Comparing MRI and conventional radiography for the detection of structural changes indicative of axial spondyloarthritis in the ASAS cohort
Bibliographic record
Abstract
OBJECTIVES: To compare MRI and conventional radiography of SI joints for detection of structural lesions typical for axial spondyloarthritis (axSpA). METHODS: Adult patients from the Assessment of SpondyloArthritis international Society (ASAS) cohort with symptoms suggestive of axSpA and both SI joint MRI and radiographs available for central reading were included. Radiographs were evaluated by three readers according to the modified New York (mNY) criteria grading system. The presence of structural damage on radiographs was defined as fulfilment of the radiographic mNY criterion and, additionally, a lower threshold for sacroiliitis of at least grade 2 unilaterally. MRI scans were assessed for the presence of structural changes indicative of axSpA by seven readers. Diagnostic performance [sensitivity, specificity, positive and negative predictive values (PPV and NPV) and positive and negative likelihood ratios (LR+ and LR-)] of MRI and radiographs (vs rheumatologist's diagnosis of axSpA) were calculated. RESULTS: Overall, 183 patients were included and 135 (73.7%) were diagnosed with axSpA. Structural lesions indicative of axSpA on MRI had sensitivity 38.5%, specificity 91.7%, PPV 92.9%, NPV 34.6%, LR+ 4.62 and LR- 0.67. Sacroiliitis according to the mNY criteria had sensitivity 54.8%, specificity 70.8%, PPV 84.1%, NPV 35.8%, LR+ 1.88 and LR- 0.64. Radiographic sacroiliitis of at least grade 2 unilaterally had sensitivity 65.2%, specificity 50.0%, PPV 78.6%, NPV 33.8%, LR+ 1.30 and LR- 0.69. CONCLUSION: Structural lesions of the SI joint detected by MRI demonstrated better diagnostic performance and better interreader reliability compared with conventional radiography.
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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 | 0.003 | 0.009 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".