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Record W2940208363 · doi:10.5603/fc.a2019.0027

Peripheral embolisation and retrieval of an everolimus-eluting stent during intervention in a tortuous right coronary artery

2016· article· en· W2940208363 on OpenAlexaboutno aff
Santosh Kumar Sinha, Sunil Kumar Tripathi, Anupam Singh, Lokendra Rekwaal, Nishant Kumar Abhishekh

Bibliographic record

VenueFolia Cardiologica · 2016
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEverolimusInternal medicineCardiologyRight coronary arteryPeripheralStentArteryCoronary angiographyMyocardial infarction

Abstract

fetched live from OpenAlex

A 78 year-old female with dyslipidemia, diabetes, and hypertension as cardiovascular risk factors underwent percutaneous coronary intervention of tortuous, diffusely diseased right coronary artery (90% stenosis) due to chronic stable angina (Canadian Cardiovascular Society class III) despite guideline-directed medical treatment. After predilatation, a 2.75 × 44 mm Xience Expedition everolimus-eluting stent (Abbott, USA) was tracked, which failed and embolised to the right deep femoral artery during its pullback. It was successfully retrieved by an EN snare: 6–10 mm (Merit Medical, USA) by contralateral femoral approach. Lesion was further dilated and successfully stented using a GuideLiner mother–and-child catheter (Vascular Solutions Inc., USA) by deploying two overlapping 2.75 × 33, and 3 × 23 Xience Expedition drug-eluting stents distally and proximally respectively showing proper stent expansion with TIMI-3 coronary flow.This case highlights trackability issues and the importance of adequate lesion preparation before stent deployment in a tortuous vessel with diffuse disease, especially with a very long 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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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 designCase report
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
Published2016
Admission routes1
Has abstractyes

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