Right ventricular pacing is associated with increased rates of appropriate implantable cardioverter defibrillator shocks
Bibliographic record
Abstract
BACKGROUND: Right ventricular (RV) pacing has been associated with increased risk of pacemaker-induced cardiomyopathy, hospitalization and death among patients with implantable cardioverter defibrillators (ICDs). Little is known about its association with ventricular tachyarrhythmias. We hypothesize that RV pacing is associated with increased incidence of appropriate ICD shocks and death. METHODS: Retrospective study of consecutive patients with de novo ICD insertion (excluding cardiac resynchronization therapy devices) from a single tertiary care center. Patients were classified into <10% RV pacing (low-pace group) and ≥10% RV pacing (high-pace group). Data were compared using two-tailed t tests and Fisher's exact test. Binomial logistic regression was performed to identify predictors of appropriate ICD therapies. RESULTS: A total of 178 patients (54 high paced and 124 low paced) were included. Mean follow-up was 43 ± 11 months. Appropriate shocks occurred in 27 patients (15%) and were significantly higher in the high-pace group (35% vs. 10%, p = 0.008), as the number of deaths (31% vs. 11%, p = 0.001). Binary logistic regression showed a significantly increased risk of shock (OR 2.99, p = 0.01) and death (OR 3.61, p = 0.002) in high-paced patients. Multivariable analysis showed no difference in risk of shocks based on age, sex or ejection fraction. Older patients had higher risk of death. CONCLUSIONS: In this population of ICD patients, those with a high prevalence of RV pacing experienced more shocks for VF/VT and had higher mortality. Further studies should be done to determine whether minimizing RV pacing reduces arrhythmias, shock burden and death in patients with ICDs.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".