Tumor necrosis factor inhibitor therapy in ankylosing spondylitis
Bibliographic record
Abstract
Ankylosing spondylitis is associated with back pain and fatigue and impacts mobility but can be treated with tumor necrosis factor inhibitors (TNFi). The differential effects of TNFi treatment on multiple symptoms and the brain is not well delineated. Thus, we conducted a 2-part study. In study 1, we conducted a retrospective chart review in 129 ankylosing spondylitis patients to assess TNFi effects on pain, fatigue, motor function, mobility, and quality of life (QoL). After at least 10 weeks of TNFi treatment, patients had clinically significant improvements (>30%) in pain (including neuropathic pain), most disease and QoL factors, and normalized sensory detection thresholds. However, residual fatigue (mean = 5.3) was prominent. Although 60% of patients had significant relief of pain, only 22% of patients had significant relief of both pain and fatigue. Therefore, the preferential TNFi treatment effect on pain compared with fatigue could contribute to suboptimal effects on QoL. Part 2 was a prospective study in 14 patients to identify TNFi treatment effects on pain, fatigue, sensory and psychological factors, and brain cortical thickness based on 3T magnetic resonance imaging. Centrally, TNFi was associated with statistically significant cortical thinning of motor, premotor, and posterior parietal regions. Pain intensity reduction was associated with cortical thinning of the secondary somatosensory cortex, and pain unpleasantness reduction was associated with the cortical thinning of motor areas. In contrast, fatigue reduction correlated with cortical thinning of the insula, primary sensory cortex/inferior parietal sulcus, and superior temporal polysensory areas. This indicates that TNFi treatment produces changes in brain areas implicated in sensory, motor, affective, and cognitive functions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".