Bibliographic record
Abstract
We would like to congratulate Wang et al.1 for conducting a well-designed randomized trial that aimed at examining the superiority of pacing the right ventricular outflow tract (RVOT) over the traditional right ventricular apex (RVA). The authors looked at left ventricular (LV) regional wall motion performance as assessed by echocardiography and found that RVA pacing was associated with more dyssynchrony and LV wall motion abnormalities. However, there was no difference observed between the groups with respect to the LV ejection fraction (LVEF) after 12 months of follow-up (63.4 ± 4.3 vs. 63.2 ± 5.0% in the RVOT and the RVA pacing groups, respectively). Notably, only patients with normal baseline LVEF were included in the study. Therefore, the findings of Wang et al. are not unexpected and are actually in line with our meta-analysis that was recently published in Europace.2 By extracting the data from five randomized studies of patients in whom LVEF at baseline was ≥40–50% we were able to show no differences in the pooled LVEF at the end of-follow-up. Importantly, we demonstrated that non-apical pacing had significant beneficial effect on LVEF at the end of follow-up in patients who had low LVEF at baseline as compared with RVA pacing. Thus, in line with current cardiac resynchronization therapy guidelines, it seems that the option of RVOT pacing should be reserved for patients with low baseline LVEF. With that in mind, the advantage observed in wall motion performance by RVOT pacing may not correlate with important clinical endpoints such as mortality. No study till date has shown superiority for non-apical pacing in terms of survival. We therefore suggest that a potential benefit of non-apical pacing should be further examined in a large randomized trial that will look at ‘harder’ endpoints in selected patients with low baseline LVEF. Conflict of interest: none declared.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.015 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".