Stanford University has published the results of a new Apple Watch and iPhone study focused on functional mobility of cardiovascular disease patients. The data suggests that iPhone and Apple Watch can accurately asses “frailty,” both in-clinic and at home.
As first spotted by MyHealthyApple, the study was funded by Apple and consisted of 110 Veterans Affairs patients using an iPhone 7 and Apple Watch Series 3. The data was collected through a study app, VascTrac, as well as passively collected Activity data.
The study used the six-minute walking test score, or 6MWT. This was added in watchOS 7 and described as a “golden standard to evaluate the functional mobility of a patient.” The 6MWT is a common measure of frailty in the health industry. Higher scores on the 6MWT are indicative of “healthier cardiac, respiratory, circulatory, and neuromuscular function,” according to Apple.
In the study, patients conducted regular at-home six-minute walking tests, then compared those results to their in-clinic performance for the same test.
Weekly at-home 6MWTs were performed via the VascTrac app. The app passively collected activity data such as daily step counts. Logistic regression with forward feature selection was used to assess at-home 6MWT and passive data as predictors for “frailty” as measured by the gold-standard supervised 6MWT. Frailty was defined as walking <300m on an in-clinic 6MWT.
The study found that an Apple Watch can accurately assess frailty with a sensitivity of 90% and specificity of 85% in a clinical setting. In an unsupervised setting, the Apple Watch can accurately asses frailty with an 83% sensitivity and 60% specificity.
The study therefore draws the conclusion that the iPhone and Apple Watch can serve as an accurate predictor of frailty based on 6MWT performance. The study conclusion explains:
In this longitudinal observational study, passive activity data acquired by an iPhone and Apple Watch were an accurate predictor of in-clinic 6MWT performance. This finding suggests that frailty and functional capacity could be monitored and evaluated remotely in patients with cardiovascular disease, enabling safer and higher resolution monitoring of patients.
