The influence of alexithymia on disease activity and quality of life in patients with axial spondyloarthritis: A cross‐sectional study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the prevalence of alexithymia and its influence on disease activity, quality of life, and clinical outcomes in axial spondyloarthritis (axSpA) patients. PATIENTS AND METHODS: This cross-sectional study included 110 (59 men and 51 women) consecutive axSpA patients who agreed to participate at our rheumatology outpatient clinic. Patient demographics, pain, disease activity measures, functionality, quality of life, alexithymia, psychological status, neuropathic pain, and fibromyalgia were evaluated. Patients were divided into 2 groups (without vs with alexithymia) and compared. The risk factors for alexithymia were evaluated. RESULTS: , respectively. Most patients with alexithymia were women. Patients with alexithymia had significantly high scores for depression, anxiety, fibromyalgia, disease activity, enthesitis, worse quality of life, and poor functionality (all P < 0.05). Female gender (odds ratio [OR] = 22.359), patient global assessment (OR = 7.873), Bath Ankylosing Spondylitis Functional Index (OR = 1.864), and fibromyalgia symptom severity (OR = 1.303) were found to be independent risk factors for alexithymia. CONCLUSION: The present study results showed that about one-third of axSpA patients had alexithymia, and the patients with alexithymia had higher disease activity, worse quality of life, and worse functional status than those without alexithymia. Female gender, patient global assessment, functional status, and fibromyalgia symptom severity were found to be important contributing factors to alexithymia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".