Correlation between clinical disease activity and sacroiliac magnetic resonance imaging detection in axial spondyloarthropathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives: The study aimed to evaluate the correlation between the clinical disease activity of axial spondyloarthropathy (axSpA) and magnetic resonance imaging findings of the sacroiliac joint. Patients and methods: Thirty-two patients (21 males, 11 females; mean age: 39.3±9.2 years; range, 18 to 55 years) who were diagnosed with axSpA according to the Assessment in Spondyloarthritis International Society classification criteria between November 2015 and August 2017 were included in this cross-sectional study. Visual Analog Scale (VAS), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Ankylosing Spondylitis Disease Activity Score (ASDAS)-erythrocyte sedimentation rate (ESR), and ASDAS-C-reactive protein (CRP) were used as the indicators of clinical activity. Magnetic resonance imaging of the sacroiliac joint was performed and the Spondyloarthritis Research Consortium of Canada (SPARCC) score was evaluated by a radiologist who was blinded to the clinical and laboratory parameters of the patients. Results: The mean duration of symptom onset was 9.3±7.7 years, and the mean duration of diagnosis was 3.6±2.8 years. Human leukocyte antigen (HLA)-B27 was positive in 16 (50%) patients. There was no correlation between the SPARCC score and VAS, BASDAI, MASES, BASFI, ASDAS-CRP, ASDAS-ESR, ESR, and CRP values (p>0.05). In the HLA-B27 subgroup analyses, a statistically significant correlation was found between HLA-B27-negative patients and SPARCC score (r=0.639, p=0.008). Conclusion: No relationship was found between other clinical disease parameters and sacroiliac joint imaging findings, except for the relationship between the SPARCC and BASDAI in HLA-B27- negative patients with axSpA.
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.
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 it