The impact of implantable cardiac defibrillators for primary prophylaxis in the community: baseline risk and clinically meaningful benefits
Bibliographic record
Abstract
OBJECTIVE: To estimate the baseline risk of arrhythmic death required for prophylactic implantable cardiac defibrillators (ICDs) to result in clinically meaningful survival benefits in the population. BACKGROUND: While proven efficacious, the absolute survival impact of ICDs for the primary prevention of sudden cardiac death among patients with left ventricular (LV) dysfunction is highly dependent upon patient's baseline risk of arrhythmic death. METHODS: Using echocardiographic data from a random sample of patients identified from community echocardiographic laboratories, patients with moderate or severe LV dysfunction (ejection fraction < 35%) were linked to administrative databases to characterize baseline mortality risk (median follow-up duration of 4.85 years). Relative efficacy was ascertained from meta-analysis and clinical trial data. The baseline annual risk of arrhythmic death required for prophylactic ICDs to result in clinically meaningful survival benefits in the population was estimated at different ranges of relative efficacy and numbers needed to treat (NNTs) thresholds. RESULTS: LV dysfunction was a significant independent predictor of adverse outcomes. In total, 35.4% of the patients with moderate to severe LV dysfunction died during the follow-up period. Assuming a base-case relative efficacy of 66%, we estimated that the baseline risk for arrhythmic death required to exert a clinically meaningful NNT threshold of 50 in order to prevent one death (from any cause) was 3% per year or higher. CONCLUSIONS: The survival impact and cost-effectiveness of prophylactic ICDs in the population will depend upon the ability to risk-stratify and identify patients whose baseline risk for sudden cardiac death exceed 3% per year.
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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 | 0.029 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".