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Record W2906613041 · doi:10.1097/hco.0000000000000595

Right ventricular failure management

2018· review· en· W2906613041 on OpenAlexaff
Shahrukh N. Bakar, Sangyang Jia, S. J. Smith

Bibliographic record

VenueCurrent Opinion in Cardiology · 2018
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineInotropeHeart failureRight ventricular failureCardiologyIntensive care medicinePredictive valueVentricular functionInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Review recent advances in the diagnosis and management of right ventricular (RV) failure. RECENT FINDINGS: Temporary and durable device-based management of RV failure has emerging applications. SUMMARY: Research advances and clinical management in RV failure have been limited by a lack of consensus on a universal definition. Echocardiographic and cardiac MRI-based predictors of RV failure are imperfect. Combinations of hemodynamic and imaging variables may have better predictive value. Loading conditions and ventriculo-arterial coupling play important roles in RV function. The current treatment approach to RV failure includes a combination of inotropy and vasodilatation but lacks conclusive evidence. Emerging biochemical and molecular targets hold promise but have yet to be proven in human studies.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.109
GPT teacher head0.420
Teacher spread0.311 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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