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The Apple Watch Heart study



Atrial fibrillation (AFib) is the most common cardiac arrhythmia. Prevalence of AFib is expected to double within the next 40 years in adults 55 years or older. AFib has a tremendous economic impact due to its association with increased morbidity and mortality, particularly 5-fold higher risk for stroke.

Silent or undetected AFib is common in the general population and in cryptogenic stroke patients (CRYSTAL AF). Detection and diagnosis of AFib is an extremely important task to provide proper management of patients with this arrhythmia such as reduction of burden of symptoms, prevention of severe complications (stroke and heart failure) and improvement of survival. Oral anticoagulation can reduce the risk of stroke in patients with AFib, but unfortunately, 18% of AF-associated strokes present with newly detected AFib.

The European Society of Cardiology guidelines for the management of AFib recommend screening for AFib all patients 65 years and older by pulse palpation and ESG recording and ECG monitoring1. These opportunistic AFib screening methods, including ECG monitoring during 2-7 days, rarely register paroxysmal AF and asymptomatic AFib. New methods of AFib screening are available now: implantable cardiac monitoring, smartphone applications, wearable fitness trackers.

In the United States, 77% of people have smartphones, 13% have smartwatches and the expanding consumer base of these devices allows an opportunity to perform an irregular pulse detection study.

The Apple Heart Study (AHS), performed from Nov 29, 2017 to Feb 25, 2019, is a prospective, single arm pragmatic study that has enrolled 419,297 participants (NCT03335800). The objective of the study was to evaluate the ability of the irregular pulse notification by Apple Watch to identify AFib and guide subsequent clinical evaluation of trial participants (Figure 1).

The primary objective was to measure the proportion of participants with an irregular pulse detected by the Apple Watch (Apple Inc, Cupertino, CA) which has a pulse rate sensor. AHS used photoplethysmography to measure blood flow activity and to detect subtle changes in the form of a tachogram, which in turn helps in identifying irregular heartbeats. The primary endpoints were AFib >30 s on ECG patch and simultaneous AFib on ECG patch and tachogram for those aged ≥65 and for participants of all ages. The secondary objectives were to:

  1. characterize the concordance of pulse irregularity episodes notification from the Apple watch with simultaneously recorded ambulatory ECGs;
  2. estimate the rate of initial contact with a health care provider within 3 months after notification of pulse irregularity2.

The goal of the objective is to understand how this technology would be received by participants, how participants would interact with virtual study health providers, how effectively the information is conveyed to their primary physicians, how real-world clinicians respond by measuring healthcare resources that are ultimately utilized.

Results

Irregular pulse notifications were rare – overall AHS 0.52% (0.49-0.54)3 (Figure 2).  Notification rates were most frequent – 3.2% in older participants - 65 years old and older.  AFib was confirmed by ECG patch in 34% with overall AHS irregular pulse notification and in 35% participants ≥65 years old.

Positive predictive value for AFib (positive tachograms compared to AFib on ECG patch): 0.71(0.69-0.74); positive predictive value for AFib (positive notifications compared to AFib on ECG patch): 0.84 (0.76-0.92).

90-day survey results after irregular rhythm was registered demonstrated, that only 57% participants of AHS contacted with non-study providers. Additional testing performed in 36% of these AHS participants, 33% participants referred to specialists and 28% participants started new medication. Add slide 5 or 20 from 3?

Conclusion

The Apple Heart Study is one of the largest AFib identification studies, it provides initial evaluation of the ability of a smartwatch algorithm to identify pulse irregularity, which may reveal previously unknown AFib in a broad population cohort.

References

  1. Kirchhof P., Benusssi S., Kotecha D., et al. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. EHJ 2016;37(38):2893-2962. http://doi.org/10.1093eurheartj/ehw210
  2. Turakhia M.P., Desai M., Hedlin H., et al. Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study. AmHeartJ2019;207:66-75.
  3. http://doi.org/10.1016/j.ahj.2018.09.002