Non-Motor Manifestations in Idiopathic Dystonia with Focal Onset – A Pilot Study
Bibliographic record
Abstract
Recent studies emphasize an increased prevalence of non-motor symptoms in idiopathic dystonia with focal onset (IDFO), but their pathophysiological relationship is not clear. We aimed to identify the prevalence of depression and neurocognitive impairment in a group of patients with idiopathic dystonia with focal onset and their impact on the patients' quality of life. This study represents a component of an ongoing research project - GENDYS. From the database of this project, we selected 48 patients 56.62+/-14.16 years old who have been examined clinically and using specific scales: Patient Health Questionnaire-9 (for depression), Montreal Cognitive Assessment - MoCA (for cognitive impairment), and a 5-degree analog scale for subjective perception of the severity of the disease. We conducted a descriptive cross-sectional study on patients with depression and cognition evaluated by the above-mentioned scales. We also performed a nested case-control analysis on 20 IDFO patients with and without at least moderate depression matched for age and gender; the cut-offs for depression were PHQ-9 score ≥10 and PHQ9 <5, for the depression group and the control group, respectively. The cut-off for MoCA was 26 points. 22 IDFO patients (46%) had depression; 54.5% of IDFO patients with depression had cognitive impairment, indicating a slight trend of increased cognitive impairment in those with depression compared to those without; the perception of the severity of disease was the greatest in patients with depression. Depression is more prevalent in patients with IDFO and is associated with a worse perception of the disease 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".