Comparison of two smartphone based atrial fibrillation screening application in Indonesian population
Background: Due to its adverse outcomes and thromboembolic complications, early detection of atrial fibrillation (AF) is advisable in the general population. This study aims to compare the diagnostic ability of two distinct method in smartphone application format, namely : AliveCor KardiaMobile and FibriCheck.
Methods: This study was conducted in Mohammad Hospital General Hospital Palembang with convenience sampling of 170 participants aged 18 years or older. The subjects underwent Fibricheck and KardiaMobile recordings followed by 12 lead electrocardiogram read by board-certified cardiologist as the diagnostic standard.
Results: After the exclusion of previous pacemaker implantation (n=7), 163 patients were included in the study. The mean age was 51±15 years with gender distribution of 74.8% men and 25.2% women. Most of the subjects were asymptomatic (87.1%) with mean blood pressure of 130/80 mmHg. The Fibricheck readings showed sensitivity of 73% and specificity of 93%, meanwhile Kardiamobile was able to detect AF with sensitivity of 77% and specificity of 98%.
Conclusion: In our study, KardiaMobile demonstrated overall greater sensitivity and specificity when compared to FibriCheck. However, KardiaMobile requires an external metal sensor that must be puchased separately. To the best of our knowledge, this is the first study to directly compare both methods in the Indonesian population.
 Ramkumar S, Nerlekar N, D’Souza D, Pol DJ, Kalman JM and Marwick TH. Atrial fibrillation detection using single lead portable electrocardiographic monitoring: a systematic review and meta-analysis BMJ Open. 2018;8
 Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, Castella M, Diener H-C, Heidbuchel H, Hendriks J, Hindricks G, Manolis A S, Oldgren J, Popescu B A, Schotten U, Van Putte B, Vardas P, Agewall S, Camm J, Baron Esquivias G, Budts W, Carerj S, Casselman F, Coca A, De Caterina R, Deftereos S, Dobrev D, Ferro J M, Filippatos G, Fitzsimons D, Gorenek B, Guenoun M, Hohnloser S H, Kolh P, Lip G Y H, Manolis A, McMurray J, Ponikowski P, Rosenhek R, Ruschitzka F, Savelieva I, Sharma S, Suwalski P, Tamargo J L, Taylor C J, Van Gelder I C, Voors A A, Windecker S, Zamorano J L and Zeppenfeld K. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS European Journal of Cardio-Thoracic Surgery. 2016;50 e1-e88
 Guzik P and Malik M. ECG by mobile technologies Journal of Electrocardiology. 2016;49 894-901
 McManus DD, Lee J, Maitas O, Esa N, Pidikiti R, Carlucci A, Harrington J, Mick E and Chon KH. A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation Heart Rhythm. 2013;10 315-9
 Walker A and Muhlestein J. Smartphone electrocardiogram monitoring: current perspectives Advanced Health Care Technologies. 2018; 4 15-24
 Hund T, Nguyen HH, Van Hare GF, Rudokas M, Bowman T and Silva JN .SPEAR Trial: Smartphone Pediatric ElectrocARdiogram Trial Plos One. 2015;10
 Haberman ZC, Jahn RT, Bose R, Tun HA, Shinbane JS, Doshi RN, Chang PM and Saxon LA. Wireless Smartphone ECG Enables Large-Scale Screening in Diverse Populations Journal of Cardiovascular Electrophysiology. 2015;26 520-6
 Lau JK, Lowres N, Neubeck L, Brieger DB, Sy RW, Galloway CD, Albert DE and Freedman SB. iPhone ECG application for community screening to detect silent atrial fibrillation: A novel technology to prevent stroke International Journal of Cardiology. 2013;165 193-4
 Proesmans T, Mortelmans C, Van Haelst R, Verbrugge F, Vandervoort P and Vaes B. Mobile Phone–Based Use of the Photoplethysmography Technique to Detect Atrial Fibrillation in Primary Care: Diagnostic Accuracy Study of the FibriCheck App JMIR mHealth and uHealth. 2019;7
 Deng L and Xu S. Adaptation of human skin color in various populations Hereditas. 2017;155
 Dörr M, Nohturfft V, Brasier N, Bosshard E, Djurdjevic A, Gross S, Raichle CJ, Rhinisperger M, Stöckli R and Eckstein J. The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation JACC: Clinical Electrophysiology. 2019;5 199-208
 Sy RW, Brieger DB, Lau JK, Wallenhorst C, Martinez C, Bauman A, Briffa T, Bennett AA, Redfern J, McLachlan AJ, Krass I, Salkeld G, Neubeck L, Lowres N and Freedman SB. Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies Thrombosis and Haemostasis. 2017;111 1167-76
 Chan PH, Wong CK, Poh YC, Pun L, Leung WW, Wong YF, Wong MM , Poh MZ, Chu DW S and Siu CW. Diagnostic Performance of a Smartphone‐Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting Journal of the American Heart Association. 2016;5
 Evans GF, Shirk A, Muturi P and Soliman EZ. Feasibility of Using Mobile ECG Recording Technology to Detect Atrial Fibrillation in Low-Resource Settings Global Heart. 2017; 12 285-9
PDF downloads: 98
Copyright (c) 2021 Indonesian Journal of Cardiology
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).