MétaCan
Menu
Back to cohort
Record W2005703095 · doi:10.1115/1.4029747

The Influence of the Aortic Root Geometry on Flow Characteristics of a Prosthetic Heart Valve

2015· article· en· W2005703095 on OpenAlexaff
Oleksandr Barannyk, Peter Oshkai

Bibliographic record

VenueJournal of Biomechanical Engineering · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAortic valveCardiologyInternal medicineAortic rootMedicineStenosisAortic valve stenosisRegurgitation (circulation)Heart valveVentricular pressureAortaHemodynamics

Abstract

fetched live from OpenAlex

In this paper, performance of aortic heart valve prosthesis in different geometries of the aortic root is investigated experimentally. The objective of this investigation is to establish a set of parameters, which are associated with abnormal flow patterns due to the flow through a prosthetic heart valve implanted in the patients that had certain types of valve diseases prior to the valve replacement. Specific valve diseases were classified into two clinical categories and were correlated with the corresponding changes in aortic root geometry while keeping the aortic base diameter fixed. These categories correspond to aortic valve stenosis and aortic valve insufficiency. The control case that corresponds to the aortic root of a patient without valve disease was used as a reference. Experiments were performed at test conditions corresponding to 70 beats/min, 5.5 L/min target cardiac output, and a mean aortic pressure of 100 mmHg. By varying the aortic root geometry, while keeping the diameter of the orifice constant, it was possible to investigate corresponding changes in the levels of Reynolds shear stress and establish the possibility of platelet activation and, as a result of that, the formation of blood clots.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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 teacher head, 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".

Quick stats

Citations25
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biomechanical EngineeringSame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207