Refined heart failure detection algorithm for improved clinical reliability of OptiVol alerts in CRT-D recipients

Mate Vamos, Noemi Nyolczas, Zsolt Bari, Peter Bogyi, Balazs Muk, Barna Szabo, Bettina Ancsin, R. Kiss, G. Duray

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Background: The reliability of intrathoracic impedance monitoring for prediction of heart failure (HF) by implantable cardiac devices is controversial. Despite using additional device-based parameters described in the PARTNERS HF study, such as new onset of arrhythmias, abnormal autonomics, low biventricular pacing rate or patient activity level, the predictive power of device diagnostic algorithm is still in doubt. The objective of this study was to compare the device diagnostic algorithm described in the PARTNERS HF study to a newly developed algorithm applying refined diagnostic criteria. Methods: Fourty two patients were prospectively enrolled who had been implanted with an intrathoracic impedance and remote monitoring capable implantable cardiac defibrillator with a cardiac resychroniza-tion therapy (CRT-D) device in this observational study. If a remote OptiVol™ alert occurred, patients were checked for presence of HF symptoms. A new algorithm was derived from the original PARTNERS HF criteria, considering more sensitive cut-offs and changes of patterns of the device-based parameters. Results: During an average follow-up of 38 months, 722 remote transmissions were received. From the total of 128 transmissions with OptiVol alerts, 32 (25%) corresponded to true HF events. Upon multivariate discriminant analysis, low patient activity, high nocturnal heart rate, and low CRT pacing (< 90%) proved to be independent predictors of true HF events (all p < 0.01). Incorporating these three refined criteria in a new algorithm, the diagnostic yield of OptiVol was improved by increasing specificity from 37.5% to 86.5%, positive predictive value from 34.1% to 69.8% and area under the curve from 0.787 to 0.922 (p < 0.01), without a relevant loss in sensitivity (96.9% vs. 93.8%). Conclusions: A refined device diagnostic algorithm based on the parameters of low activity level, high nocturnal heart rate, and suboptimal biventricular pacing might improve the clinical reliability of OptiVol alerts.

Original languageEnglish
Pages (from-to)236-244
Number of pages9
JournalCardiology Journal
Volume25
Issue number2
DOIs
Publication statusPublished - Apr 27 2018

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Heart Failure
Equipment and Supplies
Cardiac Resynchronization Therapy
Electric Impedance
Heart Rate
Implantable Defibrillators
Discriminant Analysis
Area Under Curve
Observational Studies
Cardiac Arrhythmias
Multivariate Analysis

Keywords

  • Congestive heart failure
  • CRT-D
  • Intrathoracic impedance monitoring
  • OptiVol
  • Remote monitoring

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Refined heart failure detection algorithm for improved clinical reliability of OptiVol alerts in CRT-D recipients. / Vamos, Mate; Nyolczas, Noemi; Bari, Zsolt; Bogyi, Peter; Muk, Balazs; Szabo, Barna; Ancsin, Bettina; Kiss, R.; Duray, G.

In: Cardiology Journal, Vol. 25, No. 2, 27.04.2018, p. 236-244.

Research output: Contribution to journalArticle

Vamos, Mate ; Nyolczas, Noemi ; Bari, Zsolt ; Bogyi, Peter ; Muk, Balazs ; Szabo, Barna ; Ancsin, Bettina ; Kiss, R. ; Duray, G. / Refined heart failure detection algorithm for improved clinical reliability of OptiVol alerts in CRT-D recipients. In: Cardiology Journal. 2018 ; Vol. 25, No. 2. pp. 236-244.
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abstract = "Background: The reliability of intrathoracic impedance monitoring for prediction of heart failure (HF) by implantable cardiac devices is controversial. Despite using additional device-based parameters described in the PARTNERS HF study, such as new onset of arrhythmias, abnormal autonomics, low biventricular pacing rate or patient activity level, the predictive power of device diagnostic algorithm is still in doubt. The objective of this study was to compare the device diagnostic algorithm described in the PARTNERS HF study to a newly developed algorithm applying refined diagnostic criteria. Methods: Fourty two patients were prospectively enrolled who had been implanted with an intrathoracic impedance and remote monitoring capable implantable cardiac defibrillator with a cardiac resychroniza-tion therapy (CRT-D) device in this observational study. If a remote OptiVol™ alert occurred, patients were checked for presence of HF symptoms. A new algorithm was derived from the original PARTNERS HF criteria, considering more sensitive cut-offs and changes of patterns of the device-based parameters. Results: During an average follow-up of 38 months, 722 remote transmissions were received. From the total of 128 transmissions with OptiVol alerts, 32 (25{\%}) corresponded to true HF events. Upon multivariate discriminant analysis, low patient activity, high nocturnal heart rate, and low CRT pacing (< 90{\%}) proved to be independent predictors of true HF events (all p < 0.01). Incorporating these three refined criteria in a new algorithm, the diagnostic yield of OptiVol was improved by increasing specificity from 37.5{\%} to 86.5{\%}, positive predictive value from 34.1{\%} to 69.8{\%} and area under the curve from 0.787 to 0.922 (p < 0.01), without a relevant loss in sensitivity (96.9{\%} vs. 93.8{\%}). Conclusions: A refined device diagnostic algorithm based on the parameters of low activity level, high nocturnal heart rate, and suboptimal biventricular pacing might improve the clinical reliability of OptiVol alerts.",
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AU - Nyolczas, Noemi

