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Record W2324667821 · doi:10.3899/jrheum.120238

Entheseal Power Doppler Ultrasonography: A Comparison of Psoriatic Arthritis and Fibromyalgia

2012· article· en· W2324667821 on OpenAlexvenueno aff
Antonio Marchesoni, Orazio De Lucia, L. Rotunno, Gabriele De Marco, M. Manara

Bibliographic record

VenueJournal of Rheumatology Supplement · 2012
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsoriatic arthritisFibromyalgiaPower dopplerUltrasonographyDoppler effectInternal medicineDermatologyArthritisRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the power Doppler ultrasonography (PDUS) pictures of peripheral entheses in patients with psoriatic arthritis (PsA) and fibromyalgia (FM). METHODS: Thirty patients with PsA and 30 with FM participating in a study aimed at identifying the clinical features that distinguish the 2 conditions underwent the PDUS assessment of 14 major peripheral entheses. All of the detected entheseal changes were recorded and scored, and the data were statistically analyzed by means of univariate analysis and receiver-operating characteristic curves. RESULTS: Four hundred twenty entheseal sites were assessed in each group of patients. At least 1 lesion was detected in each of the patients with PsA and in 80% of the patients with FM (p = 0.01), but inflammatory changes were present in respectively 70% and 23% (p = 0.001). A cutoff point of ≥ 3 involved sites had the greatest discriminating power in the patients with PsA, who were the only patients with bony erosions. PDUS signs of plantar fascia enthesopathy and Achilles tendon inflammation were highly specific of PsA. CONCLUSION: PDUS assessment of the peripheral entheses distinguishes patients with PsA and patients with FM in terms of the number and distribution of the involved sites, and the presence of inflammatory changes.

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 score0.068
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.016
GPT teacher head0.302
Teacher spread0.286 · 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

Citations51
Published2012
Admission routes1
Has abstractyes

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