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Record W2101884846 · doi:10.3899/jrheum.080792

Rate of Discordant Findings in Bilateral Temporal Artery Biopsy to Diagnose Giant Cell Arteritis

2009· article· en· W2101884846 on OpenAlexvenueno aff
Gabriel S. Breuer, Gideon Nesher, Ронит Нешер

Bibliographic record

VenueThe Journal of Rheumatology · 2009
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsnot available
Fundersnot available
KeywordsGiant cell arteritisMedicineBiopsyTemporal arteryArteritisRadiologyPathologyVasculitisDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine to what extent performing simultaneous bilateral temporal artery biopsies might increase the diagnostic sensitivity in giant cell arteritis (GCA). METHODS: In total 173 consecutive pathology reports of temporal artery biopsies were reviewed for histological findings by a single pathologist. The rate of discordance of biopsy results was calculated in patients with GCA. RESULTS: Biopsies were performed bilaterally and simultaneously in 132 cases; 51 had positive results. In 38 the biopsy was positive on both sides (concordant results), while in 13 patients only one side was positive (discordant results), reaching a discordance rate of 13/51=0.255. Therefore 12.7% of the patients (one-half of the discordance rate) could have been misdiagnosed as biopsy-negative had a biopsy been done only unilaterally in those 51 cases. CONCLUSION: These data suggest that performing bilateral temporal artery biopsies increases the diagnostic sensitivity of the procedure by up to 12.7%, compared to unilateral biopsies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.055
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations77
Published2009
Admission routes1
Has abstractyes

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