Multimorbidity in Axial Spondyloarthropathy and Its Association with Disease Outcomes: Results from the Ankylosing Spondylitis Registry of Ireland Cohort
Bibliographic record
Abstract
OBJECTIVE: Multimorbidity, the coexistence of 2 or more conditions in an individual, is associated with morbidity and mortality in the general population. This study aims to describe the prevalence of multimorbidity in axial spondyloarthropathy (axSpA) and assess its association with disease outcome measures. METHODS: This cross-sectional study was conducted within the Ankylosing Spondylitis Registry of Ireland (ASRI) cohort. Structured standardized assessment was performed. Multimorbidity was considered as the presence of at least 1 physician-diagnosed chronic condition (excluding extraarticular manifestations) in addition to axSpA. Validated outcome measures were collected: Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath AS Functional Index (BASFI), Health Assessment Questionnaire (HAQ), AS Quality of Life (ASQoL), and Bath AS Metrology Index (BASMI). Adjusted multiple regression was performed to investigate the association between multimorbidity and disease outcomes. RESULTS: A total of 734 patients from 12 centers were included: 77% male, mean (SD) age 45 (12) years. Of the cohort, 55% (n = 403) were multimorbid. Multimorbid patients were significantly (p < 0.01) older than axSpA-only patients [50 (12) vs 40 (11) yrs]. Obesity was the most prevalent chronic condition, affecting 27%. Multimorbid patients had more severe disease than patients with axSpA only. After adjusting for confounders, multimorbidity was associated with higher BASDAI (ß 0.7, 95% CI 0.34-1.05), BASMI (ß 0.45, 95% CI 0.09-0.80), BASFI (ß 0.5, 95% CI 0.23-0.78), HAQ (ß 0.07, 95% CI 0.00-0.13), and ASQoL (ß 0.87, 95% CI 0.28-1.46). CONCLUSION: Multimorbidity is prevalent in axSpA and is associated with more severe disease.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".