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Record W2943872206 · doi:10.15420/ecr.2018.26.1

Stable Angina Medical Therapy Management Guidelines: A Critical Review of Guidelines from the European Society of Cardiology and National Institute for Health and Care Excellence

2019· review· en· W2943872206 on OpenAlexaboutno aff
Talla A. Rousan, Udho Thadani

Bibliographic record

VenueEuropean Cardiology Review · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
FundersNational Institutes of HealthGilead SciencesAstraZenecaAmgen
KeywordsMedicineNiceExcellenceAnginaCoronary artery diseaseIntensive care medicineMedical therapyHealth careCanadian Cardiovascular SocietyStable anginaAspirinClinical trialCardiologyInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Most patients with stable angina can be managed with lifestyle changes, especially smoking cessation and regular exercise, along with taking antianginal drugs. Randomised controlled trials show that antianginal drugs are equally effective and none of them reduced mortality or the risk of MI, yet guidelines prefer the use of beta-blockers and calcium channel blockers as a first-line treatment. The European Society of Cardiology guidelines for the management of stable coronary artery disease provide classes of recommendation with levels of evidence that are well defined. The National Institute for Health and Care Excellence (NICE) guidelines for the management of stable angina provide guidelines based on cost and effectiveness using the terms first-line and second-line therapy. Both guidelines recommend using low-dose aspirin and statins as disease-modifying agents. The aim of this article is to critically appraise the guidelines' pharmacological recommendations for managing patients with stable 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 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)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.193
GPT teacher head0.446
Teacher spread0.253 · 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.

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
Published2019
Admission routes1
Has abstractyes

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