Smartphone-based cardiac implantable electronic device remote monitoring: improved compliance and connectivity

Author:

Manyam Harish12,Burri Haran3ORCID,Casado-Arroyo Ruben4ORCID,Varma Niraj5ORCID,Lennerz Carsten6ORCID,Klug Didier7,Carr-White Gerald8,Kolli Kranthi9ORCID,Reyes Ignacio9,Nabutovsky Yelena9,Boriani Giuseppe10ORCID

Affiliation:

1. Department of Cardiovascular Medicine, University of Tennessee College of Medicine Chattanooga , 979 East Third Street, Suite C-520, Chattanooga, TN 37403 , USA

2. Heart and Lung Institute, Erlanger Health System , 975 E. 3rd St., Suite C520, Chattanooga, TN 37403 , USA

3. Cardiac Pacing Unit, Cardiology Department, University Hospital of Geneva , Rue Gabrielle Perret Gentil 4, 1205 Geneva , Switzerland

4. Department of Cardiology, Université Libre de Bruxelles , 1070 Bruxelles , Belgium

5. Cleveland Clinic Heart and Vascular Institute , Cleveland, OH , USA

6. Department of Electrophysiology, German Heart Centre Munich , 80636 Munich , Germany

7. Department of Cardiology, University Hospital of Lille , 59037 Lille , France

8. Department of Cardiology, Guy’s and St Thomas’ NHS Foundation Trust , London , UK

9. Abbott, Global Data Science and Analytics , CA 95054 , USA

10. Cardiology Division, Department of Biomedical Metabolic and Neural Sciences, University of Modena and Reggio Emilia , 41124 Modena , Italy

Abstract

Abstract Aims Remote monitoring (RM) is the standard of care for follow up of patients with cardiac implantable electronic devices. The aim of this study was to compare smartphone-based RM (SM-RM) using patient applications (myMerlinPulse™ app) with traditional bedside monitor RM (BM-RM). Methods and results The retrospective study included de-identified US patients who received either SM-RM or BM-RM capable of implantable cardioverter defibrillators or cardiac resynchronization therapy defibrillators (Abbott, USA). Patients in SM-RM and BM-RM groups were propensity-score matched on age and gender, device type, implant year, and month. Compliance with RM was quantified as the proportion of patients enrolling in the RM system (Merlin.net™) and transmitting data at least once. Connectivity was measured by the median number of days between consecutive transmissions per patient. Of the initial 9714 patients with SM-RM and 26 679 patients with BM-RM, 9397 patients from each group were matched. Remote monitoring compliance was higher in SM-RM; significantly more patients with SM-RM were enrolled in RM compared with BM-RM (94.4 vs. 85.0%, P < 0.001), similar number of patients in the SM-RM group paired their device (95.1 vs. 95.0%, P = 0.77), but more SM-RM patients transmitted at least once (98.1 vs. 94.3%, P < 0.001). Connectivity was significantly higher in the SM-RM, with patients transmitting data every 1.2 (1.1, 1.7) vs. every 1.7 (1.5, 2.0) days with BM-RM (P < 0.001) and remained better over time. Significantly more SM-RM patients utilized patient-initiated transmissions compared with BM-RM (55.6 vs. 28.1%, P < 0.001). Conclusion In this large real-world study, patients with SM-RM demonstrated improved compliance and connectivity compared with BM-RM.

Funder

Abbott

Publisher

Oxford University Press (OUP)

Subject

Energy Engineering and Power Technology,Fuel Technology

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