MR Imaging of the Spine and Sacroiliac Joints for Spondyloarthritis: Influence on Clinical Diagnostic Confidence and Patient Management
Bibliographic record
Abstract
PURPOSE: To quantify the effect of magnetic resonance (MR) imaging of the spine and sacroiliac joints on clinical diagnostic confidence and to determine if MR imaging affects treatment of patients with axial spondyloarthritis. MATERIALS AND METHODS: This prospective observational study was approved by the research ethics board and included 55 consecutive patients referred by three rheumatologists for MR imaging of the spine and sacroiliac joints. Measures of diagnostic confidence for clinical features (inflammatory back pain, mechanical back pain, muscular back pain, radicular back pain, spondylitis, sacroiliitis, and other) and overall diagnoses were made by using a Likert scale both before and after MR imaging. Proposed treatment was similarly recorded before and after MR imaging interpretation. The McNemar test was performed to determine the change in diagnostic confidence and consequent effect on patient treatment. RESULTS: Diagnostic confidence for specific clinical features improved significantly after MR imaging for inflammatory back pain (14% vs 76%, before vs after; P < .001), mechanical back pain (4% vs 49%, P < .001), spondylitis (7% vs 76%, P < .001) and sacroiliitis (9% vs 87%, P < .001). Confidence for overall diagnoses also improved significantly after MR imaging for ankylosing spondylitis (29% vs 80%, P < .001), undifferentiated spondyloarthritis (58% vs 93%, P < .001) and osteoarthritis (29% vs 64%, P < .001). Of the 23 patients for whom tumor necrosis factor-α inhibitor (TNFi) therapy was recommended before MR imaging, 12 (52%) were prescribed TNFi therapy after MR imaging. Of the 32 patients for whom TNFi therapy was not recommended before MR imaging, 10 (31%) patients were prescribed TNFi therapy after MR imaging. Overall, 22 (40%) patients had a change in treatment recommendation regarding TNFi therapy after MR imaging. CONCLUSION: MR imaging of the spine and sacroiliac joints significantly influences the diagnostic confidence of rheumatologists regarding clinical features and overall diagnoses of axial spondyloarthritis, and consequently significantly affects treatment plans.
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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 | 0.002 | 0.029 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".