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Record W4389510556 · doi:10.24835/1727-818x-73-20

Features of re-endothelialization process during implantation of coronary stents (review of literature)

2023· article· en· W4389510556 on OpenAlexaboutno aff

Bibliographic record

VenueINTERNATIONAL JOURNAL OF INTERVENTIONAL CARDIOANGIOLOGY · 2023
Typearticle
Languageen
FieldEngineering
TopicPolymer Science and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsRestenosisMedicineBare metalCardiologyAngioplastyInternal medicineStentCoronary artery diseaseBalloonCoronary arteriesBare-metal stentRevascularizationArteryDrug-eluting stentMyocardial infarction

Abstract

fetched live from OpenAlex

Method of endovascular treatment for coronary artery lesions has made its way from balloon angioplasty to implantation of drug-eluting stents. Today, drug-eluting stents are widely used for coronary artery revascularization and have significantly reduced the incidence of restenosis compared to bare metal stents. Delayed or incomplete re-endothelialization is a very specific problem for most drug-eluting stents, as after their implantation, there is a risk of developing late thrombosis associated not only with incomplete endothelialization of the stent struts or impaired endothelial function, but also with chronic inflammatory reaction of the vascular wall. The development of stents with ultrathin struts, the abluminal coating of the struts with polymer and drug contribute to the decrease of vascular wall trauma and of the inflammatory response and provide faster stent endothelialization. Keywords: coronary heart disease, coronary stents, re-endothelialization, microporous coating, polymer-free antiproliferative coating, Yukon stent

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.312
Teacher spread0.299 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

Explore more

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