TY - JOUR
T1 - Can eHealth programs for cardiac arrhythmias be scaled-up by using the KardiaMobile algorithm?
AU - Slaats, Bridget M. I.
AU - Blok, Sebastiaan
AU - Somsen, G. Aernout
AU - Tulevski, Igor I.
AU - Knops, Reinoud E.
AU - van den Born, Bert-Jan H.
AU - Winter, Michiel M.
N1 - Publisher Copyright: © 2023 Heart Rhythm Society
PY - 2023
Y1 - 2023
N2 - Background: Remote monitoring devices for atrial fibrillation are known to positively contribute to the diagnostic process and therapy compliance. However, automatic algorithms within devices show varying sensitivity and specificity, so manual double-checking of electrocardiographic (ECG) recordings remains necessary. Objective: The purpose of this study was to investigate the validity of the KardiaMobile algorithm within the Dutch telemonitoring program (HartWacht). Methods: This retrospective study determined the diagnostic accuracy of the algorithm using assessments by a telemonitoring team as reference. The sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and F1 scores were determined. Results: A total of 2298 patients (59.5% female; median age 57 ± 15 years) recorded 86,816 ECGs between April 2019 and January 2021. The algorithm showed sensitivity of 0.956, specificity 0.985, PPV 0.996, NPV 0.847, and F1 score 0.976 for the detection of sinus rhythm. A total of 29 false-positive outcomes remained uncorrected within the same patients. The algorithm showed sensitivity of 0.989, specificity 0.953, PPV 0.835, NPV 0.997, and F1 score 0.906 for detection of atrial fibrillation. A total of 2 false-negative outcomes remained uncorrected. Conclusion: Our research showed high validity of the algorithm for the detection of both sinus rhythm and, to a lesser extent, atrial fibrillation. This finding suggests that the algorithm could function as a standalone instrument particularly for detection of sinus rhythm.
AB - Background: Remote monitoring devices for atrial fibrillation are known to positively contribute to the diagnostic process and therapy compliance. However, automatic algorithms within devices show varying sensitivity and specificity, so manual double-checking of electrocardiographic (ECG) recordings remains necessary. Objective: The purpose of this study was to investigate the validity of the KardiaMobile algorithm within the Dutch telemonitoring program (HartWacht). Methods: This retrospective study determined the diagnostic accuracy of the algorithm using assessments by a telemonitoring team as reference. The sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and F1 scores were determined. Results: A total of 2298 patients (59.5% female; median age 57 ± 15 years) recorded 86,816 ECGs between April 2019 and January 2021. The algorithm showed sensitivity of 0.956, specificity 0.985, PPV 0.996, NPV 0.847, and F1 score 0.976 for the detection of sinus rhythm. A total of 29 false-positive outcomes remained uncorrected within the same patients. The algorithm showed sensitivity of 0.989, specificity 0.953, PPV 0.835, NPV 0.997, and F1 score 0.906 for detection of atrial fibrillation. A total of 2 false-negative outcomes remained uncorrected. Conclusion: Our research showed high validity of the algorithm for the detection of both sinus rhythm and, to a lesser extent, atrial fibrillation. This finding suggests that the algorithm could function as a standalone instrument particularly for detection of sinus rhythm.
KW - Atrial fibrillation
KW - Diagnostic accuracy
KW - HartWacht program
KW - Single-lead electrocardiography
KW - Sinus rhythm
UR - http://www.scopus.com/inward/record.url?scp=85179112204&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.cvdhj.2023.11.004
DO - https://doi.org/10.1016/j.cvdhj.2023.11.004
M3 - Article
SN - 2666-6936
JO - Cardiovascular Digital Health Journal
JF - Cardiovascular Digital Health Journal
ER -