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The Influence of Mitral Tilted Implantation Position on the Transmitral Pressure Gradient

2025· article· W4415934506 on OpenAlexaff
Mouhammad El Hassan, Nikolay Bukharin, Zeeshan A. Rana, Ênio Pedone Bandarra Filho

Bibliographic record

Venuenot available
Typearticle
Language
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSAIT Polytechnic
Fundersnot available
KeywordsTilt (camera)Pressure gradientMitral valveHemodynamicsDiastoleCardiac catheterizationCatheter

Abstract

fetched live from OpenAlex

This study investigates the impact of mitral valve implantation tilt on transmitral pressure gradients using an in vitro left-heart simulator. A 25 mm mitral bioprosthesis was tested in four positions: posterior-lateral (reference), apical, septal 10°, and septal 20° tilts. Pressure gradients were measured simultaneously with catheterization and particle image velocimetry (PIV). Compared with the physiological posterior-lateral orientation, apical tilt produced only minor changes, whereas septal tilting resulted in substantially higher peak and mean diastolic gradients, with increases of up to$\sim 58 \%$. A substantial hemodynamic penalty occurs when the mitral valve is tilted in the septal direction as compared to the posterior-lateral and apical positions. A good agreement was found between the PIV and catheter measurements of the transvalvular pressure gradients. The present findings highlight the importance of avoiding septal tilt during surgical implantation to minimize adverse pressure gradients.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.306
Teacher spread0.300 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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