Deep brain stimulation of the centromedian nucleus for drug‐resistant epilepsy in children: Quality‐of‐life and functional outcomes from the <scp>CHILD</scp> ‐ <scp>DBS</scp> registry
Bibliographic record
Abstract
OBJECTIVE: Deep brain stimulation of the centromedian nucleus of the thalamus (CM-DBS) is an investigational, off-label treatment for drug-resistant epilepsy (DRE) in children. Although emerging evidence supports its safety and efficacy for select indications, the effect of CM-DBS on quality of life and functional outcomes such as school attendance has not been studied. Here, we analyzed data from the prospective CHILD-DBS (Child & Youth Comprehensive Longitudinal Database for Deep Brain Stimulation) to examine the impact of CM-DBS on patient- and caregiver-reported outcomes. METHODS: Twenty-two children and youth underwent bilateral CM-DBS. Caregiver-child dyads completed surveys related to seizure frequency, seizure severity, quality of life, and school attendance at baseline, 6 months, and 1 year postsurgery. Simulated volumes of tissue activation were analyzed to identify optimal stimulation targets associated with treatment outcome. RESULTS: Of 22 children, 10 experienced ≥50% reduction in seizure frequency (mean reduction = 66.7 ± 17.3%), one exhibited a modest benefit (37.5% reduction), and the remaining 11 experienced no change. The majority (73% of patients) exhibited a clinically important reduction in seizure severity, including six children who did not demonstrate any change in seizure frequency. Only those who experienced a reduction in seizure frequency demonstrated significant improvements in general health and overall quality of life. Furthermore, we observed an increase in school attendance across participants 1 year after CM-DBS. SIGNIFICANCE: CM-DBS can lead to reduction in seizure burden concurrent with improvements in quality of life and relevant functional outcomes in children with DRE. These findings further our understanding of the impact of CM-DBS on meaningful outcomes for children and caregivers.
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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 | 0.002 |
| 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 | 0.001 |
| 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".