AU - Bari, Zsolt

AU - Bogyi, Peter

AU - Muk, Balazs

AU - Szabo, Barna

AU - Ancsin, Bettina

AU - Kiss, R.

AU - Duray, G.

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N2 - Background: The reliability of intrathoracic impedance monitoring for prediction of heart failure (HF) by implantable cardiac devices is controversial. Despite using additional device-based parameters described in the PARTNERS HF study, such as new onset of arrhythmias, abnormal autonomics, low biventricular pacing rate or patient activity level, the predictive power of device diagnostic algorithm is still in doubt. The objective of this study was to compare the device diagnostic algorithm described in the PARTNERS HF study to a newly developed algorithm applying refined diagnostic criteria. Methods: Fourty two patients were prospectively enrolled who had been implanted with an intrathoracic impedance and remote monitoring capable implantable cardiac defibrillator with a cardiac resychroniza-tion therapy (CRT-D) device in this observational study. If a remote OptiVol™ alert occurred, patients were checked for presence of HF symptoms. A new algorithm was derived from the original PARTNERS HF criteria, considering more sensitive cut-offs and changes of patterns of the device-based parameters. Results: During an average follow-up of 38 months, 722 remote transmissions were received. From the total of 128 transmissions with OptiVol alerts, 32 (25%) corresponded to true HF events. Upon multivariate discriminant analysis, low patient activity, high nocturnal heart rate, and low CRT pacing (< 90%) proved to be independent predictors of true HF events (all p < 0.01). Incorporating these three refined criteria in a new algorithm, the diagnostic yield of OptiVol was improved by increasing specificity from 37.5% to 86.5%, positive predictive value from 34.1% to 69.8% and area under the curve from 0.787 to 0.922 (p < 0.01), without a relevant loss in sensitivity (96.9% vs. 93.8%). Conclusions: A refined device diagnostic algorithm based on the parameters of low activity level, high nocturnal heart rate, and suboptimal biventricular pacing might improve the clinical reliability of OptiVol alerts.

AB - Background: The reliability of intrathoracic impedance monitoring for prediction of heart failure (HF) by implantable cardiac devices is controversial. Despite using additional device-based parameters described in the PARTNERS HF study, such as new onset of arrhythmias, abnormal autonomics, low biventricular pacing rate or patient activity level, the predictive power of device diagnostic algorithm is still in doubt. The objective of this study was to compare the device diagnostic algorithm described in the PARTNERS HF study to a newly developed algorithm applying refined diagnostic criteria. Methods: Fourty two patients were prospectively enrolled who had been implanted with an intrathoracic impedance and remote monitoring capable implantable cardiac defibrillator with a cardiac resychroniza-tion therapy (CRT-D) device in this observational study. If a remote OptiVol™ alert occurred, patients were checked for presence of HF symptoms. A new algorithm was derived from the original PARTNERS HF criteria, considering more sensitive cut-offs and changes of patterns of the device-based parameters. Results: During an average follow-up of 38 months, 722 remote transmissions were received. From the total of 128 transmissions with OptiVol alerts, 32 (25%) corresponded to true HF events. Upon multivariate discriminant analysis, low patient activity, high nocturnal heart rate, and low CRT pacing (< 90%) proved to be independent predictors of true HF events (all p < 0.01). Incorporating these three refined criteria in a new algorithm, the diagnostic yield of OptiVol was improved by increasing specificity from 37.5% to 86.5%, positive predictive value from 34.1% to 69.8% and area under the curve from 0.787 to 0.922 (p < 0.01), without a relevant loss in sensitivity (96.9% vs. 93.8%). Conclusions: A refined device diagnostic algorithm based on the parameters of low activity level, high nocturnal heart rate, and suboptimal biventricular pacing might improve the clinical reliability of OptiVol alerts.

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