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Record W4367047896 · doi:10.1002/ejhf.2848

Natriuretic Peptides: Role in the Diagnosis and Management of Heart Failure: A Scientific Statement from the Heart Failure Association of the European Society of Cardiology, Heart Failure Society of America and Japanese Heart Failure Society

2023· article· en· W4367047896 on OpenAlexaff
Hiroyuki Tsutsui, Nancy M. Albert, Andrew J.S. Coats, Stefan D. Anker, Antoni Bayés‐Genís, Javed Butler, Ovidiu Chioncel, Christopher R. deFilippi, Mark H. Drazner, G. Michael Felker, Gerasimos Filippatos, Mona Fiuzat, Tomomi Ide, James L. Januzzi, Koichiro Kinugawa, Koichiro Kuwahara, Yuya Matsue, Robert J. Mentz, Marco Metra, Ambarish Pandey, Giuseppe Rosano, Yoshihiko Saito, Yasushi Sakata, Naoki Sato, Petar Seferović, John R. Teerlink, Kazuhiro Yamamoto, Michihiro Yoshimura

Bibliographic record

VenueEuropean Journal of Heart Failure · 2023
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsHeart failureMedicineNesiritideNatriuretic peptideInternal medicineManagement of heart failureCardiologyIntensive care medicineBrain natriuretic peptideNeprilysin

Abstract

fetched live from OpenAlex

Natriuretic peptides, brain (B-type) natriuretic peptide (BNP) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) are globally and most often used for the diagnosis of heart failure (HF). In addition, they can have an important complementary role in the risk stratification of its prognosis. Since the development of angiotensin receptor-neprilysin inhibitors (ARNIs), the use of natriuretic peptides as therapeutic agents has grown in importance. The present document is the result of the Trilateral Cooperation Project among the Heart Failure Association of the European Society of Cardiology, the Heart Failure Society of America and the Japanese Heart Failure Society. It represents an expert consensus that aims to provide a comprehensive, up-to-date perspective on natriuretic peptides in the diagnosis and management of HF, with a focus on the following main issues: (1) history and basic research: discovery, production and cardiovascular protection; (2) diagnostic and prognostic biomarkers: acute HF, chronic HF, inclusion/endpoint in clinical trials, and natriuretic peptide-guided therapy; (3) therapeutic use: nesiritide (BNP), carperitide (ANP) and ARNIs; and (4) gaps in knowledge and future directions.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.252
Teacher spread0.235 · 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
GenreEmpirical

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

Citations142
Published2023
Admission routes1
Has abstractyes

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