Sequence of electrode implantation and outcome of deep brain stimulation for Parkinson's disease
Bibliographic record
Abstract
INTRODUCTION: The effect of the variability of electrode placement on outcomes after bilateral deep brain stimulation of subthalamic nucleus has not been sufficiently studied, especially with respect to the sequence of hemisphere implantation. METHODOLOGY: We retrospectively analysed the clinical and radiographic data of all the consecutive patients with Parkinson's disease who underwent surgery at our centre and completed at least 1 year follow-up. The dispersion in electrode location was calculated by the square of deviation from population mean, and the direction of deviation was analysed by comparing the intended and final implantation coordinates. Linear regression analysis was performed to analyse the predictors of postoperative improvement of the motor condition, also controlling for the sequence of implanted hemisphere. RESULTS: 76 patients (mean age 58±7.2 years) were studied. Compared with the first side, the second side electrode tip had significantly higher dispersion as an overall effect (5.6±21.6 vs 2.2±4.9 mm(2), p=0.04), or along the X-axis (4.1±15.6 vs 1.4±2.4 mm(2), p=0.03) and Z-axis (4.9±11.5 vs 2.9±3.6 mm(2), p=0.02); the second side stimulation was also associated with a lower threshold for side effects (contact 0, p<0.001 and contact 3, p=0.004). In the linear regression analysis, the significant predictors of outcome were baseline activities of daily living (p=0.010) and dispersion of electrode on the second side (p=0.005). CONCLUSIONS: We observed a higher dispersion for the electrode on the second implanted side, which also resulted to be a significant predictor of motor outcome at 1 year.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".