Peripheral Manifestations in Spondyloarthritis and their Effect: An Ancillary Analysis of the ASAS-COMOSPA Study
Bibliographic record
Abstract
OBJECTIVE: To determine the factors associated with the presence of peripheral manifestations in patients with spondyloarthritis (SpA) from the Assessment in SpondyloArthritis international Society (ASAS)-COMOSPA study, and to evaluate the effect of these symptoms on treatment and patient-reported outcomes (PRO). METHODS: All patients from the ASAS-COMOSPA study were included. All patients had an SpA diagnosis according to the rheumatologist. Patients and disease characteristics associated with the presence of these peripheral manifestations (peripheral arthritis, peripheral enthesitis, or dactylitis) were analyzed by univariate and multivariate logistic regression. Patients who reported peripheral manifestations were divided into 3 categories: current, history, and no history. The effect of peripheral involvement on PRO was evaluated through the use of 1-factor ANOVA. RESULTS: Out of the 3984 patients included in ASAS-COMOSPA, 2562 (64.3%) reported at least 1 peripheral manifestation, with a prevalence of 51.5%, 37.8%, and 15.6% for peripheral arthritis, peripheral enthesitis, and dactylitis, respectively. Being from South America, having a history of uveitis, having a current case or history of psoriasis, and the absence of HLA-B27 were associated with higher prevalence of peripheral manifestations. Patients with peripheral involvement showed greater use of drugs, and those with "current" peripheral manifestations showed higher levels in all PRO, in contrast to those with past or no history. CONCLUSION: Peripheral manifestations appear in 64% of patients with SpA. Psoriasis and the absence of HLA-B27 are associated with the development of peripheral symptoms. The presence of any peripheral symptom at the time of the visit was associated with higher scores in all PRO.
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 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".