Spondyloarthritis research Consortium of Canada magnetic resonance imaging index for assessment of sacroiliac joint inflammation in ankylosing spondylitis
Bibliographic record
Abstract
OBJECTIVE: To develop a feasible magnetic resonance imaging (MRI)-based scoring system for sacroiliac joint inflammation in patients with ankylosing spondylitis (AS) that requires minimal scan time, does not require contrast enhancement, evaluates lesions separately at each articular surface, and limits the number of sacroiliac images that are scored. METHODS: A scoring method based on the assessment of increased signal denoting bone marrow edema on T2-weighted STIR sequences was used. MRI films were assessed blindly in random order at 2 sites by multiple readers. Intra- and interreader reliability was assessed by intraclass correlation coefficient (ICC); the 24-week response of patients with AS randomized to placebo:infliximab (3:8) was assessed by effect size and standardized response mean. The reliability and responsiveness of the scoring method were compared for STIR and gadolinium diethylenetriaminepentaacetic (Gd-DTPA)-enhanced MRI sequences. RESULTS: We scanned 11 patients with AS with clinically active disease and 11 additional patients randomized to the trial of infliximab therapy. ICC for total sacroiliac joint STIR score ranged from 0.90 to 0.98 (P < 0.00001) and interobserver ICC for combined readers from the 2 sites was 0.84 (P < 0.0001). ICC for change scores was lower for STIR (ICC 0.53) than for Gd-DTPA-enhanced sequences (ICC 0.79). Responsiveness was poor, although fusion was evident in one-third of patients who received treatment (placebo:infliximab) and inflammation scores were low. CONCLUSION: The Spondyloarthritis Research Consortium of Canada MRI index is a feasible and reproducible index for measuring sacroiliac joint inflammation in patients with AS.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".