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Record W4405086565 · doi:10.1002/ehf2.15105

Implementation of Guideline-Recommended Medical Therapy for Patients with Heart Failure in Europe

2024· review· en· W4405086565 on OpenAlexaff
Maurizio Volterrani, Petar Seferovic, Gianluigi Savarese, Ilaria Spoletini, Egidio Imbalzano, Antoni Bayés‐Genís, Ewa A. Jankowska, Michele Senni, Marco Metra, Ovidiu Chioncel, Andrew J.S. Coats, Giuseppe Rosano

Bibliographic record

VenueESC Heart Failure · 2024
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSurgical Specialties (Canada)
FundersMinistero della Salute
KeywordsGuidelineMedicineHeart failureIntensive care medicineDosingMedical therapyPharmacotherapyMEDLINEInternal medicinePathology

Abstract

fetched live from OpenAlex

Physicians' adherence to guideline-recommended heart failure (HF) treatment remains suboptimal, especially regarding the target doses. In particular, there is evidence that non-cardiologists are less compliant with HF guideline recommendations. This is likely to have a detrimental impact on patients' survival, readmissions and quality of life. Thus, the present document aims to address the reasons underlying low implementation and under-dosing of guideline-directed medical therapy in HF and to update a guidance for the initiation and rapid titration of HF drugs. In particular, aim of this document is to provide practical indications for drug implementation, to be applied not only by cardiologists but also by GPs and internal medicine doctors.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.378
Teacher spread0.347 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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