Implantable Cardioverter Defibrillator Therapy for Primary Prevention of Sudden Cardiac Death after Myocardial Infarction:
Bibliographic record
Abstract
STUDY OBJECTIVE: To estimate the proportion of patients eligible for implantable cardioverter defibrillator (ICD) therapy for the primary prevention of sudden cardiac death after a myocardial infarction (MI), according to the current guidelines. METHODS: Eligibility was assessed retrospectively at 6 weeks in 513 post-MI survivors (age 66 +/- 13 years, left ventricular ejection fraction 48.2 +/- 17%) on the basis of an electrocardiogram and an echocardiogram. RESULTS: LVEF was < or = 40% in 37% and < or = 35% in 30%, and QRS duration was <120 ms in 89% and > or =120 ms in 11% of patients. The proportion of post-MI patients meeting the criteria set by guidelines were 37% for 2006 American College of Cardiology/American Heart Association/European Society of Cardiology (ACC/AHA/ESC) 26.5% for 2008 ACC/AHA/Canadian Heart Rhythm Society 16.3% for 2005 US Centers for Medicare and Medicaid Services (CMS), and 5.8% for the 2006 United Kingdom (UK) National Institute of Clinical Excellence (NICE). According to 2005 CMS and 2006 UK-NICE guidelines, Holter monitoring was required in 7% and 18%, respectively. For the United States (700,000 MI in 2006), the 2006 ACC/AHA/ESC guidelines equate to 216,783 ICD implantations/year. For UK (60,499 MI in 2006), the 2006 NICE guidelines equate to 2,941 ICD implantations, 10,488 Holter studies, and 1,065 VT induction tests/year. CONCLUSIONS: Current ICD therapy guidelines for primary prevention of SCD post-MI demand a substantial increase in service provision worldwide.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".