Multi-Institutional Study of Implantable Defibrillator Lead Performance in Children and Young Adults
Bibliographic record
Abstract
BACKGROUND: Implantable cardioverter-defibrillator (ICD) therapy in children and congenital heart disease patients is hampered by poor long-term lead survival. Lead extraction is technically difficult and carries substantial morbidity. We sought to determine the outcomes of ICD leads in pediatric and congenital heart disease patients. METHODS AND RESULTS: The Pediatric Lead Extractability and Survival Evaluation (PLEASE) is a 24-center international registry. Pediatric and congenital heart disease patients with ICD lead implantations from 2005 to 2010 were eligible. Study subjects comprised 878 ICD patients (44% congenital heart disease). Mean±SD age at implantation was 18.6±9.8 years. Of the 965 total leads, 54% were thin (≤7F), of which 57% were Fidelis, and 23% were coated with expanded polytetrafluoroethylene. There were 139 ICD lead failures (14%) in 132 patients (15%) at a mean lead age of 2.0±1.4 years, causing shocks in 53 patients (40%). Independent predictors of lead failure included younger implantation age and Fidelis leads. Actuarial analysis showed an incremental risk of lead failure with younger age at implantation: <8 years compared with >18 years (P=0.015). The actuarial yearly failure rate was 2.3% for non-Fidelis and 9.1% for Fidelis leads. Extraction was performed on 143 leads (80% thin, 7% expanded polytetrafluoroethylene coated), with lead age as the only independent predictor for advanced extraction techniques. There were 6 major extraction complications (4%) but no procedural mortality. CONCLUSIONS: This study demonstrates that ICD leads in children and congenital heart disease patients have an age-related suboptimal performance, further compounded by a high failure rate of Fidelis leads. Advanced extraction techniques were common and correlated with older lead age. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00335036.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".