Design of a post-market registry for the extravascular implantable cardioverter-defibrillator: The Enlighten Study
Bibliographic record
Abstract
Background: The extravascular implantable cardioverter-defibrillator (EV-ICD) with substernal lead placement has been shown to terminate ventricular arrhythmias safely and effectively while being outside the vasculature. The performance of the EV-ICD system with a novel inappropriate shock-reducing algorithm in a real-world setting has yet to be investigated. Objective: The objective of the Enlighten Study: the EV-ICD Post-Approval Registry is to provide a comprehensive measure of the safety and performance of the EV-ICD system in real-world clinical practice over the lifetime of the device. Methods: The Enlighten Study is a global, prospective, observational, multicenter, post-approval study utilizing the manufacturer's Product Surveillance Registry. Eligible patients implanted with an Aurora EV-ICD system at participating centers will be included. Follow-up clinical data will be collected approximately every 6 months throughout the lifetime of the device, enrolling a minimum of 500 patients. Results: The primary endpoint of the study is major system-related complication-free survival at 5 years post-implantation, with a minimum threshold of >79%. The study will also characterize device performance that includes, but is not limited to, freedom from system- or procedure-related complications, performance of antitachycardia pacing, characterization of sensing and detection, inappropriate therapy, shock effectiveness, battery depletion, and system revisions. Conclusion: The Enlighten Study: the EV-ICD Post-Approval Registry will examine the real-world performance of the post-market EV-ICD system. Additionally, this study will allow for a robust assessment of EV-ICD-related complications, device revisions, and extractions over chronic (>5 years) implant durations. ClinicalTrialsgov ID: NCT06048731.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".