Feasibility of Atrial Fibrillation Screening With Mobile Health Technologies at Pharmacies.


Journal

Journal of cardiovascular pharmacology and therapeutics
ISSN: 1940-4034
Titre abrégé: J Cardiovasc Pharmacol Ther
Pays: United States
ID NLM: 9602617

Informations de publication

Date de publication:
03 2020
Historique:
pubmed: 4 10 2019
medline: 15 9 2020
entrez: 4 10 2019
Statut: ppublish

Résumé

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Thus, the aim of our study was to evaluate the smartphone-based electrocardiogram (ECG) recordings aimed at AF screening at Polish pharmacies. Prospective AF screening among patients aged ≥65 years was conducted at 10 pharmacies using Kardia Mobile with a dedicated application (Kardia app). Prior AF was a study exclusion criterion. CHA A total of 525 ECGs were performed. Kardia app diagnosis was provided in 490 cases. In 437 (89.18%) cases, it was "normal" rhythm, in 17 (3.47%) recordings "possible AF," in 23 (4.69%) ECGs "unreadable," and in 13 (2.65%) "unclassified". After the cardiologist reevaluation, the new AF was identified in 7 (1.33%) patients. Sensitivity and specificity of Kardia app in detecting AF was 100% (95% confidence interval [CI]: 71.5%-100%) and 98.7% (95% CI: 97.3%-99.5%), respectively. The positive predictive value was 64.7% (95% CI: 38.3%-85.7%) and the negative predictive value was 100% (95% CI: 99.2%-100%). CHA Kardia app is capable of fast screening and detecting AF with high sensitivity and specificity. The possible diagnosis of AF deserves additional cardiological evaluation. The results obtained in patients with low CHA

Sections du résumé

BACKGROUND
Atrial fibrillation (AF) is the most common cardiac arrhythmia. Thus, the aim of our study was to evaluate the smartphone-based electrocardiogram (ECG) recordings aimed at AF screening at Polish pharmacies.
METHODS
Prospective AF screening among patients aged ≥65 years was conducted at 10 pharmacies using Kardia Mobile with a dedicated application (Kardia app). Prior AF was a study exclusion criterion. CHA
RESULTS
A total of 525 ECGs were performed. Kardia app diagnosis was provided in 490 cases. In 437 (89.18%) cases, it was "normal" rhythm, in 17 (3.47%) recordings "possible AF," in 23 (4.69%) ECGs "unreadable," and in 13 (2.65%) "unclassified". After the cardiologist reevaluation, the new AF was identified in 7 (1.33%) patients. Sensitivity and specificity of Kardia app in detecting AF was 100% (95% confidence interval [CI]: 71.5%-100%) and 98.7% (95% CI: 97.3%-99.5%), respectively. The positive predictive value was 64.7% (95% CI: 38.3%-85.7%) and the negative predictive value was 100% (95% CI: 99.2%-100%). CHA
CONCLUSION
Kardia app is capable of fast screening and detecting AF with high sensitivity and specificity. The possible diagnosis of AF deserves additional cardiological evaluation. The results obtained in patients with low CHA

Identifiants

pubmed: 31578088
doi: 10.1177/1074248419879089
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

142-151

Auteurs

Tomasz Zaprutko (T)

Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poznań, Poland.

Joanna Zaprutko (J)

Second Department of Cardiology, Poznan University of Medical Sciences, HCP Medical Center, Poznań, Poland.

Artur Baszko (A)

Second Department of Cardiology, Poznan University of Medical Sciences, HCP Medical Center, Poznań, Poland.

Dominika Sawicka (D)

Student Scientific Society, Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poland.

Anna Szałek (A)

Student Scientific Society, Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poland.
Student Scientific Society, Second Department of Cardiology, Poznan University of Medical Sciences, HCP Medical Center, Poznań, Poland.

Magdalena Dymecka (M)

Student Scientific Society, Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poland.

Wojciech Telec (W)

Second Department of Cardiology, Poznan University of Medical Sciences, HCP Medical Center, Poznań, Poland.

Dorota Kopciuch (D)

Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poznań, Poland.

Piotr Ratajczak (P)

Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poznań, Poland.

Michał Michalak (M)

Department of Computer Sciences and Statistics, Poznan University of Medical Sciences, Poznań, Poland.

Dankowski Rafał (D)

Second Department of Cardiology, Poznan University of Medical Sciences, HCP Medical Center, Poznań, Poland.

Andrzej Szyszka (A)

Second Department of Cardiology, Poznan University of Medical Sciences, HCP Medical Center, Poznań, Poland.

Elżbieta Nowakowska (E)

Department of Pharmacoeconomics and Social Pharmacy, Poznan University of Medical Sciences, Poznań, Poland.

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Classifications MeSH