Future of bradyarrhythmia therapy systems: automaticity

Jones, Bruce R; Kim, Jungkuk; Zhu, Qing–Ling; Nelson, Jonathan D.; KenKnight, Bruce H.; Lang, Douglas J.; Warren, Jay

doi:10.1016/s0002-9149(98)01023-6

Cited by 14 publications

(6 citation statements)

References 35 publications

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“…Several automatic algorithms have been implemented in pacemaker therapy for automatic capture detection, sensing detection, impedance measurement, and longevity estimation [149], [154]. New control algorithms based on fuzzy logic are being investigated for rate adaptive pacing [155].…”

Section: A Pacemakers and Cardiology Devicesmentioning

confidence: 99%

A BioMEMS Review: MEMS Technology for Physiologically Integrated Devices

et al. 2004

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Section: A Pacemakers and Cardiology Devicesmentioning

confidence: 99%

A BioMEMS Review: MEMS Technology for Physiologically Integrated Devices

et al. 2004

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“…of sensing, impedance and capture thresholds became progressively available as an automated tool to facilitate outpatients scheduled follow-up and to trigger alarms for better and timely management of malfunctionings. 1,2 Such algorithms provide a complete insight in pacemaker (PM) and defibrillator (ICD) functioning, granting that optimal and stable electrical parameters are maintained after hospital discharge; they may also be integrated into remote monitoring, providing a thorough evaluation of CIEDs even without regular in-office visits. Various studies demonstrated the cost-effectiveness of this approach in daily practice, with a significant impact on clinical outcomes, comprising mortality.…”

Section: Introductionmentioning

confidence: 99%

Left bundle branch area pacing (LBBAP) Auto Threshold algorithms Evaluation for Conduction System Pacing: The LATECS pilot Trial

Ghiglieno

Dell’Era

Veroli

et al. 2023

Pacing Clinical Electrophis

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BackgroundAutomated threshold measurements (ATM) and output adaptation improved safety and follow‐up of cardiac implantable devices (CIED) in the last years. These algorithms were validated for conventional cardiac pacing; however, they were not suitable for permanent His Pacing. Left bundle branch area pacing (LBBAP) is an emerging technique to obtain physiologic cardiac stimulation; we tried to assess if ATM could be applied to this setting.MethodsConsecutive patients receiving ATM‐capable CIED and LBBAP in our hospital were enrolled in this prospective, observational trial; they were evaluated 3 months after implant, comparing pacing thresholds manually assessed and obtained via ATM. Subsequent remote follow‐up was carried on when available.ResultsForty‐five patients were enrolled. ATM for LBBAP lead provided consistent results in all the patients and was therefore activated; mean value of manually obtained LBBAP capture threshold was 0.66 ± 0.19 V versus ATM of 0.64 ± 0.19 V. TOST analysis showed equivalence of the two measures (p = .66). At subsequent follow‐up (mean follow up 7.7 ± 3.2 months), ATM was effective in assessing pacing thresholds and no clinical adverse event was observed.ConclusionsATM algorithms proved equivalent to manual testing in determining capture threshold and were reliably employed in patients receiving LBBAP CIED.

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“…If the signal-to-noise ratio is less than 2, the algorithm classifies the event as noise or a tachyarrhythmia based on previous events. 16 Average noise estimates for each maneuver did not significantly differ when performed with a polyurethane or silicone atrial lead with active or passive fixation. A limited number of silicon leads (3) and leads with active fixation (2) were tested, so further data may be needed for support.…”

Section: Discussionmentioning

confidence: 86%

“…One automatic sensitivity adaptation algorithm based on intracardiac atrial electrograms uses two separate sensing thresholds for detecting noise and for cardiac sensing. If the signal‐to‐noise ratio is less than 2, the algorithm classifies the event as noise or a tachyarrhythmia based on previous events 16 …”

Section: Discussionmentioning

confidence: 99%