Skip to main navigation menu Skip to main content Skip to site footer
##common.pageHeaderLogo.altText##

Original article

Vol. 153 No. 9 (2023)

Accuracy in detecting atrial fibrillation in single-lead ECGs: an online survey comparing the influence of clinical expertise and smart devices

  • Simon Weidlich
  • Diego Mannhart
  • Teodor Serban
  • Philipp Krisai
  • Sven Knecht
  • Jeanne du Fay de Lavallaz
  • Tatjana Müller
  • Beat Schaer
  • Stefan Osswald
  • Michael Kühne
  • Christian Sticherling
  • Patrick Badertscher
DOI
https://doi.org/10.57187/smw.2023.40096
Cite this as:
Swiss Med Wkly. 2023;153:40096
Published
01.09.2023

Summary

BACKGROUND: Manual interpretation of single-lead ECGs (SL-ECGs) is often required to confirm a diagnosis of atrial fibrillation. However accuracy in detecting atrial fibrillation via SL-ECGs may vary according to clinical expertise and choice of smart device.

AIMS: To compare the accuracy of cardiologists, internal medicine residents and medical students in detecting atrial fibrillation via SL-ECGs from five different smart devices (Apple Watch, Fitbit Sense, KardiaMobile, Samsung Galaxy Watch, Withings ScanWatch). Participants were also asked to assess the quality and readability of SL-ECGs.

METHODS: In this prospective study (BaselWearableStudy, NCT04809922), electronic invitations to participate in an online survey were sent to physicians at major Swiss hospitals and to medical students at Swiss universities. Participants were asked to classify up to 50 SL-ECGs (from ten patients and five devices) into three categories: sinus rhythm, atrial fibrillation or inconclusive. This classification was compared to the diagnosis via a near-simultaneous 12-lead ECG recording interpreted by two independent cardiologists. In addition, participants were asked their preference of each manufacturer’s SL-ECG.

RESULTS: Overall, 450 participants interpreted 10,865 SL-ECGs. Sensitivity and specificity for the detection of atrial fibrillation via SL-ECG were 72% and 92% for cardiologists, 68% and 86% for internal medicine residents, 54% and 65% for medical students in year 4–6 and 44% and 58% for medical students in year 1–3; p <0.001. Participants who stated prior experience in interpreting SL-ECGs demonstrated a sensitivity and specificity of 63% and 81% compared to a sensitivity and specificity of 54% and 67% for participants with no prior experience in interpreting SL-ECGs (p <0.001). Of all participants, 107 interpreted all 50 SL-ECGs. Diagnostic accuracy for the first five interpreted SL-ECGs was 60% (IQR 40–80%) and diagnostic accuracy for the last five interpreted SL-ECGs was 80% (IQR 60–90%); p <0.001. No significant difference in the accuracy of atrial fibrillation detection was seen between the five smart devices; p = 0.33. SL-ECGs from the Apple Watch were considered as having the best quality and readability by 203 (45%) and 226 (50%) participants, respectively.

CONCLUSION: SL-ECGs can be challenging to interpret. Accuracy in correctly identifying atrial fibrillation depends on clinical expertise, while the choice of smart device seems to have no impact.

