Impact of transcatheter aortic valve implantation on circulating von Willebrand factor in patients with severe aortic stenosis
Bibliographic record
Abstract
INTRODUCTION: Severe aortic stenosis (AS) can lead to degradation of high molecular weight (HMW) von Willebrand factor (VWF) which can result in haemostatic abnormalities. While studies have explored changes in VWF profiles before and after surgical aortic valve replacement (SAVR), the longer-term changes in VWF profiles pre- and post-transcatheter aortic valve implantation (TAVI) are less understood. AIM: Our primary objective was to identify differences in VWF multimer profiles and VWF function pre-TAVI and 1-month post-TAVI. Our secondary objective was to correlate VWF markers with measures of AS severity. METHODS: Adult patients with severe AS referred for TAVI at our institution were prospectively enrolled in this cohort study. Blood samples were collected for plasma analysis at three time points for all patients: 1 day pre-TAVI, 3 days post-TAVI, and 1-month post-TAVI. VWF antigen, activity, propeptide, collagen binding, multimers, and factor VIII coagulant activity were determined at each time point. Correlations between VWF parameters and severity of AS were assessed. RESULTS: Twenty participants (15 males, five females) with severe AS were recruited for the study. There was a significant increase in HMW VWF between pre-procedure and 1-month post-TAVI (p < .05). There was a transient increase in VWF antigen levels and activity at 3-days post TAVI that decreased to pre-TAVI levels at 1-month. There were no statistically significant correlations between VWF markers and AS severity. CONCLUSIONS: This is the first study to elucidate longer-term (>1 week) improvements in HMW VWF after a TAVI procedure in severe AS patients.
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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 | 0.000 | 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".