PRevention of sudden cardiac death aFter myocardial infarction by defibrillator implantation: Design and rationale of the PROFID EHRA randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Randomized clinical trials from over 20 years ago demonstrated that an implantable cardioverter defibrillator (ICD) improved survival for patients with severely reduced left ventricular ejection fraction (LVEF) after myocardial infarction (MI) compared with optimal medical therapy (OMT) alone. Since then advances in therapy have led to the reduction in the incidence of sudden cardiac death (SCD) in this population, whilst complication rates from ICD implantation are still substantial. OBJECTIVES: To determine whether OMT without ICD implantation is not inferior to OMT with ICD implantation with respect to all-cause mortality. DESIGN: The PROFID EHRA trial is an investigator-driven, prospective, parallel-group, randomized, open-label, blinded outcome assessment (PROBE), multi-center, noninferiority trial without dedicated investigational medical device (Proof of Strategy Trial) with 2 groups with 1:1 randomization. PROFID-EHRA will recruit approximately 3,595 patients with documented history of MI at least 3 months prior, LVEF ≤35%, on OMT for at least 3 months, and with New York Heart Association class II or III, who will be randomized to OMT or OMT plus ICD, to collect 374 first primary outcome events within a median observation period of around 28 months from about 180 clinical sites in an estimated 13 countries. The primary outcome is time from randomization to the occurrence of all-cause death. Secondary outcomes include time from randomization to death from cardiovascular causes, to SCD, to first hospital readmission for cardiovascular causes after date of randomization, the average length of hospital stay during follow-up, and quality of life trajectories. CLINICAL TRIAL: Trials.gov NCT05665608.
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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 | 0.067 | 0.058 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".