Global Results From the Optimize PRO Study: Standardized TAVR Technique and Care Pathway
Bibliographic record
Abstract
Background: The safety and efficacy of utilizing standardized implant protocols and care pathways are limited in large global prospective studies of transcatheter aortic valve replacement (TAVR), and institutional variability remains. This analysis aims to report 30-day outcomes from the global Optimize PRO study evaluating valve performance and procedural outcomes using an "optimized" TAVR care pathway and the cusp overlap technique (COT) in patients receiving Evolut PRO/PRO+ valves. Methods: The Optimize PRO study is a multicenter, postmarket, prospective study conducted in 50 centers in the United States, Canada, Europe, the Middle East, and Australia. Patients with symptomatic severe aortic stenosis and no preexisting pacemakers underwent TAVR with standardized optimized preprocedure, periprocedure, and postprocedure pathways. Results: There were 653 patients with attempted TAVR implants, a mean age of 79.1 ± 6.5 years, and a mean Society of Thoracic Surgeons predictive risk of mortality of 3.2% ± 2.5%. The primary 30-day end point of all-cause mortality or all stroke was 5.1%, all-cause mortality 0.8%, and disabling stroke 1.7%. The new 30-day permanent pacemaker implantation rate was 6.4% with 4-step COT compliance and 11.1% overall. At discharge, there were no instances of moderate or severe aortic regurgitation, and 76.2% of patients had none/trace aortic regurgitation. The median length of stay was 2 days. Conclusions: The Optimize PRO study demonstrated low rates of new permanent pacemaker implantation and no moderate to severe aortic regurgitation after TAVR with Evolut PRO/PRO+ using COT and perioperative protocols in a global cohort of severe aortic stenosis patients. Best practices resulted in consistent implantation depth and low complication rates.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".