Determine AF Burden With PPG Trial - Detection and Quantification of Episodes of Atrial Fibrillation Using a Cloud Analytics Service Connected to a Wearable With Photoplethysmographic (PPG) Sensor

Atrial fibrillation (AF) is the most common cardiac arrhythmia and a major risk factor for cerebrovascular insults. Paroxysmal AF is defined as an episode of AF that terminates spontaneously or with intervention within 7 days. Patients with AF may present with palpitations, shortness of breath or sensation of light-headedness but asymptomatic episodes are also possible, especially in paroxysmal AF. The lack of continuous heart rate monitoring options makes early diagnosis of paroxysmal AF challenging. In this prospective single-center trial, the PPG wearable Corsano CardioWatch 287 sensor will be used to conduct continuous heart rate and -rhythm monitoring in patients with known paroxysmal AF. Collected data will then be analysed using a Cloud Analytics Service (Preventicus Heartbeats algorithm) and compared with data from simultaneously obtained 48-hour Holter ECG. Correctly identified AF episodes, their cumulative duration per 48 hours (AF burden) and the number of asymptomatic episodes will be assessed. In the primary analyses, the sensitivity of the PPG analysing algorithm to detect AF episodes is estimated by performing a logistic regression on detection (yes/no) with only an intercept as predictor, which is then translated to a proportion (the sensitivity). In the secondary analyses we are comparing the cumulative duration of AF episodes over 48 hours (AF burden) obtained with the PPG-sensor and Holter-ECG. In summary, the purpose of the study is to evaluate the performance and efficacy of the wearable PPG sensor and the cloud analytics service in detecting and quantifying AF episodes in patients with known history of paroxysmal AF.