Abstract 12973: Intra-Procedural Change in Platelet Occlusion Time to Predict Hemodynamic and Clinical Outcomes Following Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
Background and Objectives: Transcatheter aortic valve implantation (TAVI) is an alternative to surgical aortic valve replacement for the therapeutic treatment of severe aortic stenosis. However, intraprocedural hemodynamic assessment by echocardiography is not always optimal and new tools are needed. A new approach using the blood biomarker measuring platelet occlusion time (CT-ADP) and more specifically its change between the pre-intervention and post-intervention (ΔCT-ADP) could be useful to overcome the lack of accuracy of echocardiography, but also to prevent adverse clinical events following TAVI. The objective of this study is to examine the association between ΔCT-ADP and i) intraprocedural valve hemodynamic performance; and ii) occurrence of all-cause death and rehospitalization for heart failure (HF) in TAVI patients. Methods: Three hundred and thirty-eight patients who underwent TAVI at our institute were recruited. Clinical and echocardiographic data were collected before and after the procedure. Two blood samples were collected prior to- and at the end of- TAVI to assess the immediate changes (Δ: pre minus post) in CT-ADP following TAVI. A percentage (Δ/pre-intervention value) was determined for CT-ADP and mean gradient (MG) for each patient. Results: Prior to TAVI, 135(40.0%) patients had a prolonged CT-ADP (>180 s). There was a significant but modest correlation between ΔCT-ADP and the change in mean transvalvular gradient immediately after TAVI (r=0.15, p=0.007). A ΔCT-ADP (i.e. decrease) >10% (i.e. median of cohort) was associated with a higher rate of transcatheter valve regurgitation ≥ moderate (0.0% vs 3.0%, p=0.030) following TAVI, and a longer length of hospital stay (7.8±8.3 vs. 9.7±9.0 days, p=0.002). During a median follow-up of 1.2 (1.0-2.4) years, there were 87 clinical events (30 rehospitalizations and 57 deaths). A ΔCT-ADP >10% tended toward higher risk of events in univariable analysis (HR[95%CI]: 1.49[0.94-2.37], p=0.090), but not after adjustment for other risk factors (HR[95%CI]: 1.10[0.53-2.28], p=0.79). Conclusion: A >10% decrease in CT-ADP immediately after TAVI is associated with worse hemodynamic outcomes. This association is not independent and appears to be related to other risk factors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".