Quantitative spinal cord MRI and sexual dysfunction in multiple sclerosis
Bibliographic record
Abstract
Background Sexual dysfunction (SD) is frequently reported in multiple sclerosis (MS) and is likely related to MS-related damage to the spinal cord (SC). Objective To assess associations between SD and quantitative MRI measures in people with MS (pwMS). Methods This pilot study included 17 pwMS with SD who completed questionnaires assessing SD, mood, and fatigue. All participants underwent brain, cervical, and thoracic SC-MRI at 3T. Quantitative brain and SC-MRI measures, including brain/SC atrophy, SC lesion count, diffusion-tensor imaging (DTI) indices (fractional anisotropy [FA], mean, perpendicular, parallel diffusivity [MD, λ⊥, λ||]) and magnetization-transfer ratio (MTR) were obtained. Associations between quantitative MRI measures and SD were assessed while controlling for the extent of mood and fatigue symptomatology. Results Subjects were a mean age of 46.9 years and 29% female. All subjects had self-reported SD (MSISQ-19 = 40.7, SQoL: 55.9) and 65% had a concurrent psychiatric diagnosis. When correlations between SD severity were assessed with individual brain and SC-MRI measures while controlling for psychiatric symptomatology, no associations were found. The only variables showing independent associations with SD were anxiety ( p = 0.03), depression ( p = 0.05), and fatigue ( p = 0.04). Conclusion We found no correlations between quantitative MRI measures in the brain and SC and severity of SD in pwMS, but psychiatric symptomatology and fatigue severity demonstrated relationships with SD. The multifactorial nature of SD in pwMS mandates a multidisciplinary approach.
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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 | 0.001 |
| 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".