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Record W179279341

Angina following percutaneous coronary intervention: in-stent restenosis.

2009· article· en· W179279341 on OpenAlexaff
Karen Throndson, Jo‐Ann V. Sawatzky

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsConventional PCIMedicinePercutaneous coronary interventionAnginaRestenosisCardiologyCoronary artery diseaseInternal medicineStentComplicationAngioplastyIntensive care medicineMyocardial infarction
DOInot available

Abstract

fetched live from OpenAlex

Percutaneous coronary intervention (PCI) represents a technical advance in the treatment of coronary artery disease. However, it is not without risks both during and after the procedure. In-stent restenosis (ISR) is the most common complication following PCI. Individuals who experience angina associated with ISR often fail to recognize its seriousness and, therefore, do not respond appropriately to the situation. Individuals with ISR are vulnerable to the consequences of angina, including increased morbidity and mortality, as well as a decreased health-related quality of life. In this article, the authors review the risks for developing ISR, the pathophysiology of angina related to ISR, and the challenges that face patients who develop recurrent angina post-PCI. Cardiovascular nurses play a critical role in the clinical management and education of patients following PCI. The provision of post-PCI follow-up care is key to identifying, managing, and supporting patients with recurrent angina.

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)0.001
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.240
GPT teacher head0.368
Teacher spread0.128 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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