Clinical impact of conduction disturbances in transcatheter aortic valve replacement recipients: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: The clinical impact of new-onset persistent left bundle branch block (NOP-LBBB) and permanent pacemaker implantation (PPI) on transcatheter aortic valve replacement (TAVR) recipients remains controversial. We aimed to evaluate the impact of (i) periprocedural NOP-LBBB and PPI post-TAVR on 1-year all-cause death, cardiac death, and heart failure hospitalization and (ii) NOP-LBBB on the need for PPI at 1-year follow-up. METHODS AND RESULTS: We performed a systematic search from PubMed and EMBASE databases for studies reporting raw data on 1-year clinical impact of NOP-LBBB or periprocedural PPI post-TAVR. Data from 30 studies, including 7792 patients (12 studies) and 42 927 patients (21 studies) for the evaluation of the impact of NOP-LBBB and PPI after TAVR were sourced, respectively. NOP-LBBB was associated with an increased risk of all-cause death [risk ratio (RR) 1.32, 95% confidence interval (CI) 1.17-1.49; P < 0.001], cardiac death (RR 1.46, 95% CI 1.20-1.78; P < 0.001), heart failure hospitalization (RR 1.35, 95% CI 1.05-1.72; P = 0.02), and PPI (RR 1.89, 95% CI 1.58-2.27; P < 0.001) at 1-year follow-up. Periprocedural PPI after TAVR was associated with a higher risk of all-cause death (RR 1.17, 95% CI 1.11-1.25; P < 0.001) and heart failure hospitalization (RR 1.18, 95% CI 1.03-1.36; P = 0.02). Permanent pacemaker implantation was not associated with an increased risk of cardiac death (RR 0.84, 95% CI 0.67-1.05; P = 0.13). CONCLUSION: NOP-LBBB and PPI after TAVR are associated with an increased risk of all-cause death and heart failure hospitalization at 1-year follow-up. Periprocedural NOP-LBBB also increased the risk of cardiac death and PPI within the year following the procedure. Further studies are urgently warranted to enhance preventive measures and optimize the management of conduction disturbances post-TAVR.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".