Plasma glial fibrillary acidic protein levels correlate with paramagnetic rim lesions in people with radiologically isolated syndrome
Bibliographic record
Abstract
BACKGROUND: There are no specific, evidence-based recommendations for the management of individuals with radiologically isolated syndrome. Imaging and blood biomarkers may have prognostic utility. OBJECTIVE: To determine whether plasma neurofilament light protein (NfL) or glial fibrillary acidic protein (GFAP) levels in people with radiologically isolated syndrome correlate with imaging measures that have been shown to be associated with negative clinical outcomes in people with multiple sclerosis. METHODS: Cross-sectional analysis of people with radiologically isolated syndrome. Participants underwent magnetic resonance imaging (MRI) of the brain and cervical spinal cord, and plasma was collected. Plasma NfL and GFAP levels were measured with a single-molecule array, and correlations with MRI measures were assessed, including the number of: T1-black holes, white-matter lesions demonstrating the central vein sign, paramagnetic rim lesions, cervical spinal cord lesions and infratentorial lesions. RESULTS: < 0.05). CONCLUSION: We found correlations between plasma GFAP levels and imaging measures associated with poor clinical outcomes and chronic inflammation in individuals with radiologically isolated syndrome. Plasma GFAP may have prognostic utility in clinical trials and clinical practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".