Male spondyloarthritis patients and those with longer disease duration have less severe disc degeneration: propensity score-matched comparison
Bibliographic record
Abstract
Abstract Objective Using whole spine sagittal T2 MRI, we aimed to compare the severity and prevalence of disc degeneration (DD) in axial SpA patients vs the general population and to determine any association between spinal inflammation, structural changes, mobility and DD among SpA patients. Methods Two prospectively collected cohorts of SpA patients (n = 411) and the general population (n = 2007) were recruited. Eventually, 967 participants from the populational cohort and 304 participants from the SpA cohort were analysed. Two hundred and nineteen matched pairs were generated by propensity score matching. Imaging parameters, including Pfirrmann grading, disc herniation, high-intensity zone, Schmorl’s node, Modic change and anterior marrow change were studied and compared from C2/3 to L5/S1. DD was defined as Pfirrmann grade 4 or 5. Demographic factors, including age, sex and BMI, were collected. Multivariable linear regression was used to determine the association between spinal inflammation [Spondyloarthritis Research Consortium of Canada (SPARCC) spine MRI index], structural changes [modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS)] and mobility (BASMI) with lumbar Pfirrmann score. Results SpA patients had lower prevalence of DD (P < 0.001). The disease stage-stratified regression model showed that SPARCC spinal MRI index was associated with higher lumbar Pfirrmann scores in early disease (β = 0.196, P = 0.044), whereas mSASSS was associated with lower lumbar Pfirrmann scores in later disease (β = −0.138, P = 0.038). Males had higher mSASSS (P < 0.001) and lower odds of whole spine DD (odds ratio = 0.622, P = 0.028). Conclusion SpA patients had lower DD severity than the general population. Males had higher mSASSSs, and increased mSASSS at later disease was associated with less severe DD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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 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".