MétaCan
Menu
Back to cohort
Record W2019005961 · doi:10.3346/jkms.2001.16.1.31

Influence of stent expansion states on platelet deposition in an extracorporeal porcine arteriovenous shunt model using a multichannel perfusion chamber

2001· article· en· W2019005961 on OpenAlexaff
Taehoon Ahn, Eak-Kyun Shin, Yahye Merhi, Pierre Thai, Luc Bilodeau

Bibliographic record

VenueJournal of Korean Medical Science · 2001
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsPerfusionExtracorporealShunt (medical)StenosisStentBlood flowPlateletNuclear medicineExtracorporeal circulationBiomedical engineeringMedicineCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Limited data are available about incomplete stent expansion (SE) on platelet deposition (PD). We examined PD following different SE using an extracorporeal porcine arteriovenous shunt model to which a perfusion chamber with four parallel silastic tubes were connected. Blood flow was set at a 20 and 100 mL/min in 1.8 and 3.1 mm diameter tubes, respectively. P154 stents were deployed completely (Group A, n=15) or incompletely (Group B, n=15) in 1.8 mm (n=13) and 3.1 mm (n=17) tubes. 51Cr-labelled platelet autologous blood was injected 1 hr before the perfusion. After 15 min-perfusion, the testing tubes were assessed for radioactivity counts. In-stent cross sectional area was measured by intravascular ultrasound. There was a significant difference in PD between group A and B regardless of channel size (118+/-18.4 vs 261.4+/-52.1 pits x 10(6)/cm2, p<0.05). With adjusted shear rate and similar stenosis, PD was similar in both tubes. In smaller 1.8 mm tubes, a stenosis as subtle as 10% was associated with a significant PD difference (226.1+/-20 vs 112.9+/-20.5 plts x 10(6)/cm2, p<0.005). This model enabled a repetitive, simultaneous comparison of PD following different SE states. It seems that the quality of SE remains crucial in smaller channels.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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 designSimulation or modeling
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

Citations4
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Korean Medical ScienceSame topicCardiac Arrhythmias and TreatmentsFrench-language works237,207