Maximum potential benefit of implantable defibrillators in preventing sudden death after hospital admission because of heart failure
Bibliographic record
Abstract
BACKGROUND: Implantable defibrillators are recommended for the prevention of sudden cardiac death in patients with heart failure. However, criteria to identify those who would benefit most from this therapy are lacking. We assessed the maximum potential benefit of preventing sudden death in patients with repeated hospital admissions because of heart failure. METHODS: Using a cohort assembled from an administrative database, we identified 14,374 patients admitted to hospital for the first time because of heart failure between Jan. 1, 2000, and Dec. 31, 2004. We followed subsequent admissions related to heart failure as well as mortality and causes of death to Mar. 31, 2006. We regarded all out-of-hospital cardiac deaths as sudden deaths. We calculated the maximum potential benefit of preventing sudden death by subtracting the observed survival after each hospital admission from the hypothetical survival whereby all out-of-hospital cardiac deaths were assumed to be preventable. RESULTS: The mean age of the cohort was 77 years, 45% were women, 11% had cerebrovascular disease, and 21% had chronic kidney disease. Out-of-hospital cardiac deaths constituted 13.7% (1226/8967) of all deaths during 32,055 person-years of follow-up. The median survival declined with each subsequent hospital admission related to heart failure. The hypothetical prevention of all out-of-hospital deaths prolonged life by 0.63 (95% confidence interval [CI] 0.49 to 0.77) years after the first hospital admission. This potential benefit dropped to 0.28 (95% CI 0.10 to 0.46) years after 3 hospital admissions related to heart failure. Among patients less than 65 years old, and older patients without kidney disease, dementia or cancer, more than 50% survived longer than 2 years until they had 2 or 3 hospital admissions related to heart failure. INTERPRETATION: The use of implantable defibrillators to prevent sudden death would provide limited benefit among older patients with comorbidities and among patients with multiple hospital admissions related to heart failure.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".