Actigraph-based quantification of sleep in children with dystonia undergoing deep brain stimulation
Bibliographic record
Abstract
OBJECTIVE: Dystonia is among the most common pediatric movement disorders and can manifest with a range of debilitating symptoms, including sleep disruptions. The duration and quality of sleep are strongly associated with quality of life in these individuals and could serve as biomarkers of dystonia severity and the efficacy of interventions such as deep brain stimulation (DBS). Thus, this study investigated sleep duration and its relationship to disease severity and DBS response in pediatric dystonia. METHODS: Actigraphs (wearable three-axis accelerometers) were used to record multiday sleep data in 22 children with dystonia, including 6 patients before and after DBS implantation, and age- and sex- matched healthy controls. Data were preprocessed, and metrics of sleep duration and quality were extracted. Repeated-measures statistical analyses were used. RESULTS: Children with dystonia slept less than typically developing children (p = 0.009), and shorter sleep duration showed trending correlation with worse dystonia severity (r = -0.421, p = 0.073). Of 4 patients who underwent DBS and had good-quality data, 1 demonstrated significantly improved sleep (p < 0.001) postoperatively. Reduction in dystonia severity strongly correlated with increased sleep duration after DBS implantation (r = -0.965, p = 0.035). CONCLUSIONS: Sleep disturbances are an underrecognized marker of pediatric dystonia severity, as well as the effectiveness of interventions such as DBS. They can serve as objective biomarkers of disease burden and symptom progression after treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".