Sensing and Detection With Cardiac Implantable Electronic Devices

Swerdlow, Charles D.; Brown, Mark L.; Bordachar, Pierre

doi:10.1016/b978-0-323-37804-8.00004-3

Cited by 10 publications

(11 citation statements)

References 212 publications

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“…However, we do not know the reproducibility of intermittent FF undersensing. Further, since the amplitude of the FF EGM may vary significantly with changes in posture, supine testing may not detect all patients at risk for FF undersensing . Additionally, it is unlikely that implant testing will detect the other unique failure modes we report.…”

Section: Discussionmentioning

confidence: 92%

“…Thus, to the extent that frequency content can be approximated by the ratio of amplitude to duration, NF EGMs should have higher frequency content than FF EGMs. This difference is accentuated during VT or VF during which slowed myocardial activation prolongs the FF EGM duration relative to its duration in sinus rhythm, while little change occurs in the duration of the NF EGM . Based on these considerations, it is likely that the optimal bandpass filter setting differs for FF compared to NF sensing.…”

Section: Discussionmentioning

confidence: 99%

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Mechanisms of Undersensing by a Noise Detection Algorithm That Utilizes Far‐Field Electrograms With Near‐Field Bandpass Filtering

Koneru

Swerdlow²,

Ploux³

et al. 2017

Cardiovasc electrophysiol

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Mechanisms of Undersensing by a Noise Detection Algorithm That Utilizes Far‐Field Electrograms With Near‐Field Bandpass Filtering

Koneru

Swerdlow²,

Ploux³

et al. 2017

Cardiovasc electrophysiol

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“…In this case, none of the beats are faster than the detection interval of 320 ms so the counter will not increment and the episode is not detected. A detailed description of the AF SVT algorithm has previously been reported…”

Section: Methodsmentioning

confidence: 99%

SVT discrimination algorithms significantly reduce the rate of inappropriate therapy in the setting of modern‐day delayed high‐rate detection programming

Cheng

Auricchio

Schloss

et al. 2019

Cardiovasc electrophysiol

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Background Contemporary implantable cardioverter‐defibrillator (ICD) programming involving delayed high‐rate detection and use of supraventricular tachycardia (SVT) discriminators has significantly reduced the rate of inappropriate shocks. The extent to which SVT algorithms alone reduce inappropriate therapies is poorly understood. Methods and Results PainFree SST enrolled 2770 patients with a single‐ or dual‐chamber ICD or cardiac resynchronization defibrillator. Patients were followed for 22 ± 9 months with SVT discriminators on in 96% of patients. Sustained ventricular tachyarrhythmias and SVT episodes were adjudicated by an independent physician committee. For this analysis, all episodes were subjected to postprocessing computer simulation with SVT discriminators off with and without delayed high‐rate detection criteria (ventricular fibrillation zone only, 30/40 at 320 ms). There were 3282 adjudicated SVT episodes of which 115 resulted in an ICD shock and 113 received only ATP (2‐year inappropriate shock and therapy rates of 3.1% and 4.1%). Therapy was appropriately withheld for the remaining 3054 SVT episodes. With both SVT discriminators and delayed high‐rate detection simulated off, the 2‐year inappropriate therapy rate would have been 22.9% (hazard ratio [HR] = 6.24; 95% confidence interval [CI]: 5.20‐7.49). With SVT discriminators simulated off and delayed high‐rate detection simulated on in all patients, the 2‐year rate would have been 6.4% (HR = 1.63; CI: 1.44‐1.85). Conclusions The use of SVT discriminators has a significant role in reducing the rate of inappropriate ICD therapy even in the setting of delayed high‐rate detection settings. Deactivating SVT discriminators would have resulted in an overall increase in the inappropriate ICD therapy rate by 63% and 524% with and without delayed high‐rate detection programming, respectively.

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“…The device senses these unexpected signals, referred to as oversensing, which can cause inappropriate pacing inhibition, pacemaker tracking or mode switching [11], [12]. For instance, an unintended mode switch is reported because of prolonged atrial activation [13].…”

Section: Introductionmentioning

confidence: 99%

An intracardiac electrogram model to bridge virtual hearts and implantable cardiac devices

Patel

Roop

et al. 2017

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Abstract-Virtual heart models have been proposed to enhance the safety of implantable cardiac devices through closed loop validation. To communicate with a virtual heart, devices have been driven by cardiac signals at specific sites. As a result, only the action potentials of these sites are sensed. However, the real device implanted in the heart will sense a complex combination of near and far-field extracellular potential signals. Therefore many device functions, such as blanking periods and refractory periods, are designed to handle these unexpected signals. To represent these signals, we develop an intracardiac electrogram (IEGM) model as an interface between the virtual heart and the device. The model can capture not only the local excitation but also far-field signals and pacing afterpotentials. Moreover, the sensing controller can specify unipolar or bipolar electrogram (EGM) sensing configurations and introduce various oversensing and undersensing modes. The simulation results show that the model is able to reproduce clinically observed sensing problems, which significantly extends the capabilities of the virtual heart model in the context of device validation.

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Sensing and Detection With Cardiac Implantable Electronic Devices

Cited by 10 publications

References 212 publications

Mechanisms of Undersensing by a Noise Detection Algorithm That Utilizes Far‐Field Electrograms With Near‐Field Bandpass Filtering

Mechanisms of Undersensing by a Noise Detection Algorithm That Utilizes Far‐Field Electrograms With Near‐Field Bandpass Filtering

SVT discrimination algorithms significantly reduce the rate of inappropriate therapy in the setting of modern‐day delayed high‐rate detection programming

An intracardiac electrogram model to bridge virtual hearts and implantable cardiac devices

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