Magnetic Resonance Imaging of Spinal Cord Lesions in Patients with Multiple Sclerosis in Saskatchewan, Canada
Bibliographic record
Abstract
Abstract Background: Spinal cord lesions (SCLs) contribute to disability in multiple sclerosis (MS). Data in Saskatchewan, Canada, concerning SCLs and their association with disability levels in patients with MS are lacking. The study objectives were to identify clinicodemographic profiles of patients with MS with respect to spinal cord magnetic resonance imaging (MRI) involvement; determine the frequency of individuals with MRI SCLs; and explore differences between patients with MS with and without SCLs with respect to disability and disease-modifying therapy status. Methods: A monocentric, cross-sectional, retrospective review of prospectively collected data from 532 research-consented patients seen at Saskatoon MS Clinic was performed. Data were collected from a database and electronic medical records. Results: Of the 356 patients (66.9%) with an SCL, 180 (50.6%) had only cervical cord lesions. Median Expanded Disability Status Scale (EDSS), ambulation, and pyramidal scores of patients with SCLs were higher than those of patients without SCLs. Of patients with EDSS scores of at least 6, those with SCLs were younger than those without SCLs (P = .01). Patients with SCLs were 55% less likely to have been on continuous disease-modifying therapy since diagnosis than patients without SCLs (adjusted odds ratio, 0.45; 95% CI, 0.25–0.81; P = .008). Conclusions: Prevalence and association with disability of SCLs in patients with MS are comparable with existing literature. Patients with MS with SCLs have higher levels of disability and attain EDSS scores of at least 6 at a younger age.
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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 | 0.000 | 0.001 |
| 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".