The Burden of Spine Structural Damage on Function in Patients With Axial Spondyloarthritis: Adaptation-Mediated Uncoupling?
Bibliographic record
Abstract
Objective To investigate the association between spinal damage and functional capacity in patients with axial spondyloarthritis (axSpA) and to compare the performance of 2 radiographic scores (modified Stoke Ankylosing Spondylitis Spine Score [mSASSS] and Combined Ankylosing Spondylitis Spine Score [CASSS]). Methods Radiographs from 101 patients with axSpA were scored for cervical facet joints (CFJ) and mSASSS for vertebral bodies. CASSS was calculated as the sum of both scores. Physical function was assessed by Bath Ankylosing Spondylitis Functional Index (BASFI); disease activity by Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Ankylosing Spondylitis Disease Activity Score (ASDAS); mobility by Bath Ankylosing Spondylitis Metrology Index (BASMI); and quality of life by Ankylosing Spondylitis Quality of Life (ASQOL). Univariate and multivariate analyses were performed to investigate the association between possible explanatory variables and outcomes. Results BASFI correlated strongly with ASQOL (Spearman ρ 0.66) and BASDAI (ρ 0.70), moderately with BASMI (ρ 0.46) and ASDAS (ρ 0.59), and weakly with mSASSS (ρ 0.29) and CASSS (ρ 0.28). A best-fit multivariate model for BASFI, adjusted for symptom duration, age, sex, and smoking status, included BASDAI (B0.76,P< 0.001), BASMI (B0.62,P< 0.001), and history of total hip arthroplasty (B1.22,P= 0.05). Radiographic scores were predictors of BASFI only when BASMI was removed from the model (mSASSS:B0.03,P= 0.01; CASSS:B0.02,P= 0.01). Conclusion Spinal damage was independently associated with physical function in axSpA, but to a lesser extent than disease activity and mobility. Moreover, incorporating CFJ assessment in the mSASSS did not improve the ability to predict function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".