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Record W4378471999 · doi:10.1016/j.cjco.2023.05.008

Heart Failure Management in 2023: A Pharmacotherapy- and Lifestyle-Focused Comparison of Current International Guidelines

2023· review· en· W4378471999 on OpenAlexaffabout
Blair J. MacDonald, Sean Virani, Shelley Zieroth, Ricky D. Turgeon

Bibliographic record

VenueCJC Open · 2023
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of ManitobaUniversity of British Columbia
Fundersnot available
KeywordsGuidelineEjection fractionHeart failureMedicineCanadian Cardiovascular SocietyPharmacotherapyIntensive care medicineInternal medicineCardiologyPathology

Abstract

fetched live from OpenAlex

This review examines the pharmacotherapy and lifestyle recommendations of the most recent iterations of the Canadian Cardiovascular Society (CCS) / Canadian Heart Failure Society (CHFS), the European Society of Cardiology (ESC), and the American Heart Association (AHA) / American College of Cardiology (ACC) / Heart Failure Society of America (HFSA) heart failure (HF) guidelines, which all have been updated in response to therapeutic developments across the spectrum of left ventricular ejection fraction. Identified areas of unanimity across these guidelines include the following: recommending quadruple therapy for patients with HF with reduced ejection fraction (HFrEF; although no guideline proposed an ideal sequence of initiation); intravenous iron administration for patients with HFrEF and iron deficiency; and sodium restriction for patients with HF. Recent evidence regarding the harms of HFrEF medication withdrawal in patients with HF with improved ejection fraction has prompted subsequent guidelines to recommend against withdrawal. Due to the lower quality of evidence, there are disagreements regarding management of HF with preserved ejection fraction and uncertainty regarding management of HF with mildly reduced ejection fraction. Practical guidance is provided to clinicians navigating these challenging areas. In addition to these clinically focused comparisons, we describe opportunities for guideline improvement and harmonization. Specifically, these include opportunities regarding HFrEF sequencing, the need for timely updates, shared decision-making, Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework adoption, and the creation of recommendations where high-quality evidence is lacking. Although these guidelines have broad agreement, key areas of controversy remain that may be addressed by emerging evidence and changes in guideline methodology.

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)0.019
metaresearch head score (Gemma)0.078
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 score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.078
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.008
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.231
GPT teacher head0.515
Teacher spread0.284 · 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

Citations21
Published2023
Admission routes2
Has abstractyes

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