Assessment of enthesitis in patients with psoriatic arthritis using clinical examination and ultrasound
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Enthesitis is a major feature of psoriatic arthritis. However, clinical assessment of enthesitis is known to lack accuracy and have poor interobserver reliability. OBJECTIVE: To determine effect of training on clinical assessment of enthesitis and to compare ultrasonography with clinical examination for the detection of entheseal abnormalities. METHODS: 20 rheumatologists performed repeated assessment of enthesitis in patients with established psoriatic arthritis before and after a 2-hour training session in standardised enthesitis count according to Leeds Enthesitis Index (LEI) and Spondyloarthritis Research Consortium of Canada Enthesitis Index (SPARCC). Moreover, 20 patients underwent clinical and ultrasonographic examination of entheses to evaluate consensus-based elementary lesions of enthesitis. RESULTS: Training significantly increased Intra-class Correlation Coefficient for LEI from 0.18 to 0.82 and for SPARCC from 0.38 to 0.67. Ultrasound examination showed high associations between hypoechogenicity and increased thickness of the entheses and clinical examination. There was no correlation between erosions and enthesophytes found by ultrasound and clinical assessments. CONCLUSION: Training in standardised enthesitis scoring systems significantly improved clinical assessments of enthesitis and should be performed before use in daily clinical practice. Ultrasound revealed more advanced stages of enthesitis, such as enthesophytes and erosions, which were not detected with clinical examination.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it