Inappropriate Shocks in Patients With Fidelis® Lead Fractures: Impact of Remote Monitoring and the Lead Integrity Algorithm

Blanck, Zalmen; Axtell, Kathi; Brodhagen, Kathy; O'hearn, Laura; Albelo, Tammy; Ceretto, Cheryl; Dhala, Anwer; Sra, Jasbír; Akhtar, Masood

doi:10.1111/j.1540-8167.2011.02077.x

Cited by 35 publications

(35 citation statements)

References 30 publications

(118 reference statements)

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“…Caregivers must respond rapidly to alerts to minimize inappropriate shocks [144,149]. Wireless remote monitoring has been reported to reduce response time [150]. The principal disadvantage of lead alerts is falsepositive triggers.…”

Section: Lead-related Oversensingmentioning

confidence: 99%

2015 HRS/EHRA/APHRS/SOLAECE expert consensus statement on optimal implantable cardioverter-defibrillator programming and testing

et al. 2016

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Section: Lead-related Oversensingmentioning

confidence: 99%

2015 HRS/EHRA/APHRS/SOLAECE expert consensus statement on optimal implantable cardioverter-defibrillator programming and testing

et al. 2016

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“…In patients with LIA and wireless CareLink, only 2 of 14 patients (14%) received IS; among patients with LIA and no wireless CareLink, 26% received IS. 27 Our study has a number of limitations. We had no data on the site of lead failure in our individual cases.…”

Section: Birnie Et Al Predictors Of Fidelis Lead Failurementioning

confidence: 99%

“…These data point in a similar direction, although with less magnitude, as 2 previous single-center experiences. 26,27 Inappropriate shocks were a first sign of lead failure in 69% 26 and 52% 27 of patients preceding LIA and in only 17% 26 and 21% 27 of patients after LIA was uploaded. Both studies also reported that, in patients presenting with IS, the mean number of shocks was reduced; however, we did not observe this in our study.…”

Section: Birnie Et Al Predictors Of Fidelis Lead Failurementioning

confidence: 99%

Clinical Predictors of Fidelis Lead Failure

Birnie

Parkash²,

Exner³

et al. 2012

Circulation

104

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Background-Approximately 268 000 Fidelis leads were implanted worldwide until distribution was suspended because of a high rate of early failure. Careful analyses of predictors of increased lead failure hazard are required to help direct future lead design and also to inform decision making on lead replacement. We sought to perform a comprehensive analysis of all potential predictors in a multicenter study. Methods and Results-A total of 3169 Sprint Fidelis leads were implanted in 11 centers with a total of 251 failures. Lead failure rates at 3, 4, and 5 years were 5.3%, 10.6%, and 16.8%, respectively. The rate of lead failure continues to accelerate (PϽ0.001). There were 4 independent predictors of failure: center, sex, access vein, and previous lead failure. Women had a higher hazard of failure (hazard ratio 1.51; 95% confidence interval, 1.14 -2.04; Pϭ0.005). Both axillary and subclavian access increased the hazard of failure (Pϭ0.007); hazard ratio for axillary was 1.94, (95% confidence interval, 1.23-3.04) and for subclavian 1.63 (95% confidence interval, 1.08 -2.46). Previous lead failure increased the hazard of a subsequent Fidelis failure with a hazard ratio of 3.12 (95% confidence interval, 1.80 -5.41; PϽ0.001). Conclusions-The rate of Fidelis failure continues to increase over time, with failures approaching 17% at 5 years.Women, patients with leads inserted via the subclavian or axillary vein, and those with a previous lead fracture were at greatest risk of Fidelis failure. Our data suggest that Fidelis replacement should be strongly considered at the time of generator replacement. (Circulation. 2012;125:1217-1225.)

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“…Despite concerns that the use of remote monitoring might drain the battery (leading to the need for more frequent generator change procedures), it appears that the energy efficiency that can be gained via relevant programming changes minimizes any excess battery use that might occur. 197,199 Furthermore, remote monitoring can detect problems before they occur, preventing important outcomes such as inappropriate and appropriate implantable cardioverter-defibrillator discharges, 197,200 which can substantially adversely affect quality of life and lead to significant healthcare use.…”

Section: Patient-reported Informationmentioning

confidence: 99%

The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association

Maddox¹,

Albert²,

Borden³

et al. 2017

Circulation

118

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ABSTRACT:The learning healthcare system uses health information technology and the health data infrastructure to apply scientific evidence at the point of clinical care while simultaneously collecting insights from that care to promote innovation in optimal healthcare delivery and to fuel new scientific discovery. To achieve these goals, the learning healthcare system requires systematic redesign of the current healthcare system, focusing on 4 major domains: science and informatics, patient-clinician partnerships, incentives, and development of a continuous learning culture. This scientific statement provides an overview of how these learning healthcare system domains can be realized in cardiovascular disease care. Current cardiovascular disease care innovations in informatics, data uses, patient engagement, continuous learning culture, and incentives are profiled. In addition, recommendations for next steps for the development of a learning healthcare system in cardiovascular care are presented.H ealth care has never been more complex. Clinicians and patients must make decisions that integrate the continually evolving scientific evidence base with hundreds of individual data points such as patients' vital signs, symptoms, comorbidities, medications, test results, and preferences. Furthermore, once these decisions are made, little information is available about their impact, limiting the ability to learn from and ultimately improve care delivery. This inability of the healthcare system to learn from its operation results in significant inefficiencies, substantial costs, and suboptimal health outcomes.The creation of a learning healthcare system (LHS) can potentially address these issues. The LHS uses health information technology and the health data infrastructure to apply scientific evidence at the point of clinical care while simultaneously collecting insights from that care to promote innovation in optimal healthcare delivery and to fuel new scientific discovery 1,2 (Figure 1). Thus, the LHS enables rapid, iterative learning in which "evidence informs practice, and practice informs evidence." 2 The authors argued that recent advances in information processing and connectivity, healthcare organizational design, and reimbursement policies centered on quality rather than quantity of care provided the necessary tools for the creation of the LHS. Accordingly, they called for systematic redesign of the healthcare system, focusing on 4 major domains: science and informatics, patient-clinician partnerships, incentives, and development of a continuous learning culture.

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Inappropriate Shocks in Patients With Fidelis® Lead Fractures: Impact of Remote Monitoring and the Lead Integrity Algorithm

Cited by 35 publications

References 30 publications

2015 HRS/EHRA/APHRS/SOLAECE expert consensus statement on optimal implantable cardioverter-defibrillator programming and testing

2015 HRS/EHRA/APHRS/SOLAECE expert consensus statement on optimal implantable cardioverter-defibrillator programming and testing

Clinical Predictors of Fidelis Lead Failure

The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association

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