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Record W4210828549 · doi:10.1093/ehjci/jeab289.366

Severe MAC increases shear stresses on particles traversing the mitral valve: an in vitro study

2022· article· en· W4210828549 on OpenAlexaff
GS Pressman, Ahmed Darwish, EJ Friend, PC Wiener, Lyes Kadem

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsConcordia University
Fundersnot available
KeywordsShear stressMaterials scienceVentricleMitral valveCardiologyBiomedical engineeringInternal medicineMedicineComposite material

Abstract

fetched live from OpenAlex

Abstract Funding Acknowledgements Type of funding sources: None. Background Mitral annular calcification (MAC) is a strong predictor of stroke but mechanism(s) are poorly defined. Severe MAC can produce a gradient across the mitral valve (MV) and, when studied in vitro, disturbs normal flow across the valve resulting in increased viscous energy dissipation. Purpose We hypothesized that severe MAC would increase shear stress on particles traveling across the MV into the left ventricle (LV). Given that shear stresses cause platelet activation this might represent a mechanism by which MAC could increase stroke risk. Methods A silicone model MV was created using a 3D TEE dataset. 3D printed calcium phantoms were incorporated into the valve simulate severe MAC. The valve was tested in a left heart duplicator under rest and exercise conditions and compared with a duplicate valve without the calcium phantoms. Fine particles suspended in a water/glycerol blood analogue allowed for measurement of vortex formation and shear stresses using particle image velocimetry (PIV). Particle residence time (PRT) maps were created to assess how long blood particles would remain in the LV. Particle residence index (PRI - ratio of remaining particles in LV/initial number of particles) is a more quantitative measure of how fast particles leave the LV. These calculations were used to approximate viscous shear stresses on blood particles. For each particle the induced viscous shear stress was evaluated for the entire duration of residence in the LV. Results For the normal MV all released particles left the LV by the 3rd cycle; with severe MAC particles completely left the LV shortly after the 7th cycle. PRI measurements confirmed that particles remained longer in the LV in the presence of severe MAC (figure 1). MAC also induced a shift in the accumulated shear stress levels from the high range > 0.4 Pa.s and the low range < 0.1 towards the middle region (0.16-0.32 Pa.s, figure 2). As shear stress is reported for one cycle, one may expect MAC to lead to higher accumulated higher viscous stresses as particles reside in the LV for a longer time. Conclusions In the presence of severe MAC blood particles remain longer in the LV and are exposed to greater cumulative shear stresses vs the normal situation. Given that shear stress is known to cause platelet activation this may be a mechanism by which MAC increases risk of ischemic stroke. Abstract Figure 1 Abstract Figure 2

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.074
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.312
Teacher spread0.286 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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