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Record W4409017833 · doi:10.21037/qims-24-2059

Peak regurgitant diastolic wall shear stress increases in bicuspid aortic valve regurgitation: association of regurgitation severities and aortic root dilation

2025· article· en· W4409017833 on OpenAlexaff
Shirin Aliabadi, Carmen Lydell, Louis Kolman, Murad Bandali, Julio García

Bibliographic record

VenueQuantitative Imaging in Medicine and Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsAlberta Children's HospitalLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsRegurgitation (circulation)Bicuspid aortic valveCardiologyAortic rootInternal medicineMedicineShear stressAortic valveDilation (metric space)DiastoleAortaMaterials scienceMathematicsComposite materialBlood pressureGeometry

Abstract

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Background: Bicuspid aortic valve (BAV) disease, especially with regurgitation, lacks adequate clinical management. While root aortopathy is often attributed to genetic factors and aortic regurgitation, the diastolic hemodynamic characteristics in BAV patients with varying regurgitation severities are not well understood. Flow-derived velocity-weighted flow displacement (FD) and wall shear stress (WSS) are linked to aortopathy progression. We sought to evaluate peak systolic and peak regurgitant diastolic regional WSS and FD at the aortic root in BAV patients with regurgitation (BAV-REG) and BAV patients without or with trivial regurgitation (BAV-No/Trivial REG). Methods: To conduct this retrospective study, a total of 98 subjects (N=38 BAV-No/Trivial REG, age: 48±16 years, N=35 BAV-REG, age: 52±13 years, and N=25 healthy, age: 38±14 years) were recruited. All subjects underwent routine cardiac magnetic resonance imaging (MRI) followed by four-dimensional cardiovascular magnetic resonance flow imaging using a 3.0 Tesla MRI scanner. Regional peak systolic (WSSSys) and peak regurgitant diastolic (WSSDia) WSS as well as FD (FDSys, FDDia) at annulus, sinus of Valsalva, sinotubular junction, and mid ascending aorta planes were calculated by dividing the extracted two-dimensional planes into eight sectors. Patients were also followed for the occurrence of aortic valve surgery. Independent-samples Kruskal-Wallis H test (Bonferroni corrected at a 0.05 significance level), along with univariate and logistic regression analyses statistical tests were used. Results: BAV-REG had similar planar WSSSys patterns compared to BAV-No/Trivial REG. However, peak regurgitant planar WSSDia was significantly higher in BAV-REG compared to both healthy controls and BAV-No/Trivial REG at the annulus and sinus of Valsalva planes (P<0.05) in specific left-sided octants. Normalized peak regurgitant FDDia was significantly higher only in BAV-REG compared to healthy controls (P=0.03). WSSDia showed a significant association with the regurgitation severities at the annulus (ρ=0.34, P<0.001), sinus of Valsalva (ρ=0.34, P<0.001), sinotubular junction (ρ=0.48, P<0.001) planes. Furthermore, logistic regression analysis highlighted the potential role of peak regurgitant WSSDia in the likelihood of requiring surgery (β=5.49, P=0.009). Conclusions: Higher WSSDia in BAV patients, particularly in BAV-REG, and the significant association between WSSDia and regurgitation severity underscore its potential pathophysiological role in aortic root dilation.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.028
GPT teacher head0.313
Teacher spread0.285 · 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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Citations1
Published2025
Admission routes1
Has abstractyes

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