Biomedical subjects

Bruce D Gunderson

Publications and source records attributed to Bruce D Gunderson.

5 recordsLinked to original sources

PubMed2006

Development and testing of an algorithm to detect implantable cardioverter-defibrillator lead failure.

BACKGROUND: Implantable cardioverter-defibrillator (ICD) lead failures often present as inappropriate shock therapy. An algorithm that can reliably discriminate between ventricular tachyarrhythmias and noise due to lead failure may prevent patient discomfort and anxiety and avoid device-induced proarrhythmia by preventing inappropriate ICD shocks. OBJECTIVES: The goal of this analysis was to test an ICD tachycardia detection algorithm that differentiates noise due to lead failure from ventricular tachyarrhythmias. METHODS: We tested an algorithm that uses a measure of the ventricular intracardiac electrogram baseline to discriminate the sinus rhythm isoelectric line from the right ventricular coil-can (i.e., far-field) electrogram during oversensing of noise caused by a lead failure. The baseline measure was defined as the product of the sum (mV) and standard deviation (mV) of the voltage samples for a 188-ms window centered on each sensed electrogram. If the minimum baseline measure of the last 12 beats was <0.35 mV-mV, then the detected rhythm was considered noise due to a lead failure. The first ICD-detected episode of lead failure and inappropriate detection from 24 ICD patients with a pace/sense lead failure and all ventricular arrhythmias from 56 ICD patients without a lead failure were selected. The stored data were analyzed to determine the sensitivity and specificity of the algorithm to detect lead failures. RESULTS: The minimum baseline measure for the 24 lead failure episodes (0.28 +/- 0.34 mV-mV) was smaller than the 135 ventricular tachycardia (40.8 +/- 43.0 mV-mV, P <.0001) and 55 ventricular fibrillation episodes (19.1 +/- 22.8 mV-mV, P <.05). A minimum baseline <0.35 mV-mV threshold had a sensitivity of 83% (20/24) with a 100% (190/190) specificity. CONCLUSION: A baseline measure of the far-field electrogram had a high sensitivity and specificity to detect lead failure noise compared with ventricular tachycardia or fibrillation.

Aged↗

PubMed2005

Automatic identification of clinical lead dysfunctions.

Implantable cardioverter defibrillators (ICD) lead dysfunctions can cause inappropriate shocks. Current ICDs store lead diagnostics and detected episodes. This stored information with intracardiac electrograms (EGM) and sensed RR interval patterns may characterize the ICD lead performance. The aim of this analysis was to determine the sensitivity and positive predictive value (PPV) of an automatic lead dysfunction identification algorithm. This algorithm uses RR and EGM data to distinguish noncardiac oversensing (OS), for example, due to conductor fracture, and cardiac OS, for example, T-wave OS, from detected episodes. The algorithm also uses lead diagnostics: sensing integrity counter trends (e.g., RR intervals <140 ms), nonsustained tachyarrhythmias episodes with a mean RR <200 ms and impedance trends to identify lead fractures. The PPV was determined using the stored memory from 1,756 ICD patients enrolled in a 13-center long-term lead study with an average follow-up of 18.3 patient-months. Sensitivity was determined in 35 patients who presented with OS or lead fracture-related adverse events confirmed by stored ICD diagnostics. The algorithm sensitivity was 97.1% (34/35). There were 43 additional patients identified by the algorithm without an adverse event. Stored ICD diagnostics confirmed lead dysfunctions in 32 of 43 patients corresponding with an 85.7% PPV (66/77). ICD memory diagnostics and episodes with intracardiac EGM may be used to identify ICD lead dysfunctions with high sensitivity and PPV. This algorithm may be implemented in postprocessing ICD environments (e.g., remote server, programmer) to rapidly identify lead dysfunction prior its clinical manifestation.

Algorithms↗

PubMed2004

An algorithm to predict implantable cardioverter-defibrillator lead failure.

OBJECTIVES: The goal of this analysis was to test an algorithm that identifies implantable cardioverter-defibrillator (ICD) lead problems before clinical failure and/or inappropriate therapy. BACKGROUND: The ICD lead failures typically present as inappropriate shock therapy. Identifying lead failures before their clinical presentation may prevent patient discomfort, improve device longevity, and avoid device-induced proarrhythmia. METHODS: We tested an algorithm that uses two measures of oversensing and one measure of abnormal impedance to detect a lead failure. The oversensing measures consisted of a counter for RR intervals <140 ms and nonsustained ventricular tachycardia episodes with mean RR interval <200 ms. The impedance measure tracked lead impedances every day and each week. Abnormal impedance was defined as a decrease in impedances or an outlier value compared with baseline. Lead failures were identified when both oversensing measures were met or abnormal impedance and one oversensing measure occurred. The stored data from 696 patients with an ICD were analyzed to determine the sensitivity and specificity of the algorithm to detect lead failures. RESULTS: Twenty-nine patients demonstrated clinical lead failures with an average of 6 +/- 9 inappropriate shocks per patient. The two oversensing measures used in the algorithm predicted 72% (21 of 29) of the lead failures. Fulfilling at least two of the three impedance and oversensing measures, the sensitivity of our algorithm was 83% (24 of 29) with a 100% (667 of 667) specificity. CONCLUSION: Oversensing combined with abnormal impedance trends may be used to identify ICD lead failures with high sensitivity and very high specificity.

