Atrial Fibrillation Screening With Photo-plethysmography Through a Smartphone Camera

Frederik H. Verbrugge; Tine Proesmans; Johan Vijgen; Wilfried Mullens; Maximo Rivero-Ayerza; Hugo Van Herendael; Pieter Vandervoort; Dieter Nuyens

Disclosures

Europace. 2019;21(8):1167-1175. 

In This Article

Results

Screening Coverage

After publication of the article on smartphone-based AF screening in the layman's press, 12 328 individuals registered for voluntarily participation to the screening programme and completed at least one measurement with a PPG signal of sufficient quality for analysis within the 7-day study period. A group of 480 subscribers (3.7%) was excluded, because they either had performed no heart rhythm measurements or did only achieve measurements of insufficient quality because of an incompatible smartphone. With the local community served by the newspaper as the denominator, the screening coverage of the overall population was 1.43%. Screening uptake was highest in individuals 40–69 years of age and substantially decreased below 20 years and above 70 years (Figure 2). Among study participants, 1179 (10%) strictly adhered to the recommended screening protocol of at least two measurements per day. Premature drop-out from screening, defined as compliance with the screening protocol on Day 1, but no measurements on Day 7 was observed in 3328 (27%).

Figure 2.

Screening coverage of the overall population after the publication of one local newspaper article (print + online) providing free access for atrial fibrillation screening through a smartphone-based application during a 7-day period.

Screened Population and Diagnostic Yield for Possible Atrial Fibrillation

The average age of the screened population was 49 ± 14 years with 7184 male genders (58%). Possible AF was detected by the application's algorithm and confirmed by offline analysis of the corresponding raw PPG signals in 136 participants for an overall prevalence of 1.1%. Population characteristics according to the potential presence of AF are presented in Table 1. The prevalence of possible AF increased from 0.1% in the age group <40 years to 11.1% in individuals ≥80 years (Figure 3). Individuals with a diagnosis of possible AF were more frequently men compared with women (P < 0.001) and had a higher body mass index (P = 0.004). The proportion of study participants diagnosed with AF was 1.9% vs. 1.0% in individuals who did vs. did not adhere to the recommended screening frequency, respectively (P = 0.008). The cumulative diagnostic yield for possible AF increased from 0.4% with a single heart rhythm assessment performed to 1.4% with screening during the entire 7-day screening period (Figure 4).

Figure 3.

Prevalence of atrial fibrillation in the screened population according to age.

Figure 4.

Cumulative diagnostic yield (curve) and prevalence (arrow) for atrial fibrillation during the 7-day screening period. The cumulative diagnostic yield is calculated based on the number of participants performing measurements on the corresponding days. The prevalence is calculated based on the total study population.

Photo-plethysmography Signal Quality

Measurements by study participants generated 120 446 unique PPG traces of 60 s duration. PPG signal quality was sufficient for analysis in 110 713 cases (92%). The frequency of measurements with insufficient quality for analysis decreased significantly during the screening period, from 17% on Day 1 to 2% on Day 7 (P < 0.001; Figure 5).

Figure 5.

Frequency of smartphone-based photo-plethysmography measurements of insufficient quality for analysis during the study period.

Heart rhythm Analysis by the Smartphone Application

A flowchart of the results of heart rhythm screening by the smartphone application's algorithm and confirmation by secondary offline analysis of the raw PPG data is provided in Figure 6. In 98 586 measurements (89%), the algorithm classified the heart rhythm as normal and no further action was performed. In 12 127 cases (11%), possible irregularities were identified of whom 615 (5%) were confirmed as possible AF by confirmatory offline analysis of the raw PPG data. The average revision time per irregular measurement was 7 s. Examples of different PPG measurements are given in Figure 7.

Figure 6.

A flowchart of the results of heart rhythm screening by the smartphone application's algorithm and confirmation by secondary offline analysis of the raw PPG data. PPG, photo-plethysmography.

Figure 7.

Examples of raw PPG traces and their tachogram and Poincaré plot, representing different rhythms. PPG, photo-plethysmography.

The average result on the 5-point Likert scale for well-being was 2.6 ± 2.3 in cases with confirmed AF vs. 2.6 ± 2.2 in cases where the heart rhythm was classified as normal (P = 0.556). Associated symptoms during measurements are presented in Figure 8. Symptoms of palpitations, confusion, and shortness of breath were more frequent in measurements that were indicative for AF (P < 0.001). Palpitations were the most frequently reported symptom at 11% in individuals with possible AF. Overall, individuals did report symptoms in 139/615 (24%) of measurements indicative for AF.

Figure 8.

Symptoms associated with heart rhythm assessments according to its result. AF, atrial fibrillation.

Patient-reported Outcomes

Screen-positive participants were informed of the detection of possible AF in their end-report and referred to a medical professional to confirm diagnosis. Four months after reporting, they were contacted to collect outcome information. One hundred screening-positive subjects consented to provide this information. Forty subjects did not have a prior diagnosis, of which 53% consulted a physician and had the diagnosis confirmed on ECG. Sixty subjects were known AF patients, of which 28% received an adjustment of their current care strategy after consultation of a physician. Persistent or permanent AF was confirmed on 12-lead ECG, paroxysmal AF was confirmed on Holter monitor or implantable loop recorder.

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