Survival After Implantable Cardioverter-Defibrillator Implantation in the Elderly
Bibliographic record
Abstract
BACKGROUND: The benefit of implantable cardioverter-defibrillators (ICDs) among elderly patients is controversial and may be attenuated by nonarrhythmic death. We examined the impact of age on device-delivered therapies and outcomes after primary or secondary prevention ICD. METHODS AND RESULTS: In a prospective, inclusive registry of 5399 ICD recipients in Ontario, Canada (February 2007 to September 2010), device-delivered therapies and complications were determined at routine clinic visits. Among primary prevention ICD recipients aged 18 to 49 (n=317), 50 to 59 (n=769), 60 to 69 (n=1336), 70 to 79 (n=1242), and ≥80 (n=275) years, mortality increased with age, as follows: 2.1, 3.0, 5.4, 6.9, and 10.2 deaths per 100 person-years, respectively (P<0.001). Secondary prevention ICD recipients aged 18 to 49 (n=114), 50 to 59 (n=244), 60 to 69 (n=481), 70 to 79 (n=462), and ≥80 (n=159) years also exhibited increasing mortality, as follows: 2.2, 3.8, 6.1, 8.7, and 15.5 deaths per 100 person-years, respectively (P<0.001). However, rates of appropriate shock were similar across age groups: from 6.7 (18-49 years) to 4.2 (≥80 years) per 100 person-years after primary prevention ICDs (P=0.139) and from 11.4 (18-49 years) to 11.9 (≥80 years) per 100 person-years after secondary prevention ICDs (P=0.993). Covariate-adjusted competing risk analysis demonstrated higher risk of death (Ptrend<0.001 for both primary and secondary prevention) but no significant decline in appropriate shocks with older age after primary (P=0.130) or secondary (P=0.810) prevention ICD implantation. CONCLUSIONS: Whereas elderly patients exhibited increased mortality after ICD implantation, rates of appropriate device shocks were similar across age groups. Decisions regarding ICD candidacy should not be based on age alone but should consider factors that predispose to mortality despite defibrillator implantation.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".