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Record W2098159631 · doi:10.1002/ccd.24376

Effect of percutaneous coronary intervention on quality of life: A consensus statement from the society for cardiovascular angiography and interventions

2012· review· en· W2098159631 on OpenAlexaboutno aff
James C. Blankenship, J. Jeffrey Marshall, Duane S. Pinto, Richard A. Lange, Eric Bates, Elizabeth M. Holper, Cindy L. Grines, Charles E. Chambers

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2012
Typereview
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConventional PCIPercutaneous coronary interventionAnginaPsychological interventionQuality of life (healthcare)Canadian Cardiovascular SocietyCoronary artery diseaseCardiologyReimbursementInternal medicineIntervention (counseling)Physical therapyMyocardial infarctionHealth careNursing

Abstract

fetched live from OpenAlex

Percutaneous coronary intervention (PCI) decreases ischemic complications of acute coronary syndromes. The benefits of PCI in stable ischemic heart disease (SIHD) depend on its effect on quality of life (QoL), including angina, physical activity, and emotional well-being. PCI decreases angina and the need for anti-anginal medications, and increases exercise capacity and QoL, compared with baseline status and compared with medical therapy without PCI. These benefits are greater when QOL is markedly impaired by severe angina before the procedure. When considering treatment options for symptomatic SIHD, physicians should consider and provide objective data regarding QoL effects for each treatment strategy. QoL outcomes should be considered in clinical trials, appropriate use criteria, practice guidelines, and reimbursement policies for PCI.

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)0.006
metaresearch head score (Gemma)0.006
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 score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.003
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 head0.084
GPT teacher head0.369
Teacher spread0.285 · 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

Citations52
Published2012
Admission routes1
Has abstractyes

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