Worldwide Clinical Experience with a New Dual‐Chamber Implantable Cardioverter Defibrillator System
Bibliographic record
Abstract
INTRODUCTION: Management of atrial tachyarrhythmias represents a significant challenge in patients with implantable cardioverter defibrillators (ICDs). Drug therapy of these arrhythmias is limited by moderate efficacy, ventricular proarrhythmia, and drug-device interactions. This study tested the safety and efficacy of a new dual-chamber ICD to detect and treat atrial as well as ventricular tachyarrhythmias. METHODS AND RESULTS: A dual-chamber ICD (Medtronic 7250 Jewel AF) was implanted in 293 of 303 patients at 49 centers in Europe, Canada, and North America. Specific data were collected at implant and during a mean follow-up period of 7.9+/-4.7 months. There were no clinically evident failures to detect and treat ventricular arrhythmias. In patients with at least one of the dual-chamber detection criteria activated, 1,056 of 1,192 episodes of ventricular tachycardia or fibrillation detected were judged to be appropriate (89% positive predictive accuracy). Therapy efficacy was 100% in the ventricular fibrillation zone and 98% in the ventricular tachycardia zone. Positive predictive accuracy for detection of atrial episodes was 95% (1,052/1,107). For episodes classified as atrial tachycardia by the device, the efficacy of atrial antitachycardia pacing and high-frequency (50-Hz) burst pacing was 55% and 17%, respectively. High-frequency burst pacing terminated 16.8% of episodes classified as atrial fibrillation, and atrial defibrillation had an estimated efficacy of 76%. The actuarial estimates of 6-month complication-free survival and total survival were 88% and 94%, respectively. CONCLUSION: This novel dual-chamber ICD is capable of safely and effectively discriminating atrial from ventricular tachyarrhythmias and of treating atrial tachyarrhythmias without compromising detection and treatment of ventricular tachyarrhythmias.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".