Performance of a multi-sensor implantable defibrillator algorithm for heart failure monitoring in the presence of atrial fibrillation

Author:

Boriani Giuseppe1ORCID,Bertini Matteo2ORCID,Manzo Michele3ORCID,Calò Leonardo4ORCID,Santini Luca5ORCID,Savarese Gianluca6,Dello Russo Antonio7ORCID,Santobuono Vincenzo Ezio8ORCID,Lavalle Carlo9ORCID,Viscusi Miguel10,Amellone Claudia11,Calvanese Raimondo12ORCID,Santoro Amato13ORCID,Rapacciuolo Antonio14ORCID,Ziacchi Matteo15ORCID,Arena Giuseppe16ORCID,Imberti Jacopo F117ORCID,Campari Monica18,Valsecchi Sergio18ORCID,D’Onofrio Antonio19ORCID

Affiliation:

1. Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena , Modena , Italy

2. Cardiology Department, University of Ferrara, S. Anna University Hospital , Ferrara , Italy

3. Cardiology Department, OO.RR. San Giovanni di Dio Ruggi d'Aragona , Salerno , Italy

4. Division of Cardiology, Policlinico Casilino , Rome , Italy

5. Division of Cardiology, Giovan Battista Grassi’ Hospital , Rome , Italy

6. Division of Cardiology, ‘S. Giovanni Battista’ Hospital , Foligno , Italy

7. Cardiology and Arrhythmology Clinic, Marche Polytechnic University , Ancona , Italy

8. University Cardiology Unit, Interdisciplinary Department of Medicine, University of Bari Aldo Moro, Policlinico di Bari , Bari , Italy

9. Department of Clinical, Internal, Anesthesiologist and Cardiovascular Sciences, Sapienza University of Rome , Rome , Italy

10. Cardiology Department, S. Anna e S. Sebastiano Hospital , Caserta , Italy

11. Division of Cardiology, ‘Maria Vittoria’ Hospital , Turin , Italy

12. Cardiology Department, Ospedale del Mare , ASL NA1, Naples , Italy

13. Division of Cardiology, AOU Senese , Siena , Italy

14. Department of Advanced Biomedical Sciences, Federico II University of Naples , Naples , Italy

15. Cardiology Unit, Cardio-Thoracic and Vascular Department, S.Orsola University Hospital, University of Bologna , Bologna , Italy

16. Cardiology Department, Ospedale Civile Apuane , Massa (MS) , Italy

17. Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia , Modena , Italy

18. Rhythm Management Division, Boston Scientific , Milan , Italy

19. Unità Operativa di Elettrofisiologia, Studio e Terapia delle Aritmie, Monaldi Hospital , Naples , Italy

Abstract

Abstract Aims The HeartLogic Index combines data from multiple implantable cardioverter defibrillators (ICDs) sensors and has been shown to accurately stratify patients at risk of heart failure (HF) events. We evaluated and compared the performance of this algorithm during sinus rhythm and during long-lasting atrial fibrillation (AF). Methods and results HeartLogic was activated in 568 ICD patients from 26 centres. We found periods of ≥30 consecutive days with an atrial high-rate episode (AHRE) burden <1 h/day and periods with an AHRE burden ≥20 h/day. We then identified patients who met both criteria during the follow-up (AHRE group, n = 53), to allow pairwise comparison of periods. For control purposes, we identified patients with an AHRE burden <1 h throughout their follow-up and implemented 2:1 propensity score matching vs. the AHRE group (matched non-AHRE group, n = 106). In the AHRE group, the rate of alerts was 1.2 [95% confidence interval (CI): 1.0–1.5]/patient-year during periods with an AHRE burden <1 h/day and 2.0 (95% CI: 1.5–2.6)/patient-year during periods with an AHRE-burden ≥20 h/day (P = 0.004). The rate of HF hospitalizations was 0.34 (95% CI: 0.15–0.69)/patient-year during IN-alert periods and 0.06 (95% CI: 0.02–0.14)/patient-year during OUT-of-alert periods (P < 0.001). The IN/OUT-of-alert state incidence rate ratio of HF hospitalizations was 8.59 (95% CI: 1.67–55.31) during periods with an AHRE burden <1 h/day and 2.70 (95% CI: 1.01–28.33) during periods with an AHRE burden ≥20 h/day. In the matched non-AHRE group, the rate of HF hospitalizations was 0.29 (95% CI: 0.12–0.60)/patient-year during IN-alert periods and 0.04 (95% CI: 0.02–0.08)/patient-year during OUT-of-alert periods (P < 0.001). The incidence rate ratio was 7.11 (95% CI: 2.19–22.44). Conclusion Patients received more alerts during periods of AF. The ability of the algorithm to identify increased risk of HF events was confirmed during AF, despite a lower IN/OUT-of-alert incidence rate ratio in comparison with non-AF periods and non-AF patients. Clinical Trial Registration http://clinicaltrials.gov/Identifier: NCT02275637

Publisher

Oxford University Press (OUP)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

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