P.038 Exploring alternative deep brain stimulation targets for movement disorder in children – a systematic literature review
Bibliographic record
Abstract
Background: Deep Brain Stimulation (DBS) has become increasingly prevalent in the management of paediatric movement disorders, with the globus pallidus interna (GPi) serving as the most utilized target. However, limitations exist, including variable responses in genetic versus acquired forms of movement disorder and structural damage in the GPi would preclude its use as a target. Given these limitations, there is a pressing need to explore alternative targets. We investigated the application of non-GPi targets in paediatrics through a systematic review. Methods: Individual data points were gathered from references identified through a systematic electronic search and analysed descriptively. We included paediatric patients (0-18 years) with movement disorders who underwent non-GPi-DBS. We excluded adults and other indications. Results: Preliminarily, 64 patients were identified from 40 references. Dystonia was the most common movement disorder type, followed by tremor and chorea. The subthalamic nucleus was the frequent DBS target for dystonia, yielding promising outcomes of improvement as measured on the Burke-Fahn-Marsden movement scale ranging from 43% to 95%. The ventral intermediate nucleus was the second most employed target, demonstrating favourable results. Conclusions: Non-pallidal DBS targets hold promise as potentially efficient and safe. However, to further validate their effectiveness and safety, larger multi-centre randomized studies are required.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".