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Functional Mitral Regurgitation and Heart Failure With Preserved Ejection Fraction: Clinical Implications and Management

2024· article· en· W4393087527 on OpenAlexaff
Mauro Riccardi, Maja Čikeš, Marianna Adamo, Matteo Pagnesi, Carlo Lombardi, Scott D. Solomon, Marco Metra, Riccardo M. Inciardi

Bibliographic record

VenueJournal of Cardiac Failure · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineCardiologyInternal medicineHeart failureMitral regurgitationHeart failure with preserved ejection fractionContext (archaeology)VentricleEjection fractionDiastoleFunctional mitral regurgitationRegurgitation (circulation)Blood pressure

Abstract

fetched live from OpenAlex

Heart failure with preserved ejection fraction (HFpEF) is highly prevalent and associated with worse cardiovascular outcomes. The pathophysiology of HFpEF mostly relies on the development of elevated left ventricle filling pressure, diastolic dysfunction, and atrial dilatation and impairment. This dynamic process may eventually lead to the development of functional mitral regurgitation (MR), characterized by mitral annular dilatation and consequent leaflet remodeling, in the context of preserved left ventricular ejection fraction. These observations highlight the possible common pathophysiology of MR and HFpEF. However, less is known about the prevalence and the clinical value of MR in the context of HFpEF. This review aims to provide an overview of the association and interplay between functional MR and HFpEF, discuss the underlying mechanisms that are common to these diseases, and summarize potential targeted pharmacological treatments.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.342
Teacher spread0.322 · 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 designObservational
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

Citations19
Published2024
Admission routes1
Has abstractyes

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