Performance of the ASAS Health Index for the Evaluation of Spondyloarthritis in Daily Practice
Bibliographic record
Abstract
OBJECTIVE: The Assessment of SpondyloArthritis international Society Health Index (ASAS HI) is a tool designed to assess disease impact in spondyloarthritis (SpA), but its clinical performance is barely known. We aimed to test the clinimetric properties of ASAS HI in a real clinical setting. METHODS: This cross-sectional study included 111 consecutive patients with SpA. The measurement properties of ASAS HI were tested against conventional assessment measures. Convergent validity was assessed by Spearman rho correlations, while discriminative validity was analyzed through receiver-operating characteristic (ROC) curves. A multivariate regression analysis was designed to identify ASAS HI items associated with active disease. RESULTS: The average ASAS HI was 5.4 ± 3.8 (interquartile range 3-8). ASAS HI showed high convergent validity against other SpA measures (rho ≥ 0.70, p < 0.0005). The optimal criteria for detecting high/very high disease activity Ankylosing Spondylitis Disease Activity Score (ASDAS) categories was an ASAS HI score > 6, area under the ROC curve 0.86 (95% CI 0.78-0.92), positive likelihood ratio 7.3 (95% CI 3.1-17.1), p < 0.0001. The ASAS HI items significantly associated with Bath Ankylosing Spondylitis Disease Activity Index active disease were "I often get frustrated" (OR 9.2, 95% CI 1.2-69.4, p = 0.032), and "I sleep badly at night" (OR 7.7, 95% CI 1.4-41.6, p = 0.018). As for ASDAS, it was "pain sometimes disrupts my normal activities" (OR 8.7, 95% CI 1.7-45.2, p = 0.010). CONCLUSION: The ASAS HI is a useful and simple instrument for its application in daily practice. Given its good clinimetric properties, it could be used as an additional instrument to evaluate SpA.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".