Central Obesity in Axial Spondyloarthritis: The Missing Link to Understanding Worse Outcomes in Women?
Bibliographic record
Abstract
Objective. To determine (1) the prevalence of central obesity in axial spondyloarthritis (axSpA) and its effect on disease-related outcomes and (2) how this differs between sexes. Methods. Data were extracted from the Ankylosing Spondylitis Registry of Ireland. Patients with physical measurements for the calculation of anthropometric measures were included. BMI and waist-to-hip ratio (WHR) were used to compare classifications of obesity. Comparison analyses based on sex and central obesity were carried out. Multivariate analysis examined the effects of these factors on the following patient-reported outcomes: the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), the Ankylosing Spondylitis Quality of Life (ASQoL) questionnaire, and the Health Assessment Questionnaire (HAQ). Results. In total, 753 patients were included in the analysis. Of these patients, 29.6% (n = 223) were classified as obese based on their BMI, and 41.3% (n = 311) were classified as centrally obese according to the WHR. The prevalence of central obesity was significantly higher among women with axSpA compared to men (71.6% vs 29.9%, P < 0.01). Central obesity had a clear effect on patient outcomes, regardless of sex. Presence of central obesity was associated with significantly worse BASFI scores (P < 0.01), HAQ scores (P < 0.01), and ASQoL questionnaire scores (P = 0.01), with a nonsignificant trend toward worse BASDAI scores (P = 0.07). Conclusion. There was a high prevalence of central obesity as assessed by the WHR in axSpA, most notably among women with axSpA. This modifiable comorbidity was significantly associated with worse quality of life, greater impairment of functional ability, and a trend toward worse disease activity. Regular use of the WHR to screen for central obesity as part of an axSpA assessment would provide an opportunity for prompt identification and intervention for at-risk patients.
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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 | 0.003 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".