A systematic review and meta-analysis of the impact of left bundle branch area pacing on right ventricular function
Bibliographic record
Abstract
Objective This study aims to systematically evaluate and perform a meta-analysis on the effects of LBBAP on right ventricular (RV) function by collecting data on Right Ventricular Fractional Area Change (RV-FAC), Tricuspid Annular Plane Systolic Excursion (TAPSE), Interventricular Mechanical Delay (IVMD), and the incidence of tricuspid regurgitation (TR) worsening in Left bundle branch area pacing (LBBAP) patients. Methods A comprehensive search was conducted for studies published from the establishment of the respective databases until October 2024 in PubMed, Embase, Web of Science, and the Cochrane Library. After screening and data extraction, the Newcastle-Ottawa Scale was used for the quality assessment of the included cohort studies, and meta-analysis was performed using R software. The effect size was estimated using either a random-effect model or a fixed-effect model, with odds ratio (OR) and mean difference (MD). Results A total of 14 studies were included, analyzing 1,555 LBBAP patients. The meta-analysis revealed that compared with intrinsic conduction, LBBAP implantation significantly improved RV-FAC (MD = 1.93; 95% CI: 0.64–3.23, P = 0.0034) and TAPSE (MD = 1.57; 95% CI: 1.07–2.06, P < 0.0001). Compared to the RVP group, LBBAP implantation significantly shortened IVMD (MD = −21.27; 95% CI: −31.33 to −11.22, P < 0.0001). For patients with RV dysfunction or right bundle branch block (RBBB), LBBAP implantation also significantly reduced IVMD (MD = −31.31; 95% CI: −37.10 to −25.52, P < 0.0001). The incidence of TR worsening within one year after LBBAP was approximately 8%, increasing to 23% beyond one year. Conclusion This meta-analysis demonstrates the superiority of LBBAP over intrinsic conduction in improving RV systolic function. Compared to RVP, LBBAP significantly enhances biventricular synchronization. Furthermore, LBBAP also improves ventricular synchronization in patients with RV dysfunction or RBBB.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".