Male smokers with HLA-B27 positivity, SI joints inflammation have more radiological damages and higher prevalence of AS while females have higher BASDAI scores: observations from cluster analyses of a group of SpA patients
Bibliographic record
Abstract
Abstract Objectives To describe the clinical characteristics and the relations with disease activity, functional status, and syndesmophytes formation in patients with axial spondyloarthritis (AxSpA) by categorizing them into different groups. Methods One hundred and sixty three patients with AxSpA were recruited. Clinical and blood parameters were collected. Patients were asked to complete the self-assessment questionnaires, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and Bath Ankylosing Spondylitis Functional Index (BASFI). Spinal mobility was measured according to Bath Ankylosing Spondylitis Metrology Index (BASMI). Radiographs of cervical and lumbosacral spine were performed for modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). Radiological sacroiliitis was scored for ankylosing spondylitis (AS). Magnetic resonance imaging (MRI) of the sacroiliac (SI) joints was performed for spondyloarthritis research consortium of Canada (SPARCC) MRI inflammation score. Two-way cluster analyses were performed to determine the relationships between the parameters. Results Two cluster models were built using SPARCC scores of different scorers. Results were similar. The group of patients with highest mSASSS (20.33 vs 20.33) and prevalence radiological AS (85% vs 86%) were male patients (75% vs 75%), positive for HLA-B27 (70.0% vs 66.7%), smokers (87.5% vs 97.2%), and higher SPARCC SI joints score (5.32 vs 3.17). Higher BASDAI was observed among female sex. BASMI varies little but the group with highest BASMI (3.60 vs 3.62) also had highest mSASSS (20.33 vs 20.33). Conclusion Our data showed that male smokers with HLA-B27 positivity and SI joints inflammation have more radiological damage and higher prevalence of AS, consistent with known poor prognosis factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".