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Abstract 4367120: Impact of Aortic Valve Calcification on Functional Valve Area and Cardiac Structure and Function in a Phase 2 Trial of Ataciguat

2025· article· en· W4415789851 on OpenAlexaff
Héctor I. Michelena, Philippe Pîbarot, Wanying Li, Ping Wu, Jay M. Edelberg, Carlos del Rı́o, Cheryl Abbas, Jordan D. Miller, Brian R. Lindman

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
Keywordsvalvular heart diseasePlaceboAortic valveStenosisCardiac function curveCalcificationDiastoleAortic valve stenosisHeart failure

Abstract

fetched live from OpenAlex

Background: Calcific aortic valve stenosis (CAVS) is characterized by the progressive accrual of aortic valvular calcium (AVC), resulting in impaired valvular compliance and mechanics and impaired cardiac function leading to heart failure (HF). In a phase 2 trial of 23 patients with moderate CAVS, ataciguat (ATA), a soluble guanylate cyclase activator, relative to placebo slowed the deposition of AVC, decreases in aortic valve area (AVA; by continuity equation), and increases in diastolic dysfunction and left ventricular (LV) mass. ATA may have other favorable effects on ventricular, valvular, and/or vascular pathophysiology relevant to patients with CAVS. Hypothesis: We hypothesized that slowing the rate of AVC deposition is associated with improvements in valvular compliance and in measures of cardiac structure and function. Methods: A phase 2 study randomized patients with moderate CAVS 1:1 to receive ATA 200 mg/day or placebo for up to 12 months (NCT02481258). The primary endpoint was change in AVC assessed by cardiac CT, and measures of aortic valve function and cardiac structure and function were also assessed. AVA was calculated by the Modified Gorlin (Hakki) equation to additionally assess valvular compliance. Correlations between AVC, AVA, and other measures of cardiac structure and function were assessed by exploratory linear mixed models. Results: Changes in AVC from baseline were negatively correlated with changes in AVA (slope = −0.0002 [95% CI −0.0004, 0.0001]; Figure 1), such that patients with the least AVC deposition had minimal changes in AVA. Reciprocally, changes from baseline in AVA were positively correlated with changes in cardiac output (CO; slope = 0.16 [95% CI 0.13, 0.18]; Figure 2). Treatment with ATA, compared with placebo, was associated with improvements in systolic function. Changes in AVC deposition correlated with changes in CO (slope = −0.0007 [95% CI −0.0021, 0.0008]; Figure 3), and measured improvements in CO were generally more observed in patients with less of an increase in AVC, which were more frequently observed in those treated with ATA compared with placebo. Conclusions: These data suggest that slowing the rate of AVC deposition with ATA may result in improvements in CO through improved myocardial function and valvular compliance. Larger controlled trials are needed to assess such favorable myocardial/valvular effects that may help to preserve functional capacity and slow progression to HF.

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.023
GPT teacher head0.355
Teacher spread0.332 · 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 designNon-randomized trial
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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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