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Record W2611746389 · doi:10.3899/jrheum.170061

Poor Predictive Value of Isolated Adventitial and Periadventitial Infiltrates in Temporal Artery Biopsies for Diagnosis of Giant Cell Arteritis

2017· article· en· W2611746389 on OpenAlexvenueno aff
Claire Le Pendu, Véronique Meignin, Solange Gonzalez‐Chiappe, A. Hij, Françoise Galateau-Sallé, Alfred Mahr

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsnot available
Fundersnot available
KeywordsGiant cell arteritisVasa vasorumMedicineAdventitiaPredictive valueArteritisVasculitisGold standard (test)Temporal arteryPathologyAortitisMedical diagnosisPolymyalgia rheumaticaRadiologyCardiologyInternal medicineAortaDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: We investigated the diagnostic value of inflammation limited to the adventitia (ILA), and isolated vasa vasorum or small-vessel vasculitis (VVV, SVV) in temporal artery biopsies (TAB) for giant cell arteritis (GCA). METHODS: Two pathologists reviewed consecutive first TAB. Using the clinical diagnoses as the gold standard, positive predictive values (PPV) were calculated. RESULTS: Among the 75 patients without classic TAB features of GCA, 8 had GCA diagnoses. The PPV of ILA, VVV, and SVV seen by either or both pathologists were 17%, 0%, and 7%, and 17%, 0%, and 10%, respectively. CONCLUSION: (Peri)adventitial infiltrates in TAB poorly predict GCA.

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)0.002
metaresearch head score (Gemma)0.019
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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

Citations26
Published2017
Admission routes1
Has abstractyes

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