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Record W2024234202 · doi:10.1097/aco.0b013e32835b8be2

Perioperative right ventricular dysfunction

2012· review· en· W2024234202 on OpenAlexaff
André Denault, François Haddad, Eric Jacobsohn, Alain Deschamps

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2012
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of ManitobaMontreal Heart InstituteCentre Hospitalier de l’Université de MontréalUniversité de Montréal
Fundersnot available
KeywordsMedicineCardiologyHemodynamicsModalitiesVentricular functionInternal medicinePerioperativeHeart failureRight ventricular failureIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To evaluate new information on the importance of right ventricular function, diagnosis and management in cardiac surgical patients. RECENT FINDINGS: There is growing evidence that right ventricular function is a key determinant in survival in cardiac surgery, particularly in patients with pulmonary hypertension. The diagnosis of this condition is helped by the use of specific hemodynamic parameters and echocardiography. In that regard, international consensus guidelines on the echocardiographic assessment of right ventricular function have been recently published. New monitoring modalities in cardiac surgery such as regional near-infrared spectroscopy can also assist management. Management of right ventricular failure will be influenced by the presence or absence of myocardial ischemia and left ventricular dysfunction. The differential diagnosis and management will be facilitated using a systematic approach. SUMMARY: The use of right ventricular pressure monitoring and the publications of guidelines for the echocardiographic assessment of right ventricular anatomy and function allow the early identification of right ventricular failure. The treatment success will be associated by optimization of the hemodynamic, echocardiographic and near-infrared spectroscopy parameters.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.149
GPT teacher head0.413
Teacher spread0.264 · 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 designOther design
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

Citations103
Published2012
Admission routes1
Has abstractyes

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