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Record W2069781070 · doi:10.1093/ehjci/jet260

A tale of two ventricles: ventricular-ventricular interactions and LV dysfunction after surgical repair of Tetralogy of Fallot

2013· editorial· en· W2069781070 on OpenAlexaff
Andréea Dragulescu, Mark K. Friedberg

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2013
Typeeditorial
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsTetralogy of FallotCardiologyMedicineInternal medicineEjection fractionPopulationExercise intoleranceHeart failureHeart disease

Abstract

fetched live from OpenAlex

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect with good long-term survival after surgical correction.1 Nonetheless, patients suffer from significant morbidity and mortality including exercise intolerance, arrhythmias, and sudden death, presenting an important healthcare burden.2 To date, most clinical and research emphasis in TOF has been placed on right ventricular (RV) pathology. Indeed, progressive RV dilatation and dysfunction are common and are well-established risk factors for adverse clinical outcomes.3,4 In contrast, relatively little attention has been paid to left ventricular (LV) dysfunction and to adverse ventricular–ventricular interactions in this population. However, recent studies show that LV dysfunction is not only common in adults after TOF repair, but is linked to adverse clinical outcomes.5–7 The mechanisms driving LV dysfunction in this population appear to be related, at least in part, to RV dysfunction.8 RV and LV ejection fraction (EF) are closely related after TOF repair, and myocardial deformation studies demonstrate impairment in multiple components of both RV …

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.004
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)0.0000.000

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 head0.011
GPT teacher head0.270
Teacher spread0.259 · 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
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

Citations12
Published2013
Admission routes1
Has abstractyes

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