Predictors of response to intra-articular steroid injection in psoriatic arthritis
Bibliographic record
Abstract
OBJECTIVES: To assess the effectiveness of IA corticosteroid (IAS) injections in PsA and to determine the association between macrophage migration inhibition factor (MIF) gene polymorphism and response to IAS injections. METHODS: A cohort analysis of PsA patients who were followed prospectively was performed. Clinical response was defined as no tenderness or effusion in the injected joint at 3 months. Relapse was defined as re-occurrence of joint pain or effusion. MIF 173C > G genotyping (rs755622) was performed. RESULTS: Two hundred and twenty patients with 245 IAS injections were included in the study. The probability of responding at 3 months was 41.6%. Within 12 months, 25.5% of the joints relapsed. Clinical factors that were associated with response included duration of psoriasis [Odds ratio (OR) 1.03] and the use of MTX or anti-TNF agents at the time of injection (OR 2.68). Factors that were associated with relapse included injection into large joints (OR 4.58) and elevated sedimentation rate (OR 15.0), whereas absence of clinical and/or radiographic damage (OR 0.23) and duration of PsA (OR 0.92) reduced risk of relapse. MIF polymorphism was not associated with clinical response, but was associated with relapse (OR 3.2). On multivariate analysis including clinical covariates, the association between MIF polymorphism and relapse was lost. CONCLUSIONS: IAS injections are effective in PsA. MIF gene polymorphism is associated with relapse. However, this effect is explained by clinical variables that reflect disease activity, suggesting that MIF gene polymorphism influences inflammatory activity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".