Differences in spinal structural lesions between patients with early axSpA and non-axSpA chronic back pain: 2-year SPACE cohort results
Bibliographic record
Abstract
Objectives To compare spinal structural lesions on radiography and magnetic resonance imaging (MRI) over 2 years, between patients with early axial spondyloarthritis (axSpA) and non-axSpA chronic back pain. Methods Patients from the SPACE cohort with available radiography or MRI at both baseline and 2years were included. Spinal lesions on radiography were assessed by the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS), corner MRI lesions by the modified Canada–Denmark scoring system. Baseline spinal structural lesions and 2-year changes were compared between axSpA and non-axSpA. Generalized estimating equations were used to assess the change over 2 years, adjusting for age, sex, non-steroidal anti-inflammatory drug use and diagnosis. Results Radiography data from 318 patients (67% axSpA), MRI data from 351 patients (69% axSpA) were included. At baseline, the mean (SD) mSASSS was 0.6 (1.1) for both axSpA and non-axSpA. Over 2 years, mSASSS progression was minimal (0.01 units/year) in both groups. On MRI, axSpA patients had a mean of 1.4 (2.9) total structural lesions compared with 0.7 (2) in non-axSpA at baseline (<em>P = </em>0.12). Significant 2-year increase in structural lesions [0.5 (1.8)] was mainly due to fat lesions [0.5 (1.6)] in axSpA. On MRI, fat lesions changed at a rate of 0.16 units/year in axSpA (<em>P = </em>0.002) and −0.02 units/year in non-axSpA (<em>P = </em>0.70). Conclusion Over 2 years, spinal structural damage typical for axSpA progressed minimally on radiography in axSpA and non-axSpA. On MRI, axSpA showed a significant increase in fat lesions, while non-axSpA had no progression. Fat lesions may be important to assess spinal changes from early disease onwards.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".