Early hypo-attenuated leaflet thickening in balloon-expandable transcatheter aortic heart valves
Bibliographic record
Abstract
AIMS: We sought to evaluate the frequency of early hypo-attenuated leaflet thickening (HALT) of the SAPIEN 3 transcatheter aortic valve (S3). METHODS AND RESULTS: Of 249 patients who had undergone S3 implantation, we studied 156 consecutive patients (85 women, median age 82.2 ± 5.5 years) by electrocardiogram (ECG)-triggered dual-source computed tomography angiography (CTA) after a median of 5 days post-transcatheter aortic valve implantation. The prosthesis was assessed for HALT. Apart from heparin, peri-interventional antithrombotic therapy consisted of single- (aspirin 29%) or dual- (aspirin plus clopidogrel 71%) antiplatelet therapy. Hypo-attenuated leaflet thickening was found in 16 patients [10.3% (95% confidence interval (CI) 5.5-15.0%)] of the patients. None of the baseline and procedural variables were significantly associated with HALT, nor did we find a significant association with the antithrombotic regimen, either peri-interventionally or at the time of CTA. Hypo-attenuated leaflet thickening was found in 6 of 45 patients with peri-interventional single-antiplatelet therapy and in 10 of 111 patients with dual-antiplatelet therapy at the time of intervention [13.3% (95% CI 3.4-23.3%) vs. 9% (95% CI 3.7-14.3%), P = 0.42]. Hypo-attenuated leaflet thickening was not associated with clinical symptoms, but a small, albeit significant difference in mean pressure gradient at the time of CTA (11.6 ± 3.4 vs. 14.9 ± 5.3 mmHg, P = 0.026). Full anticoagulation led to almost complete resolution of HALT in 13 patients with follow-up CTA. CONCLUSION: Irrespective of the antiplatelet regimen, early HALT occurred in 10% of our patients undergoing transcatheter aortic S3 implantation. Early HALT is clinically inapparent and reversible by full anticoagulation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".