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Record W4411348457 · doi:10.1093/eurheartj/ehaf322

Right heart catheterization in heart failure: indications, interpretation, and pitfalls

2025· article· en· W4411348457 on OpenAlexaff
Katarina Zeder, Susanna Mak, Nazzareno Galiè, Stephan Rosenkranz, Bradley A. Maron

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineCardiogenic shockHeart failureHemodynamicsHeart transplantationCardiologyIntensive care medicineInternal medicineRight heart catheterizationShock (circulatory)Myocardial infarction

Abstract

fetched live from OpenAlex

Right heart catheterization (RHC) plays a pivotal role across the spectrum of heart failure, from ambulatory patients to those in cardiogenic shock or under consideration for left ventricular assist device (LVAD) therapy and heart transplantation. Hemodynamic data are critical for early recognition of clinical deterioration, prognostication, and guiding treatment decisions. This state-of-the-art review provides a practical guide to hemodynamic assessment, troubleshooting, and interpretation of hemodynamic variables assessed with RHC for clinicians treating patients with heart failure in the acute setting, including acute heart failure and cardiogenic shock as well as chronic heart failure and advanced disease states that may warrant LVAD or heart transplantation. A special focus is set on contextualizing hemodynamic variables within the clinical presentation to avoid diagnostic misclassification. In addition, opportunities for future research, including novel parameters as well as forward-thinking non-invasive technologies to inform hemodynamics, are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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

Citations8
Published2025
Admission routes1
Has abstractyes

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