C.4 Understanding the role of deep brain stimulation for Refractory Status Dystonicus in children: case series and systematic review
Bibliographic record
Abstract
Background: Status dystonicus (SD) is a life-threatening form of dystonia with limited treatments available. We sought to better understand the processes, outcomes, and complications of deep brain stimulation (DBS) for pediatric SD through a systematic review alongside an institutional case series. Methods: Data regarding treatment, stimulation parameters, dystonia severity and outcomes was collected for the case series (n=7) and systematic review (n=70, conducted in accordance with PRISMA guidelines). This was analysed descriptively (rates, outcome measures). For the case series we created probabilistic voxel-wise maps for improvement in dystonia based on brain region stimulated. Results: All patients in our case series and > 95% of patients in the systematic review had resolution of SD with DBS, typically within 2-4 weeks. Most patients in the review (84%) and all patients in the case series had DBS implanted to the globus pallidus internus. In terms of dystonia severity scores, there was a mean improvement of 25% (case series) or 49% (systematic review). Reported mortality was 4% in the systematic review. Conclusions: DBS for pediatric SD is feasible and safe. It allows for increased survival as well as quality of life - however risks still exist. More work is needed to determine timing, eligibility, and stimulation parameters.
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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 | 0.008 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".