A trial design for evaluation of empiric programming of implantable cardioverter defibrillators to improve patient management
Bibliographic record
Abstract
The delivery of implantable cardioverter defibrillator (ICD) therapy is sophisticated and requires the programming of over 100 settings. Physicians tailor these settings with the intention of optimizing ICD therapeutic efficacy, but the usefulness of this approach has not been studied and is unknown. Empiric programming of settings such as anti-tachycardia pacing (ATP) has been demonstrated to be effective, but an empiric approach to programming all VT/VF detection and therapy settings has not been studied. A single standardized empiric programming regimen was developed based on key strategies with the intention of restricting shock delivery to circumstances when it is the only effective and appropriate therapy. The EMPIRIC trial is a worldwide, multi-center, prospective, one-to-one randomized comparison of empiric to physician tailored programming for VT/VF detection and therapy in a broad group of about 900 dual chamber ICD patients. The trial will provide a better understanding of how particular programming strategies impact the quantity of shocks delivered and facilitate optimization of complex ICD programming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".