ASDAS is associated with both the extent and intensity of DW-MRI spinal inflammation in active axial spondyloarthritis
Bibliographic record
Abstract
Objective: To investigate the relationship between Ankylosing Spondylitis Disease Activity Score (ASDAS) and intensity of spinal inflammation measured by apparent diffusion coefficient (ADC) in MRI in participants with active axial spondyloarthritis (SpA). Methods: Participants with axial SpA and back pain were recruited. Clinical, demographic, biochemical and imaging data were collected. ASDAS was calculated based on C reactive protein (CRP) and erythrocyte sedimentation rate (ESR). Inflammatory lesions were identified in short tau inversion recovery images and the corresponding ADC maps to determine the maximum apparent diffusion coefficient (ADCmax), normalised maximum ADC, mean apparent diffusion coefficient (ADCmean) and normalised mean ADC by two independent readers. Spondyloarthritis Research Consortium of Canada (SPARCC) spine and sacroiliac (SI) joint MRI indexes were determined. Univariate and multivariate linear regression models were used to determine the associations between of ASDAS with ADC values, SPARCC spine and SI MRI scores. Results: Eighty-two participants had identifiable ADC lesions. Multivariate analyses using ADCmax and SPARCC spine MRI as independent variables showed associations with ASDAS-CRP (ADCmax: B=0.27, p=0.02; SPARCC: B=0.32, p=0.01) and ASDAS-ESR (ADCmax: B=0.24, p=0.03; SPARCC: B=0.36, p<0.01); using ADCmean and SPARCC spine MRI as independent variables also showed an association with ASDAS-ESR (ADCmean: B=0.22, p=0.05; SPARCC: B=0.36, p<0.01) and a tendency to associate with ASDAS-CRP (ADCmean: B=0.21, p=0.07; SPARCC: B=0.34, p<0.01). Conclusion: ASDAS is associated with both the extent and the intensity of spinal inflammation in patients with detectable inflammatory lesions. Our results showed that ASDAS is an objective disease assessment tool. Trial registration number: HKUCTR-2087.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".