Experience with a Dual Chamber Implantable Defibrillator
Bibliographic record
Abstract
An implantable defibrillator with dual chamber pacing may have advantages for pacing, sensing, and detection of brady- and tachyarrhythmias. This study evaluates the safety and performance of a dual chamber implantable cardioverter defibrillator that incorporates an algorithm to discriminate supraventricular from ventricular arrhythmias. The 300 patients in this study had the device implanted for the following indications: ventricular tachycardia (47%), sudden cardiac death survivorship (51%), and prophylactic implants (2%). Patients received dual chamber pacing for accepted bradyarrhythmic (51.7%) or investigational indications. During a mean follow-up period of 1.7 months a total of 1,092 arrhythmia episodes in 96 patients were fully documented in the device memory: 66 patients experienced a total of 796 ventricular tachyarrhythmia episodes and 42 experienced a total of 296 supraventricular episodes. The device appropriately detected 100% of sustained ventricular tachyarrhythmias while reducing the inappropriate detection of supraventricular tachyarrhythmias by 72% compared to single chamber rate only detection. The positive predictive value was 90.5% for ventricular tachyarrhythmia detection in episodes that exceeded the tachycardia detection rate. Adverse events observed in at least 2% of the patients were incisional pain (22%), inappropriate ventricular detection (7%), atrial lead dislodgement (4%), atrial oversensing/undersensing (3%), hematoma (3%), incessant ventricular tachyarrhythmia (2%), and pneumothorax (2%). There were 13 deaths, none of which were attributed to device failure. The Gem DR is safe and effective for the detection and treatment of ventricular tachyarrhythmias. The dual chamber detection algorithm appropriately recognized supraventricular tachycardia with rapid ventricular rates 72% of the time while maintaining 100% detection of sustained 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".