Clinical peripheral enthesitis in the DESIR prospective longitudinal axial spondyloarthritis cohort.
Bibliographic record
Abstract
OBJECTIVES: We aimed to describe the prevalence and characteristics of peripheral enthesitis in recent onset axial spondyloarthritis, estimate the incidence of peripheral enthesitis over time, and determine the factors associated with the presence of peripheral enthesitis. METHODS: 708 patients with recent onset axial spondyloarthritis were enrolled in the DESIR cohort ( prospective multi-centre, longitudinal). Data regarding the patients and spondyloarthritis characteristics at baseline with a specific focus on enthesitis and occurrence of peripheral enthesitis were collected during the five years of follow-up. RESULTS: At inclusion, 395 patients (55.8%) reported peripheral enthesitis. The locations were mainly the plantar fascia (53.7%) and the Achilles tendon (38.5%). During the 5-year follow-up period, 109 additional patients developed peripheral enthesitis resulting in an estimated (Kaplan-Meier method) percentage of 71% (95% CI: 68-75). Variables associated with peripheral enthesitis in the univariate analysis were: older age, male gender, absence of HLA B27, MRI sacroiliitis and fulfilled Modified NY criteria, presence of anterior chest wall pain, peripheral arthritis, dactylitis, psoriasis, high BASDAI, BASFI, mean score ASAS-and the use of NSAIDs. Only the history of anterior chest wall pain and of peripheral arthritis were retained in the multivariate analysis (odds ratio (OR)=1.6 [95% confidence interval [1.1-2.3], and OR=2.1 [1.4-3.0], respectively). CONCLUSIONS: This study highlights the high prevalence of peripheral enthesitis in recent onset axial spondyloarthritis, and suggests that in combination with peripheral arthritis, enthesitis might have an impact on the burden of the disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".