Understanding the drivers of BASDAI and back pain scores in psoriatic arthritis
Bibliographic record
Abstract
OBJECTIVES: The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is widely used to assess axial disease activity in psoriatic arthritis (PsA). However, 5 of its 6 questions reflect general disease activity rather than axial-specific symptoms. We aimed to evaluate the performance of BASDAI and its back pain subscore in assessing axial disease in PsA. METHODS: Patients with BASDAI scores were identified from a longitudinal PsA cohort initiated in 1978. Axial disease was defined radiographically. Trends in BASDAI and back pain scores were compared between patients with and without axial involvement. Associations of total BASDAI and back pain subscore with axial disease were assessed using univariable and multivariable linear mixed models in the entire cohort and stratified subgroups. RESULTS: Of 1059 patients, 449 (42.4%) had axial and 610 (57.6%) had peripheral disease only. The mean age was 44.4 years (SD 12.8), and 55.9% were male. No difference in the BASDAI and back pain trends was observed between the axial and peripheral disease groups. Axial involvement was not associated with total BASDAI scores (β = -0.14, 95% CI -0.05 to 0.33). However, it was associated with a small, yet significant increase in back pain subscore (0.30, 0.06-0.55). Both BASDAI and back pain scores were associated with active peripheral joints, enthesitis, dactylitis, age, Psoriasis Area and Severity Index, and inversely with male sex. These associations were consistent across axial and peripheral disease subgroups. CONCLUSIONS: BASDAI and its back pain subscore are influenced by peripheral musculoskeletal and skin disease activity in PsA, limiting their utility for assessing axial 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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".