The relationship between sacroiliac joint MRI scores and central sensitization in axial spondyloarthritis: A cross-sectional study
Bibliographic record
Abstract
ABSTRACT Objective: To investigate the relationship between sacroiliac joint (SIJ) involvement and central sensitization (CS) in patients with axial spondyloarthritis (axSpA). Patients and Methods: Twenty-four patients with axSpA were included in this study. CS was investigated via pressure pain threshold (PPT), temporal summation (TS), conditional pain modulation (CPM), and the central sensitization inventory (CSI). Sacroiliac joint involvement was assessed using the magnetic resonance imaging (MRI)-based Canadian Spondyloarthritis Research Consortium (SPARCC) scoring system. CS-related parameters and SPARCC score correlations were analyzed. Results: The median (IQR) sacroiliac PPT score for the right SIJ was calculated as 17.47 (4.43) and 17.67 (4.57) for the left SIJ. In the TS measurement, the right SIJ TS median (IQR) value was calculated as 4.0 (3.5) and 4.0 (2.75) for the left side. The median (IQR) value was 149.67 (107.5) for CPM and 45.0 (27.75) for CSI. The median (IQR) sacroiliac inflammation score was calculated as 3.0 (8.75), and the median (IQR) structural score was calculated as 7.0 (11.5). No correlation was found between SPARCC scores and PPT, TS, CPM, and CSI values. Conclusion: In axSpA patients, there was no association observed between pain sensitivity measures and sacroiliac involvement. Further comprehensive studies are required, taking into account the complex nature of CS.
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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 | 0.000 |
| 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) | 0.002 | 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".