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Record W4280595574 · doi:10.1002/ejhf.2542

Head‐to‐head comparison between recommendations by the <scp>ESC</scp> and <scp>ACC</scp> / <scp>AHA</scp> / <scp>HFSA</scp> heart failure guidelines

2022· review· en· W4280595574 on OpenAlexaff
Antoni Bayés‐Genís, Alberto Aimo, Marco Metra, Stefan D. Anker, Petar Seferović, Claudio Rapezzi, Vincenzo Castiglione, Julio Núñez, Michele Emdin, Giuseppe Rosano, Andrew J.S. Coats

Bibliographic record

VenueEuropean Journal of Heart Failure · 2022
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineHeart failureGuidelineEjection fractionInternal medicineCardiologyIntensive care medicinePathology

Abstract

fetched live from OpenAlex

Recommendations represent the core messages of guidelines, and are particularly important when the body of scientific evidence is rapidly growing, as in the case of heart failure (HF). The main messages from two latest major HF guidelines, endorsed by the European Society of Cardiology (ESC) and the American College of Cardiology/American Heart Association/Heart Failure Society of America (ACC/AHA/HFSA), are partially overlapping, starting from the four pillars of treatment for HF with reduced ejection fraction. Some notable differences exist, in part related to the timing of recent publications (most notably, the Universal Definition of HF paper and the EMPEROR-Preserved trial), and in part reflecting differing views of the natural history of HF (with a clear differentiation between stages A and B HF in the ACC/AHA/HFSA guidelines). Different approaches are proposed to specific issues such as risk stratification and implantable cardioverter defibrillator use for primary prevention in HFrEF patients with non-ischaemic aetiology. The ACC/AHA/HFSA guidelines put a greater emphasis on some issues that are particularly relevant to the US setting, such as the cost-effectiveness of therapies and the impact of health disparities on HF care. A comparison between guideline recommendations may give readers a deeper understanding of the ESC and ACC/AHA/HFSA guidelines, and help them apply sensible approaches to their own practice, wherever that may be in the world. A comparison may possibly also help further harmonization of recommendations between future guidelines, by identifying why some areas have led to conflicting recommendation, even when ostensibly reviewing the same published evidence.

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)0.053
metaresearch head score (Gemma)0.369
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.053
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.369
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0090.012
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0030.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0130.003

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 head0.094
GPT teacher head0.369
Teacher spread0.275 · 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 designSystematic review
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

Citations27
Published2022
Admission routes1
Has abstractyes

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