Prospective long-term follow-up of silicone-polyurethane–insulated implantable cardioverter-defibrillator leads
Bibliographic record
Abstract
BACKGROUND: St Jude Medical (now Abbott) Optim-insulated implantable cardioverter-defibrillator (ICD) leads were expected to overcome problems with insulation abrasion and externalized conductors in earlier models. Long-term follow-up is essential to the evaluation of lead performance. OBJECTIVE: To determine, in a prospective cohort of Optim-insulated ICD leads, the rates of all-cause mechanical failure and its subtypes (conductor fracture, insulation abrasion, externalized conductors, and other mechanical failures) and electrical dysfunction adjudicated as nonmechanical failure. METHODS: Abbott established 3 prospective registries, enrolling 11,155 leads among 10,872 patients beginning in 2006. There was standardized baseline documentation, 6-monthly follow-up, adverse events reporting, and documentation of lead revision or inactivation, study withdrawal, and death or transplant. The Population Health Institute (McMaster University) reviewed database functions, adjudicated all potential mechanical lead failures, and conducted independent data analyses. RESULTS: During a median follow-up of 4.6 years, there were 171 mechanical failures (1.53%, 95.4% freedom from failure by 12 years). There were no significant differences in survival among Durata DF4 and DF1 and Riata ST Optim leads. The year-to-year rate of failure of leads increased over time. There were 69 electrical dysfunctions (0.62%, 98.8% freedom from failure by 12 years) adjudicated as nonmechanical failure. CONCLUSION: During follow-up as long as 12 years (median 4.6 years), Optim-insulated leads had low rates of mechanical failure and electrical dysfunction. Independent analyses provide reliable data on the long-term outcomes essential to analyzing ICD lead performance.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".