Cognitive profile of patients with facioscapulohumeral muscular dystrophy
Bibliographic record
Abstract
ABSTRACT Although it is predominantly a muscular disease, impairments in the central nervous system in patients with facioscapulohumeral muscular dystrophy (FSHD) have been described in the literature. Objective: To describe the cognitive profile of patients with FSHD and to correlate the impairments found with clinical variables and quality of life. Methods: Cross-sectional and case–control study that evaluated FSHD patients using a series of cognitive assessments (Mini-Mental State Examination — MMSE, Montreal Cognitive Assessment — MoCA, verbal fluency with phonological restriction — FAS, categorical verbal fluency — FAS-cat, trail-making test — TMT, and Rey’s Verbal Auditory Learning Test); a neurological severity scale (Gardner–Medwin–Walton — GMWS); and a quality of life measurement tool (Medical Outcomes Study 36-Item Short-Form Health Survey). Results: Individuals with FSHD (13) and healthy controls (26) were paired by gender and age. Significant differences between case and control groups were found in MMSE, TMT A, and A7 (p≤0.05) and MOCA (p≤0.001) performances. A positive correlation was verified in long-term memory impairments and the age in which symptoms appear (r=-0.593, p=0.033). Regarding quality of life assessment, the emotional domain correlated to MEEM (r=0.657, p=0.015), TMT A (r=-0.601, p=0.030), and A7 (r=0.617, p=0.025) performances. Conclusions: Individuals with FSHD presented mild impairments in the performance of tasks that involve attention, planning, and long-term memory functions. Those impairments were associated neither with the disease duration nor with its neurological severity.
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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 | 0.001 | 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) | 0.001 | 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".