Recruitment

Recruitment Status
Recruiting
Estimated Enrollment
Same as current

Summary

Conditions
Paroxysmal Atrial Fibrillation
Type
Interventional
Phase
Not Applicable
Design
Allocation: Non-RandomizedIntervention Model: Parallel AssignmentIntervention Model Description: Participants will receive a PPG sensor in form of a smartwatch or a bracelet and will be instructed to wear them continuously for 48 hours. Assigning patients to the smartwatch or the bracelet group will occur in an alternating fashion.Masking: None (Open Label)Primary Purpose: Diagnostic

Participation Requirements

Age
Between 18 years and 125 years
Gender
Both males and females

Description

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 se...

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.

Tracking Information

NCT #
NCT04563572
Collaborators
  • Preventicus GmbH
  • Manufacture Modules Technologies SA
  • GETEMED GmbH
  • Eurostars
Investigators
Principal Investigator: Jens Eckstein, MD, PhD University Hospital, Basel, Switzerland