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Record W4414933724 · doi:10.31579/2692-9759/164

Giant Vegetation of Mitral Valve

2025· article· en· W4414933724 on OpenAlexaboutno aff
Ramachandran Muthiah

Bibliographic record

VenueCardiology Research and Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsInfective endocarditisMitral valveVegetation (pathology)Mitral regurgitationEndocarditisHeart diseaseIncidence (geometry)

Abstract

fetched live from OpenAlex

Infective endocarditis (IE) is the infection of inner endothelial layer of the heart including the heart valves and it may present as rapidly progressive or manifest itself as subacute or chronic disease. The epidemiology of infective endocarditis has been changed over the past few decades and the incidence of IE in children in United States and Canada is 1 in 1,250 pediatric hospital admissions in the early 1980s. Atleast 70% of infective endocarditis in children occurs with congenital heart disease whereas rheumatic heart disease in southern states of India and the degenerative mitral valve disease (myxomatous, mitral valve prolapse) in the western countries are the most underlying predisposing conditions to infective endocarditis in adolescents. The characteristic lesion of infective endocarditis is ‘vegetation’ and a‘large’ vegetation > 10 mm in size has been reported with an incidence 15.9-62.5% of patients. The significance of vegetation size has been a subject of discussion for many years to predict the embolic episodes. Background of this case study illustrated the varying size and shape of giant vegetation attached to the anterior leaflet of mitral valve in an underlying rheumatic mitral valvulitis and its consequence of valve damage such as chordal rupture, flail leaflet and mitral regurgitation with a description of anatomic features and echocardiographic manifestations in a 10-year old female child.

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 score0.148
Threshold uncertainty score0.160

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 head0.040
GPT teacher head0.394
Teacher spread0.354 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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