Diagnostic brain MRI findings in primary progressive multiple sclerosis
Bibliographic record
Abstract
The clinical course of multiple sclerosis can be classified as relapsing from onset (relapsing-remitting), or progressive from onset (primary progressive - PPMS). These clinical phenotypes have been based on historical and clinical observations. It has been reported that PPMS patients tend to have quantitatively less MRI activity and disease burden. We evaluated the sensitivity and diagnostic value of conventional brain MRI scan in 143 PPMS patients. Brain MRIs were blindly evaluated to determine if they satisfied Paty and/or Fazekas diagnostic criteria. Patients were divided into those with typical, atypical or normal scans. They satisfied brain MRI criteria in 92% cases. Findings included: 131 typical, four atypical, and eight normal scans. All 12 non-typical scans' subjects had spinal onset; spinal MRI scans were positive in four of seven cases. Sex, age of onset, site and number of symptoms involved at onset among those groups were not significantly different but accumulation of disability had a tendency to be slower in these few individuals with normal or atypical head MRI's. Although there may be quantitative differences in lesion activity/burden, MRI scanning in PPMS unexpectedly has diagnostic sensitivity very similar to that seen in RRMS. A normal brain MRI is unusual in PPMS patients.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".