Effects of Pneumocephalus on Electrode Location After Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson Disease
Bibliographic record
Abstract
OBJECTIVE: This study investigates the impact of pneumocephalus on electrode positioning following subthalamic nucleus deep brain stimulation (STN-DBS) in patients with Parkinson disease. METHODS: A retrospective analysis was performed on 111 patients who underwent bilateral STN-DBS at the First Affiliated Hospital of Anhui Medical University. Preoperative magnetic resonance imaging and postoperative computed tomography scans were utilized to assess electrode positions and pneumocephalus volume. The brain imaging data were standardized to the Montreal Neurological Institute space for precise comparison. Statistical analyses were performed to identify factors influencing the volume of pneumocephalus. RESULTS: This study found that pneumocephalus absorption significantly affects electrode positioning, leading to a forward and upward shift. A higher degree of brain atrophy and a higher number of microelectrode recording passages were significantly correlated with increased pneumocephalus volume and more pronounced electrode displacement. CONCLUSIONS: Pneumocephalus plays a critical role in electrode displacement during STN-DBS surgery. Minimizing cerebrospinal fluid loss and careful planning of microelectrode recording passages are essential for improving surgical accuracy. Further studies with larger sample sizes and multicenter data are needed to validate these findings and increase their generalizability.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".