Upper cervical spinal cord atrophy in MS: Sex, menopause, and neurodegeneration
Bibliographic record
Abstract
Background: Spinal cord (SC) atrophy is a key imaging biomarker of progressive multiple sclerosis (MS). Progressive MS is more common in men and postmenopausal women. Objective: Investigate the impact of sex and menopause on SC measurements in persons with MS (pwMS). Methods: In pwMS and age- and sex-matched controls, upper cervical SC area from brain MRI (UCC brain ) was obtained. Impact of sex and menopause on UCC brain (adjusted for total intracranial volume) and its association with progression and disability, including MS functional composite (MSFC), were investigated. Results: UCC brain was smaller in pwMS ( n = 118, 51.4 ± 5.3 mm 2 ) than controls ( n = 118, 54.2 ± 4.4 mm 2 , p < 0.001) and inversely correlated with older age in pwMS ( r = −0.24, p = 0.010) but not in controls ( r = −0.025, p = 0.786). In 173 pwMS (413 brain MRIs), UCC brain was smaller in men (49.5 ± 5.9 mm 2 ) than women (51.6 ± 5.5 mm 2 , p = 0.001), postmenopausal women (49.4 ± 5.6 mm 2 ) than premenopausal women (52.9 ± 4.1 mm 2 , p < 0.001), and progressive (47.5 ± 5.6 mm 2 ) than relapsing MS (52.1 ± 5.2 mm 2 , p < 0.001). UCC brain also correlated with disease duration ( r = −0.39, p < 0.001), 9-hole peg test ( r = −0.26, p = 0.005), and severe ambulatory disability (Expanded Disability Status Scale ⩾6) ( r = −0.27, p < 0.001). Conclusion: UCC brain , a biomarker of progressive MS, is inversely associated with age, disease duration, male sex, and menopause, highlighting the potential impact of sex and hormones on neurodegeneration in MS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".