Permanent Pacemaker Implantation After Transcatheter Aortic Valve Implantation
Bibliographic record
Abstract
BACKGROUND: Very few data exist on the clinical impact of permanent pacemaker implantation (PPI) after transcatheter aortic valve implantation. The objective of this study was to assess the impact of PPI after transcatheter aortic valve implantation on late outcomes in a large cohort of patients. METHODS AND RESULTS: A total of 1556 consecutive patients without prior PPI undergoing transcatheter aortic valve implantation were included. Of them, 239 patients (15.4%) required a PPI within the first 30 days after transcatheter aortic valve implantation. At a mean follow-up of 22±17 months, no association was observed between the need for 30-day PPI and all-cause mortality (hazard ratio, 0.98; 95% confidence interval, 0.74-1.30; P=0.871), cardiovascular mortality (hazard ratio, 0.81; 95% confidence interval, 0.56-1.17; P=0.270), and all-cause mortality or rehospitalization for heart failure (hazard ratio, 1.00; 95% confidence interval, 0.77-1.30; P=0.980). A lower rate of unexpected (sudden or unknown) death was observed in patients with PPI (hazard ratio, 0.31; 95% confidence interval, 0.11-0.85; P=0.023). Patients with new PPI showed a poorer evolution of left ventricular ejection fraction over time (P=0.017), and new PPI was an independent predictor of left ventricular ejection fraction decrease at the 6- to 12-month follow-up (estimated coefficient, -2.26; 95% confidence interval, -4.07 to -0.44; P=0.013; R(2)=0.121). CONCLUSIONS: The need for PPI was a frequent complication of transcatheter aortic valve implantation, but it was not associated with any increase in overall or cardiovascular death or rehospitalization for heart failure after a mean follow-up of ≈2 years. Indeed, 30-day PPI was a protective factor for the occurrence of unexpected (sudden or unknown) death. However, new PPI did have a negative effect on left ventricular function over time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".