Relationship between electrode position of deep brain stimulation and motor symptoms of Parkinson’s disease
Bibliographic record
Abstract
BACKGROUND: To investigate the relationship between the position of bilateral STN-DBS location of active contacts and the clinical efficacy of STN-DBS on motor symptoms in Parkinson's disease (PD) patients. METHODS: Retrospectively analyze the clinical data of 57 patients with PD who underwent bilateral STN-DBS from March 2018 to December 2018. Unified Parkinson's Disease Rating Scale-Part III (UPDRS-III) score, levodopa equivalent day dose (LEDD), Parkinson's Disease Quality of Life Scale (PDQ-39) before operation and within 6 months after operation, determine the location of activated contacts and volume of tissue activated (VTA) in the Montreal Neurological Institute (MNI) space, and analyze their correlation with the improvement rate of motor symptoms (UPDRS-III score improvement rate). RESULTS: After 6 months of follow up, the UPDRS-III scores of 57 patients (Med-off) were improved by 55.4 ± 18.9% (P<0.001) compared with that before operation. The improvement rate of PDQ-39 scores [(47.4 ± 23.2)%, (P < 0.001)] and the reduction rate of LEDD [(40.1 ± 24.3)%, (P < 0.01)] at 6 months postoperation were positively correlated with the improvement rate of motor symptoms (Med-off)(PDQ-39:r = 0.461, P<0.001; LEDD: r = 0.354, P = 0.007), the improvement rate of UPDRS-III (Med-off) and the Z-axis coordinate of the active contact in the MNI space were positively correlated (left side: r = 0.349,P = 0.008;right side: r = 0.369,P = 0.005). In the MNI space, there was no correlation between the UPDRS-III scores improvement rate (Med-off) at 6 months after operation and bilateral VTA in the STN motor subregion, STN associative subregion and STN limbic subregion of the active electrode contacts of 57 patients (all P > 0.05). At 6 months after surgery, the difference between the Z-axis coordinate in the different improvement rate subgroups(<25, 25 to 50%, and>50%) in the MNI space was statistically significant (left side: P = 0.030; right side: P = 0.024). In the MNI space, there was no statistically significant difference between the groups in the VTA of the electrode active contacts (all P > 0.05). CONCLUSION: STN-DBS can improve the motor symptoms of PD patients and improve the quality of life. The closer the stimulation is to the STN dorsolateral sensorimotor area, the higher the DBS is to improve the motor symptoms of PD patients.
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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 | 0.001 |
| 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".