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Record W2981471796 · doi:10.1093/eurheartj/ehz748.1168

P2859Low rates of mechanical failures of silicone-polyurethane copolymer-coated ICD leads: 11 years prospective follow-up

2019· article· en· W2981471796 on OpenAlexaff
John A. Cairns, Ellison Themeles, ALBERT EPSTEIN, Jeff S. Healey, Stuart J. Connolly

Bibliographic record

VenueEuropean Heart Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsMedicineLead (geology)SiliconeMechanical failureSurgeryComposite materialMaterials science

Abstract

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Abstract Background High rates of ICD lead mechanical failures (insulation abrasion and conductor fracture) resulted in FDA recalls and substantial design modifications. Most subsequent reports of lead failures of newer generation leads are based upon modest-sized, retrospective cohorts with relatively brief follow-up and may be unreliable. Following lead modifications (including silicone-polyurethane copolymer insulation coating), in 2007, one manufacturer established 3 prospective registries, and engaged a university-based methods center to independently review the registries, to adjudicate all reports of lead failures and to independently analyze lead survival. Up to 11 years of follow-up is now available. Purpose To adjudicate all reports of leads inactivated because of possible mechanical failure and to independently calculate rates of mechanical failure overall and by specific type. Methods Manufacturer expert staff confirm each lead inactivation by site interrogation. Following formal algorithms which incorporate lead testing and remote monitoring, they designate all-cause mechanical failure (fracture; insulation abrasion; failure at crimp, bond or weld; or uncertain) based upon the finding of electrical noise, very low or very high or rapidly rising impedance or alternatively they designate non-mechanical dysfunction (e.g. no impedance criteria but elevated thresholds, over or under sensing). The results of returned product analyses are incorporated when available (31%). The methods center receives electronic data transfers twice yearly, reviews all documentation, adjudicates all instances of possible lead failure, assigns probable cause (by 2 electrophysiologists) and conducts independent analyses of lead survival. Results 10,866 patients (73% male, mean age 65.9 yr., LVEF 29.3%, NYHA class II or III 89%) with 11,132 leads had follow-up of 4.6 yr. (median) and 11 yr. (maximum) (Aug 31, 2018). Lead follow-up was censored at the time of lead inactivation, death/transplant or administrative withdrawal. Of leads enrolled, there were 26.6% still in follow-up and of those not the status was 7.4% inactivated, 29.5% death or transplant, 33.8% administrative withdrawal and 3.7% reason missing. Following adjudication, there were 156 all-cause mechanical failures (1.40% total, 0.29%/yr.). Rates of cause-specific mechanical failures were: fracture 1.02% total, 0.22%/yr.; insulation abrasion 0.28% total, 0.06%/yr.; miscellaneous/uncertain 0.12% total, 0.02%/yr.; and externalized conductors 0%. Life-table rates of freedom from lead failure by 11 years were: all-cause mechanical failure 95.9%, conductor fracture 97.0%, insulation abrasion 99.1%, mechanical failure other/uncertain type 99.9%, and externalized conductors 100%. Conclusions Up to 11 yr prospective follow-up of silicone-polyurethane-coated ICD leads with independent adjudication and analyses of events shows low rates of all-cause mechanical failure and no externalized conductors. Acknowledgement/Funding Abbott

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.311
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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