Routine post-dilatation at nominal volume to optimise the expansion of balloon-expandable valves: the DOUBLE-TAP study
Bibliographic record
Abstract
BACKGROUND: Incomplete expansion of balloon-expandable (BE) transcatheter heart valves (THVs) is sometimes treated by ad hoc post-dilatation with an overfilled or larger valvuloplasty balloon. The efficacy of this approach has not been rigorously evaluated, although increased risk for adverse events has been demonstrated. Observational experience suggests that post-dilatation using the original delivery system balloon at the identical filling volume (i.e., double-tap) may routinely improve the degree of THV expansion with low risk. AIMS: We sought to assess the safety and efficacy of a strategy of routine double-tap after BE transcatheter aortic valve implantation (TAVI). METHODS: Patients undergoing TAVI with the SAPIEN 3 Ultra (S3U) valve were prospectively included. Patients with severe annular or subannular calcification were excluded. A validated method of fluoroscopic analysis was utilised to assess the cross-sectional area at the inflow, midpoint, and outflow of the THV before and after double-tap. Thirty-day clinical outcomes were documented. RESULTS: Routine double-tap was performed in 102 patients. Despite nominal deployment, all patients had some degree of THV underexpansion after the first inflation. Fluoroscopic analysis documented an increase in minimal THV expansion by cross-sectional area of 9.8% for the 20 mm S3U (p=0.151), 9.9% for the 23 mm S3U (p<0.001), 9.2% for the 26 mm S3U (p<0.001), and 8.6% for the 29 mm S3U (p=0.002). There was no stroke or cardiovascular mortality at 30 days. CONCLUSIONS: In favourable anatomy, routine double-tap after BE TAVI improved THV expansion with no safety concerns. The impact of this strategy on THV function, haemodynamic profile, and durability remains to be determined.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".