Long-term complications, reoperations and survival following cardioverter-defibrillator implant
Bibliographic record
Abstract
OBJECTIVE: Implantable cardioverter-defibrillators (ICDs) reduce risk of death in select populations, but are also associated with harms. We aimed to characterise long-term complications and reoperation rate. METHODS: We assessed the rate, cumulative incidence and predictors of long-term reoperation and survival using a prospective, multicentre registry serving British Columbia in Canada, a universal single payer healthcare system with 4.5 million residents. 3410 patients (mean 63.3 years, 81.7% male) with new primary (n=1854) or secondary prevention (n=1556) ICD implant from 2003 to 2012 were followed for a median of 34 months (single chamber n=1069, dual chamber n=1905, biventricular n=436). Independent predictors of adverse outcomes were defined using Cox regression models. RESULTS: The overall reoperation rate was 12.0% per patient-year, and less for single vs dual vs biventricular ICDs (9.1% vs 12.5% vs 17.8% per patient-year, respectively). The Kaplan-Meier complication estimates (excluding generator end of life) at 1, 3 and 5 years were respectively: single chamber 10.2%, 16.2% and 21.6%; dual 11.7%, 19.1% and 27.4% and biventricular 15.9%, 22.2% and 24.7%. Cardiac resynchronisation therapy had the highest rate of early lead complications, but lower long-term need for upgrade. Device complexity, age and atrial fibrillation were key determinants of complications. Overall mortality at 1, 3 and 5 years was 5.4%, 17.4% and 32.7%, respectively. In younger patients, observed 5-year survival approached the expected survival in the general population (relative survival ratio=0.96 (0.90-0.98)). With increasing age, observed survival steadily declined relative to expected. CONCLUSIONS: In a prospective registry capturing all procedures, complication and reoperation rates following de novo ICD implantation were high. Shared decision making must carefully consider these factors.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".