References

  1. Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, et al.; ESC Scientific Document Group. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS): The Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Eur Heart J. 2021 Feb;42(5):373–498. 10.1093/eurheartj/ehaa612 DOI: https://doi.org/10.1093/eurheartj/ehab648
  2. Selder JL, Breukel L, Blok S, van Rossum AC, Tulevski II, Allaart CP. A mobile one-lead ECG device incorporated in a symptom-driven remote arrhythmia monitoring program. The first 5,982 Hartwacht ECGs. Neth Heart J. 2019 Jan;27(1):38–45. 10.1007/s12471-018-1203-4 DOI: https://doi.org/10.1007/s12471-018-1203-4
  3. William AD, Kanbour M, Callahan T, Bhargava M, Varma N, Rickard J, et al. Assessing the accuracy of an automated atrial fibrillation detection algorithm using smartphone technology: the iREAD Study. Heart Rhythm. 2018 Oct;15(10):1561–5. 10.1016/j.hrthm.2018.06.037 DOI: https://doi.org/10.1016/j.hrthm.2018.06.037
  4. Avram R, Ramsis M, Cristal AD, Nathan V, Zhu L, Kim J, et al. Validation of an algorithm for continuous monitoring of atrial fibrillation using a consumer smartwatch. Heart Rhythm. 2021 Sep;18(9):1482–90. 10.1016/j.hrthm.2021.03.044 DOI: https://doi.org/10.1016/j.hrthm.2021.03.044
  5. Seshadri DR, Bittel B, Browsky D, Houghtaling P, Drummond CK, Desai MY, et al. Accuracy of Apple Watch for Detection of Atrial Fibrillation. Circulation. 2020 Feb;141(8):702–3. 10.1161/CIRCULATIONAHA.119.044126 DOI: https://doi.org/10.1161/CIRCULATIONAHA.119.044126
  6. Ford C, Xie CX, Low A, Rajakariar K, Koshy AN, Sajeev JK, et al. Comparison of 2 Smart Watch Algorithms for Detection of Atrial Fibrillation and the Benefit of Clinician Interpretation: SMART WARS Study. JACC Clin Electrophysiol. 2022 Jun;8(6):782–91. 10.1016/j.jacep.2022.02.013 DOI: https://doi.org/10.1016/j.jacep.2022.02.013
  7. Bumgarner JM, Lambert CT, Hussein AA, Cantillon DJ, Baranowski B, Wolski K, et al. Smartwatch Algorithm for Automated Detection of Atrial Fibrillation. J Am Coll Cardiol. 2018 May;71(21):2381–8. 10.1016/j.jacc.2018.03.003 DOI: https://doi.org/10.1016/j.jacc.2018.03.003
  8. Badertscher P, Lischer M, Mannhart D, Knecht S, Isenegger C, Du Fay de Lavallaz J, et al. Clinical validation of a novel smartwatch for automated detection of atrial fibrillation. Heart Rhythm O2. 2022 Feb;3(2):208–10. 10.1016/j.hroo.2022.02.004 DOI: https://doi.org/10.1016/j.hroo.2022.02.004
  9. Mannhart D, Lischer M, Knecht S, du Fay de Lavallaz J, Strebel I, Serban T, et al. Clinical Validation of 5 Direct-to-Consumer Wearable Smart Devices to Detect Atrial Fibrillation: BASEL Wearable Study. JACC Clin Electrophysiol. 2023 Feb;9(2):232–42. 10.1016/j.jacep.2022.09.011 DOI: https://doi.org/10.1016/j.jacep.2022.09.011
  10. Schnabel RB, Marinelli EA, Arbelo E, Boriani G, Boveda S, Buckley CM, et al. Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference. EP Europace 2022. doi:10.1093/europace/euac062 DOI: https://doi.org/10.1093/europace/euac062
  11. Leclercq C, Witt H, Hindricks G, Katra RP, Albert D, Belliger A, et al. Wearables, telemedicine, and artificial intelligence in arrhythmias and heart failure: Proceedings of the European Society of Cardiology Cardiovascular Round Table. EP Europace. 2022;24:1372–83. doi:10.1093/europace/euac052 DOI: https://doi.org/10.1093/europace/euac052
  12. Kalarus Z, Mairesse GH, Sokal A, Boriani G, Średniawa B, Arroyo RC, et al. Searching for atrial fibrillation: looking harder, looking longer, and in increasingly sophisticated ways. An EHRA position paper. EP Europace; 2022. 10.1093/europace/euac144 DOI: https://doi.org/10.1093/europace/euac144
  13. Svennberg E, Tjong F, Goette A, Akoum N, Di Biase L, Bordachar P, et al. How to use digital devices to detect and manage arrhythmias: an EHRA practical guide. Europace. 2022 Jul;24(6):979–1005. 10.1093/europace/euac038 DOI: https://doi.org/10.1093/europace/euac038
  14. Linz D, Hermans A, Tieleman RG. Early atrial fibrillation detection and the transition to comprehensive management. Europace. 2021 Apr;23(23 Suppl 2):ii46–51. 10.1093/europace/euaa424 DOI: https://doi.org/10.1093/europace/euaa424
