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Record W4398289251 · doi:10.1002/ejhf.3295

How to Tackle Therapeutic Inertia in Heart Failure with Reduced Ejection Fraction. A Scientific Statement of the Heart Failure Association of the ESC

2024· article· en· W4398289251 on OpenAlexaff
Gianluigi Savarese, Felix Lindberg, Antonio Cannatà, Ovidiu Chioncel, Davide Stolfo, Francesca Musella, Daniela Tomasoni, Magdy Abdelhamid, Debasish Banerjee, Antoni Bayés‐Genís, Emmanuelle Berthelot, Frieder Braunschweig, Andrew J.S. Coats, Nicolas Girerd, Ewa A. Jankowska, Loreena Hill, Mitja Lainščak, Yu. M. Lopatin, Lars H. Lund, Aldo P. Maggioni, Brenda Moura, Amina Rakisheva, Robin Ray, Petar Seferović, Hadi Skouri, Cristiana Vitale, Maurizio Volterrani, Marco Metra, Giuseppe Rosano

Bibliographic record

VenueEuropean Journal of Heart Failure · 2024
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsHealth Care FoundationSurgical Specialties (Canada)
FundersBiosense WebsterRespicardiaAbbott VascularStockholms Läns LandstingServierKarolinska InstitutetImpulse DynamicsVifor PharmaVetenskapsrådetMinistero della SalutePfizerLivaNovaBoston Scientific CorporationNovo NordiskTeva Pharmaceutical IndustriesCytokineticsSanofiAmgenAcceleronAstraZenecaEli Lilly and Company
KeywordsMedicineHeart failureGuidelineEjection fractionPsychological interventionClinical PracticeTelemedicineIntensive care medicinePhysical therapyCardiologyNursingHealth care

Abstract

fetched live from OpenAlex

Guideline-directed medical therapy (GDMT) in patients with heart failure and reduced ejection fraction (HFrEF) reduces morbidity and mortality, but its implementation is often poor in daily clinical practice. Barriers to implementation include clinical and organizational factors that might contribute to clinical inertia, i.e. avoidance/delay of recommended treatment initiation/optimization. The spectrum of strategies that might be applied to foster GDMT implementation is wide, and involves the organizational set-up of heart failure care pathways, tailored drug initiation/optimization strategies increasing the chance of successful implementation, digital tools/telehealth interventions, educational activities and strategies targeting patient/physician awareness, and use of quality registries. This scientific statement by the Heart Failure Association of the ESC provides an overview of the current state of GDMT implementation in HFrEF, clinical and organizational barriers to implementation, and aims at suggesting a comprehensive framework on how to overcome clinical inertia and ultimately improve implementation of GDMT in HFrEF based on up-to-date 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 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)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.253
Teacher spread0.239 · 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
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

Citations74
Published2024
Admission routes1
Has abstractyes

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