. Kevin Hall and Michele Spencer-Manzon, who both come at this with a pediatrics background. Dr. Hall is the director of the pediatric heart failure program and Dr. Spencer-Manzon is a geneticist.
The study appears to case an incredibly wide net. Kids as young as two years old are eligible to participate with the consent of their parents. The background of the apps’ creators comes through in the study design, particularly in the way cardiomyopathies are classified in the app. Participants can indicate cardiomyopathy etiologies including hypertrophic, ischemic, dilated/non-ischemic, restrictive, LV non-compaction, and arrhythmogenic (presumably ARVD).
Over time, participants will periodically fill out questionnaires, in particular around quality of life. One of the particularly interesting parts of this study are plans to conduct 6 minute walk tests, directed by the app. Participants who have connected heart rate monitors can also upload heart rate data. The data will be stored at Yale and participants can indicate whether they are ok with de-identified data being shared with other institutions for analysis.
As far as ResearchKit studies, the Yale Cardiomyopathy Index is definitely one of the broadest in terms of scope. It could also prove to be one of the most challenging. Cardiomyopathy is a technical term that few of my patients ever use. They are far more likely to talk about their “heart failure,” and patients with heart failure are an incredibly heterogenous group. I wonder what percentage of patients with “heart failure” know whether they have a cardiomyopathy or not, let alone the etiology. Once we get all the way down to that group, selection bias seems like it would become a big issue.
To some extent, those limitations could be overcome by one of the strengths of this approach – getting huge numbers. ResearchKit apps directed towards cardiovascular disease and asthma have certainly seen extraordinary success in recruitment. Once there are enough patients enrolled, it could be that several subsets will have more complete, rich data for analysis.
For decades, prospective cohort studies have delivered incredible insights into health and disease. Just over fifty years ago, studies out of Framingham began to describe the concept of “risk factors” and identified several for heart disease, like high blood pressure. Those studies, however, are incredibly expensive. Digital health technology seems poised to form the foundation for the prospective cohorts of the future, collecting data on a scale orders of magnitude greater than previously possible.
As this first wave of studies gets off the ground, it will be interesting to see how their successes and failures unfold and shape future digital cohort studies.