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Abstract 12973: Intra-Procedural Change in Platelet Occlusion Time to Predict Hemodynamic and Clinical Outcomes Following Transcatheter Aortic Valve Replacement

2021· article· en· W3215053251 on OpenAlexaff
Sebastien Hecht, Jérémy Bernard, Lionel Tastet, Rami Abu-Alhayja’a, Jonathan Beaudoin, Nancy Côté, Robert DeLarochellière, Jean‐Michel Paradis, Marie‐Annick Clavel, Josep Rodés‐Cabau, Philippe Pîbarot

Bibliographic record

VenueCirculation · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart InstituteInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineCardiologyHemodynamicsInternal medicineStenosisRegurgitation (circulation)Valve replacementAortic valve replacementAortic valveRadiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.022
GPT teacher head0.350
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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