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Record W4323846129 · doi:10.3390/jcdd10030114

Practical Pharmacological Treatment of Heart Failure: Does Ejection Fraction Matter Anymore?

2023· review· en· W4323846129 on OpenAlexaff
Jonathan C.H. Chan, Emily Cowley, Michael Chan

Bibliographic record

VenueJournal of Cardiovascular Development and Disease · 2023
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsEjection fractionHeart failureMedicineCardiologyInternal medicineClinical trial

Abstract

fetched live from OpenAlex

Heart failure (HF) is a complex clinical syndrome involving structural and/or functional abnormalities of the heart. Heart failure is often classified based on left ventricular ejection fraction, which serves as a predictor of mortality. The majority of the data supporting disease-modifying pharmacological therapies are from patients with reduced ejection fraction (less than 40%). However, with the recent results from the sodium glucose cotransporter-2 inhibitor trials, there is renewed interest in identifying potential beneficial pharmacological therapies. This review focuses on and includes pharmacological HF therapies across the spectrum of ejection fraction, providing an overview of the novel trials. We also examined the effects of the treatments on mortality, hospitalization, functional status, and biomarker levels to further investigate the interplay between ejection fraction and HF.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.905
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.064
GPT teacher head0.358
Teacher spread0.295 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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