Subclinical Leaflet Thrombosis in Transcatheter and Surgical Bioprosthetic Valves
Bibliographic record
Abstract
BACKGROUND: Subclinical leaflet thrombosis, characterized by hypoattenuated leaflet thickening (HALT) and reduced leaflet motion observed on 4-dimensional computed tomography (CT), may represent a form of bioprosthetic valve dysfunction. OBJECTIVES: The U.S. Food and Drug Administration mandated CT studies to understand the natural history of this finding, differences between transcatheter and surgical valves, and its association with valve hemodynamics and clinical outcomes. METHODS: The PARTNER 3 (The Safety and Effectiveness of the SAPIEN 3 Transcatheter Heart Valve in Low-Risk Patients With Aortic Stenosis) CT substudy randomized 435 patients with low-surgical-risk aortic stenosis to undergo transcatheter aortic valve replacement (n = 221) or surgery (n = 214). Serial 4-dimensional CTs were performed at 30 days and 1 year and were analyzed independently by a core laboratory. RESULTS: The incidence of HALT increased from 10% at 30 days to 24% at 1 year. Spontaneous resolution of 30-day HALT occurred in 54% of patients at 1 year, whereas new HALT appeared in 21% of patients at 1 year. HALT was more frequent in transcatheter versus surgical valves at 30 days (13% vs. 5%; p = 0.03), but not at 1 year (28% vs. 20%; p = 0.19). The presence of HALT did not significantly affect aortic valve mean gradients at 30 days or 1 year. Patients with HALT at both 30 days and 1 year, compared with those with no HALT at 30 days and 1 year, had significantly increased aortic valve gradients at 1 year (17.8 ± 2.2 mm Hg vs. 12.7. ± 0.3 mm Hg; p = 0.04). CONCLUSIONS: Subclinical leaflet thrombosis was more frequent in transcatheter compared with surgical valves at 30 days, but not at 1 year. The impact of HALT on thromboembolic complications and structural valve degeneration needs further assessment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".