Effects of Deep Brain Stimulation on Postural Trunk Deformities: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Deep brain stimulation (DBS) effects on postural deformities are still poorly explored. METHODS: Systematic review in accord with the Preferred Reporting Items for Systematic review and Meta-Analysis guidelines (PRISMA). RESULTS: All 38 studies that met predefined eligibility criteria had high risk of bias attributed to retrospective analysis of heterogeneous populations with variable and incompletely reported demographic and clinical characteristics, definitions, outcomes, DBS indications, targets, and settings. Five patient groups were identified in the 35 studies with individual data available: (1) parkinsonian camptocormia (n = 96): 89 patients underwent subthalamic (STN) and 7 globus pallidus pars interna (GPi) DBS. Camptocormia was the indication in 3 patients. After DBS, camptocormia improved in 57 of 96 patients (4.3-100% improvement) and remained stable or worsened in 39 of 96 patients (2-100% worsening). (2) dystonic camptocormia (n = 16): All underwent GPi-DBS. They were younger and with shorter disease duration, but longer deformity duration, compared with parkinsonian camptocormia. After GPi-DBS, camptocormia improved in all patients (50-100% improvement). (3) Parkinsonian Pisa syndrome (n = 14): 11 patients underwent STN-DBS for motor fluctuations whereas Pisa syndrome was the indication for pedunculopontine and GPi-DBS in 2 patients. After DBS, Pisa improved in 10 of 14 patients (33.3-66.7% improvement). (4) Dystonic opisthotonus: 2 young patients remarkably responded to GPi-DBS. (5) Parkinsonian anterocollis: There were variable responses in 3 patients after STN-DBS for motor fluctuations. CONCLUSIONS: Low-quality level of evidence suggests that dystonic camptocormia and opisthotonus improve after GPi-DBS. Parkinsonian camptocormia, Pisa syndrome, and anterocollis have variable responses, and their dystonic features should be further explored.
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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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".