Right ventricular apical pacing: a necessary evil?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Clinical trial evidence suggests that traditional right ventricular apical pacing may be harmful. This review summarizes the existing evidence and outlines the major avenues of ongoing research in this field. RECENT FINDINGS: Despite theoretical advantages of dual-chamber pacing, large randomized trials found only a small advantage over single-chamber ventricular pacing. Subsequent analysis of one of these trials suggested that this was due to the tendency for dual-chamber pacemakers to produce frequent, unnecessary right ventricular pacing. This hypothesis is supported by a prospective study among defibrillator recipients, showing that dual-chamber pacing results in a very high frequency of ventricular pacing and worse clinical outcomes, compared with backup ventricular pacing. These observations have led to a renewed interest in single-chamber atrial pacing for sinus node dysfunction, the development of new dual-chamber pacemaker algorithms designed to minimize right ventricular pacing, and the search for better ways to pace the ventricles in patients who require ventricular pacing. SUMMARY: Conventional right ventricular apical pacing should be avoided whenever possible. In patients who require ventricular pacing, ongoing research will determine if selected-site pacing or multisite pacing improves clinical outcomes compared with traditional right ventricular apical pacing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".