Algorithms↗

PubMed2004

Incidence of nonsustained and sustained ventricular tachyarrhythmias in patients with an implantable cardioverter defibrillator.

INTRODUCTION: Nonsustained ventricular tachycardia (NSVT) is a frequent phenomenon in some patients with heart disease, but its association with sustained ventricular tachycardias (ventricular tachycardia [VT]/ventricular fibrillation [VF]) is still not clear. The aim of this study was to determine whether NSVT incidence was associated with sustained VT/VF in patients with an implantable cardioverter defibrillator (ICD). METHODS AND RESULTS: Retrospective data analysis was conducted in 923 ICD patients with a mean follow-up of 4 months. NSVT and sustained VT/VF were defined as device-detected tachycardias. The incidence rates of NSVT and sustained VT/VF as well as ICD therapies were determined as episodes per patient. The NSVT index was defined as the product of NSVT episodes/day times the mean number of beats per episode, i.e., total beats/day. The NSVT index peak was defined as the highest value on or prior to the day with sustained VT/VF episodes. Patients (n = 393) with NSVT experienced a higher incidence of sustained VT/VF (17.2 +/- 63.0 episodes/patient) and ICD therapies (15.2 +/- 61.4 episodes/patient) than patients (n = 530) without NSVT (sustained VT/VF: 0.5 +/- 6.6 and therapies: 0.5 +/- 5.6; P < 0.0001). Approximately 74% of NSVT index peaks occurred on the same day or <3 days prior to sustained VT/VF episodes. The index was higher for peaks < or =3 days prior to the day with sustained VT/VF (94.3 +/- 140.1 total beats/day) than for peaks >3 days prior to the day with sustained VT/VF (32.7 +/- 55.9 total beats/day; P < 0.0001). CONCLUSION: ICD patients with NSVT represent a population more likely to experience sustained VT/VF episodes with a temporal association between an NSVT surge and sustained VT/VF occurrence.

Female↗

PubMed2003

An adaptive interval-based algorithm for withholding ICD therapy during sinus tachycardia.

Avoiding inappropriate ICD therapy during supraventricular tachycardia (SVT) while assuring 100% sensitivity for VT/VF remains a challenge. Inappropriate VT/VF therapy during sinus tachycardia (ST) is particularly distressing to the patient because the full sequence of ICD therapies is often delivered. ST or 1:1 atrial tachycardia (AT) with long PR intervals and ST or AT with atrial oversensing of far-field R waves cause the majority of inappropriate therapy in the Medtronic GEM DR (Model 7271) ICD. The goals of the present effort were to define an adaptive interval-based algorithm for withholding VT/VF therapy in dual chamber ICDs during ST and to compare performance of the adaptive algorithm with that of the original ST withholding algorithm in the GEM DR. The adaptive algorithm uses a combination of 1:1 atrial to ventricular conduction pattern, changes in RR intervals and changes in intrinsic PR intervals to establish evidence for or against the presence of ST. Performances of the adaptive and original ST withholding algorithms were compared on 3 databases collected by implanted GEM DR devices. The first database included 684 spontaneous VT/VF episodes. The second database included 216 spontaneous SVT episodes that received inappropriate VT/VF therapy. These databases included up to 2,000 atrial or ventricular sensed or paced events preceding the spontaneous tachycardias. The third database included 320 spontaneous ST/AT episodes for which therapy was appropriately withheld by the GEM DR. Performance of the adaptive algorithm on the third database was predicted rather than directly computed because of record length limitations. VT/VF therapy was classified as "withheld" if evidence of ST remained high for one algorithm (i.e., at least 7 more beats to VT/VF detection) at the point of VT/VF detection by the other algorithm. For the 684 true VT/VF episodes, the original algorithm withheld VT/VF therapy in 5 episodes and the adaptive algorithm withheld VT/VF therapy in 3 episodes. The 95% confidence interval for the difference in VT/VF sensitivity between the adaptive and original algorithms was [-0.5 to + 1.1%]. Twelve of the 320 ST/AT episodes (3.8%) that were appropriately classified by the original algorithm were predicted to receive inappropriate therapy by the adaptive algorithm. However, relative to the original algorithm, the adaptive algorithm appropriately withheld VT/VF therapy for 76 of 216 true SVT episodes (i.e., incremental specificity of 35.2%). For the specific SVT episodes that were the targets for improvement by the adaptive ST algorithm (ST/AT with long PR intervals and ST/AT with intermittent atrial oversensing of far-field R waves), the adaptive algorithm reduced inappropriate therapy by 63.2%.

Algorithms↗