  15. Boriani G, Svennberg E, Guerra F, Linz D, Casado-Arroyo R, Malaczynska-Rajpold K, et al. Reimbursement practices for use of digital devices in atrial fibrillation and other arrhythmias: a European Heart Rhythm Association survey. Europace. 2022 Nov;24(11):1834–43. 10.1093/europace/euac142 DOI: https://doi.org/10.1093/europace/euac142
  16. Manninger M, Zweiker D, Svennberg E, Chatzikyriakou S, Pavlovic N, Zaman JA, et al. Current perspectives on wearable rhythm recordings for clinical decision-making: the wEHRAbles 2 survey. Europace. 2021 Jul;23(7):1106–13. 10.1093/europace/euab064 DOI: https://doi.org/10.1093/europace/euab064
  17. Saxon LA. Ubiquitous wireless ECG recording: a powerful tool physicians should embrace. J Cardiovasc Electrophysiol. 2013 Apr;24(4):480–3. 10.1111/jce.12097 DOI: https://doi.org/10.1111/jce.12097
  18. Nasarre M, Strik M, Daniel Ramirez F, Buliard S, Marchand H, Abu-Alrub S, et al. Using a smartwatch electrocardiogram to detect abnormalities associated with sudden cardiac arrest in young adults. Europace. 2022 Mar;24(3):406–12. 10.1093/europace/euab192 DOI: https://doi.org/10.1093/europace/euab192
  19. Mannhart D, Hennings E, Lischer M, Vernier C, Du Fay de Lavallaz J, Knecht S, et al. Clinical Validation of Automated Corrected QT-Interval Measurements From a Single Lead Electrocardiogram Using a Novel Smartwatch. Front Cardiovasc Med. 2022 Jun;9:906079. 10.3389/fcvm.2022.906079 DOI: https://doi.org/10.3389/fcvm.2022.906079
  20. Stark K, Czermak T, Massberg S, Orban M. Watch out for ST-elevation myocardial infarction: a case report of ST-elevation in single-lead electrocardiogram tracing of a smartwatch. Eur Heart J Case Rep. 2020 Nov;4(6):1–4. 10.1093/ehjcr/ytaa353 DOI: https://doi.org/10.1093/ehjcr/ytaa353
  21. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, et al.; REDCap Consortium. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019 Jul;95:103208. 10.1016/j.jbi.2019.103208 DOI: https://doi.org/10.1016/j.jbi.2019.103208
  22. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377–81. 10.1016/j.jbi.2008.08.010 DOI: https://doi.org/10.1016/j.jbi.2008.08.010
  23. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007 Oct;335(7624):806–8. 10.1136/bmj.39335.541782.AD DOI: https://doi.org/10.1136/bmj.39335.541782.AD
  24. Gruwez H, Evens S, Proesmans T, Duncker D, Linz D, Heidbuchel H, et al. Accuracy of Physicians Interpreting Photoplethysmography and Electrocardiography Tracings to Detect Atrial Fibrillation: INTERPRET-AF. Front Cardiovasc Med. 2021 Sep;8:734737. 10.3389/fcvm.2021.734737 DOI: https://doi.org/10.3389/fcvm.2021.734737
  25. Himmelreich JC, Karregat EP, Lucassen WA, van Weert HC, de Groot JR, Handoko ML, et al. Diagnostic Accuracy of a Smartphone-Operated, Single-Lead Electrocardiography Device for Detection of Rhythm and Conduction Abnormalities in Primary Care. Ann Fam Med. 2019 Sep;17(5):403–11. 10.1370/afm.2438 DOI: https://doi.org/10.1370/afm.2438
  26. Karregat EP, Himmelreich JC, Lucassen WA, Busschers WB, van Weert HC, Harskamp RE. Evaluation of general practitioners’ single-lead electrocardiogram interpretation skills: a case-vignette study. Fam Pract. 2021 Mar;38(2):70–5. 10.1093/fampra/cmaa076 DOI: https://doi.org/10.1093/fampra/cmaa076
  27. Koshy AN, Sajeev JK, Negishi K, Wong MC, Pham CB, Cooray SP, et al. Accuracy of blinded clinician interpretation of single-lead smartphone electrocardiograms and a proposed clinical workflow. Am Heart J. 2018 Nov;205:149–53. 10.1016/j.ahj.2018.08.001 DOI: https://doi.org/10.1016/j.ahj.2018.08.001
  28. Abu-Alrub S, Strik M, Ramirez FD, Moussaoui N, Racine HP, Marchand H, et al. Smartwatch Electrocardiograms for Automated and Manual Diagnosis of Atrial Fibrillation: A Comparative Analysis of Three Models. Front Cardiovasc Med. 2022 Feb;9:836375. 10.3389/fcvm.2022.836375 DOI: https://doi.org/10.3389/fcvm.2022.836375
  29. Mant J, Fitzmaurice DA, Hobbs FD, Jowett S, Murray ET, Holder R, et al. Accuracy of diagnosing atrial fibrillation on electrocardiogram by primary care practitioners and interpretative diagnostic software: analysis of data from screening for atrial fibrillation in the elderly (SAFE) trial. BMJ. 2007 Aug;335(7616):380. 10.1136/bmj.39227.551713.AE DOI: https://doi.org/10.1136/bmj.39227.551713.AE

Most read articles by the same author(s)

1 2 3 > >>