Atrial Fibrillation is Associated with Increased Pacemaker Implantation Rates in the Placement of AoRTic Transcatheter Valve (PARTNER) Trial
Bibliographic record
Abstract
Atrial fibrillation (AF) is associated with worse outcomes in many cardiovascular diseases. There are few data examining pacemaker implantation rates and indications in patients with AF who undergo transcatheter aortic valve replacement (TAVR). To examine the impact of AF on the incidence of and indications for pacemakers in patients undergoing TAVR, we evaluated data of 1723 patients without pre-existing pacemakers who underwent TAVR in the Placement of AoRTic TraNscathetER Valve (PARTNER) trial. Permanent pacemaker implantation rates and indications were compared in groups based on baseline and discharge heart rhythm: sinus rhythm (SR) vs. AF. 1211 patients manifested SR at baseline/SR at discharge (SR/SR), 105 SR baseline/AF discharge (SR/AF), and 407 AF baseline/AF discharge (AF/AF). Patients who developed and were discharged with AF (SR/AF) had the highest rates of pacemaker implantation at 30 days (13.7% SR/AF vs. 5.4% SR/SR, p=0.0008 and 5.9% AF/AF, p=0.008) and 1 year (17.7% SR/AF vs. 7.1% SR/SR, p=0.0002 and 8.1% AF/AF, p=0.0034). Conversion from SR to AF by discharge was an independent predictor of increased pacemaker implantation at 30 days (HR 2.19 vs. SR/SR, 95% CI 1.23-3.93, p=0.008) and 1 year (HR 1.91 vs. SR/SR, 95% CI 1.33-3.80). Pacemaker indications differed between groups, with relatively more implanted in the AF groups for sick sinus syndrome (SSS) versus AV block. In conclusion, conversion to AF is an independent predictor of permanent pacemaker implantation in TAVR patients. Indications differ depending on heart rhythm, with patients in AF manifesting clinically significant tachy-brady syndrome versus AV block.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".