Distinguishing atrial fibrillation from sinus rhythm using commercial pulse detection systems: The non-interventional BAYathlon study.
Digit Health
; 7: 20552076211019620, 2021.
Article
en En
| MEDLINE
| ID: mdl-34104466
ABSTRACT
OBJECTIVE:
Early diagnosis of atrial fibrillation (AFib) is a priority for stroke prevention. We sought to test four commercial pulse detection systems (CPDSs) for ability to distinguish AFib from normal sinus rhythm using a published algorithm (Zhou et al., PLoS One 2015;10e0136544), compared with visual diagnosis by electrocardiogram inspection.METHODS:
BAYathlon was a prospective, non-interventional, single-centre study. Adult cardiology patients with documented AFib or sinus rhythm who were due to have a routine 5-min electrocardiogram were randomized to undergo a parallel 5-min pulse assessment with a Polar V800, eMotion Faros 360, TomTom heart rate monitor, or Adidas miCoach Smart Run.RESULTS:
144 patients (73 with AFib, 71 with sinus rhythm (based on electrocardiograms); median age 73 years; 53.5% male) were analysed. Algorithm sensitivities (primary endpoint) and specificities for AFib when applied to CPDS recordings were 93.3% and 94.1% with the Polar V800, 90.0% and 84.2% with the eMotion Faros 360, and 0% and 100% with the other CPDSs (analysis period 127 heart rate signals + 2 min). When applied to routine electrocardiograms, the algorithm correctly detected AFib in 71/73 patients. Different analysis periods (127 heart rate signals +1 or 3 min) only slightly changed the sensitivities with the Polar V800 and eMotion Faros 360 and had no effect on the sensitivities with the other CPDSs.CONCLUSION:
AFib screening using the applied algorithm is feasible with the Polar V800 and eMotion Faros 360 (which provide RR interval data) but not with the other CPDSs (which provide pre-processed heart rate time series).ClinicalTrials.gov identifier NCT02875106.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Clinical_trials
/
Diagnostic_studies
/
Screening_studies
Idioma:
En
Revista:
Digit Health
Año:
2021
Tipo del documento:
Article
País de afiliación:
Alemania