MétaCan
Menu
Back to cohort
Record W2002892149 · doi:10.2214/ajr.182.2.1820333

<b>High-Resolution Sonography of the Triangular Fibrocartilage:</b> Initial Experience and Correlation with MRI and Arthroscopic Findings

2004· article· en· W2002892149 on OpenAlexaff
Ciarán Keogh, Anthony Wong, Neil J. Wells, John E. Barbarie, P L Cooperberg

Bibliographic record

VenueAmerican Journal of Roentgenology · 2004
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineFibrocartilageArthroscopyTearsRadiologyHigh resolutionEndoscopyWrist arthroscopyNuclear medicineArticular cartilageSurgeryOsteoarthritisPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of our study was to compare the findings of high-resolution sonography of the triangular fibrocartilage with those of MRI and arthroscopy. SUBJECTS AND METHODS. Thirteen patients with clinically suspected triangular fibrocartilage tears prospectively underwent sonography, followed by MRI, of their wrists. Triangular fibrocartilage tears were classified as predominantly ulnar or predominantly radial. Only the surgeon was aware of the results of both studies, and eight patients subsequently underwent arthroscopy. The findings of the different techniques were compared. RESULTS: For the presence or absence of a tear, seven (87.5%) of eight sonographic examinations correlated with arthroscopy, and 11 (84.6%) of 13 sonographic examinations correlated with MRI. Sonography missed one small radial tear that was detected at arthroscopy and MRI, but sonography showed an ulnar tear in triangular fibrocartilage that appeared normal on MRI. CONCLUSION: High-resolution sonography shows good correlation with MRI and arthroscopy for the evaluation of triangular fibrocartilage tears. Sonography has the potential to be a rapid and cost-effective means of diagnosing tears of the triangular fibrocartilage, particularly those involving the ulnar aspect of the cartilage.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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

Citations32
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of RoentgenologySame topicOrthopedic Surgery and RehabilitationFrench-language works237,207