Impact of Predilation During Transcatheter Aortic Valve Replacement: Insights From the PARTNER 3 Trial
Bibliographic record
Abstract
Background: The use of predilation during transcatheter aortic valve replacement (TAVR) is variable, and its association with outcomes remains unknown. We evaluated the impact of predilation versus no predilation (direct TAVR) in the low-risk population enrolled in the PARTNER 3 trial (Placement of Aortic Transcatheter Valves). Methods: In the PARTNER 3 trial, 495 patients with severe symptomatic aortic stenosis underwent TAVR with the SAPIEN 3 valve. The use of predilation was left to operator discretion. The primary end point was a composite of all-cause death, stroke, or rehospitalization. Secondary end points included valve hemodynamic performance and the need for postdilation. Propensity score matching was performed. Results: Predilation and direct TAVR were performed in 286 (57.8%) and 209 (42.2%) patients, respectively. Before matching, the primary end point occurrence at 30 days (3.8% versus 4.8%, P =0.604) and 1 year (8.7% versus 8.1%, P =0.831) was similar in the predilation versus direct TAVR groups. Similar results were observed after matching (202 patients in each groups). Incidence of ≥ mild paravalvular regurgitation was similar in both groups. Incidence of severe prosthesis-patient mismatch was low but higher in the predilation group versus the direct TAVR group (8.2% versus 2.6%, P =0.023). Compared with direct TAVR, the use of predilation was associated with longer procedure duration (63.2 versus 51.4 minutes, P =0.001), while the rate of postdilation did not differ between the 2 groups (24.8% versus 18.8%, P =0.150). Conclusions: Predilation and direct TAVR are safe in patients with low surgical risk and favorable aortic valve anatomy. Direct TAVR decreased the procedure duration and did not predispose to more postdilation. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02675114.
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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 | 0.029 |
| 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) | 0.000 | 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 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".