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Narrative Review: Pharmacotherapy for Chronic Heart Failure: Evidence from Recent Clinical Trials

2005· review· en· W2067932198 on OpenAlexaff
Andrew T. Yan, Raymond T. Yan, Peter P. Liu

Bibliographic record

VenueAnnals of Internal Medicine · 2005
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineHeart failureClinical trialIntensive care medicinePharmacotherapyNarrative reviewAngiotensin Receptor BlockersEplerenoneCardiologyInternal medicineAngiotensin-converting enzymeBlood pressureSpironolactone

Abstract

fetched live from OpenAlex

Heart failure is an important cause of morbidity and mortality. Clinical trials over the past 2 decades have revolutionized the care of patients with systolic heart failure, and substantial data support the use of angiotensin-converting enzyme inhibitors, beta-blockers, angiotensin-receptor blockers, and aldosterone blockers in the management of this serious condition. This article reviews the evidence on the pharmacologic treatment of heart failure, with a focus on recent clinical trials.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.491
GPT teacher head0.609
Teacher spread0.118 · 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

Citations50
Published2005
Admission routes1
Has abstractyes

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