Reliability of Radiographic Scoring Methods in Axial Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Important differences exist between axial psoriatic arthritis (AxPsA) and ankylosing spondylitis (AS). The Bath Ankylosing Spondylitis Radiology Index (BASRI), the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS), and the Radiographic Ankylosing Spondylitis Spinal Score (RASSS) were developed to score AS, and the Psoriatic Arthritis Spondylitis Radiology Index (PASRI) to score AxPsA. We aimed to develop a computerized scoring application and compare the intra- and interrater reliability of these scoring systems in AS and AxPsA. METHODS: A computerized scoring application was developed to facilitate the scoring of radiographic features and calculate total scores for established scoring methods for AS and AxPsA. Digital spinal radiographs of 18 patients with AS and 40 patients with AxPsA were read in random order individually by 4 rheumatologists, data were entered into the application, and scores were obtained. The intraclass correlation coefficients (ICC) of the intra- and interrater reliability of scores for each method were then computed. RESULTS: In AS, the intra- and interrater ICC was 0.91 and 0.80 for sacroiliitis grade, 0.96 and 0.86 for BASRI-spine, 0.98 and 0.86 for mSASSS, 0.96 and 0.75 for RASSS, and 0.99 and 0.93 for PASRI, respectively. In AxPsA, the intra- and interrater ICC was 0.81 and 0.67 for sacroiliitis grade, 0.77 and 0.52 for BASRI-spine, 0.91 and 0.65 for mSASSS, 0.90 and 0.68 for RASSS, and 0.92 and 0.88 for PASRI, respectively. CONCLUSION: Available radiographic scoring systems perform well in AS and have moderate intra- and interrater reliability when applied to AxPsA. However, PASRI may be superior for assessing structural damage in AxPsA.
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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 | 0.031 | 0.096 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".