Long-term Efficacy of Subthalamic Nucleus Deep Brain Stimulation in Parkinson's Disease
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Bibliographic record
Abstract
BACKGROUND: Subthalamic nucleus deep brain stimulation (STN DBS) is effective against advanced Parkinson's disease (PD), allowing dramatic improvement of Parkinsonism, in addition to a significant reduction in medication. Here we aimed to investigate the long-term effect of STN DBS in Chinese PD patients, which has not been thoroughly studied in China. METHODS: Ten PD patients were assessed before DBS and followed up 1, 3, and 5 years later using Unified Parkinson's Disease Rating Scale Part III (UPDRS III), Parkinson's Disease Questionnatire-39, Parkinson's Disease Sleep Scale-Chinese Version, Mini-mental State Examination, Montreal Cognitive Assessment, Hamilton Anxiety Scale and Hamilton Depression Scale. Stimulation parameters and drug dosages were recorded at each follow-up. Data were analyzed using the ANOVA for repeated measures. RESULTS: In the "off" state (off medication), DBS improved UPDRS III scores by 35.87% in 5 years, compared with preoperative baseline (P < 0.001). In the "on" state (on medication), motor scores at 5 years were similar to the results of preoperative levodopa challenge test. The quality of life is improved by 58.18% (P < 0.001) from baseline to 3 years and gradually declined afterward. Sleep, cognition, and emotion were mostly unchanged. Levodopa equivalent daily dose was reduced from 660.4 ± 210.1 mg at baseline to 310.6 ± 158.4 mg at 5 years (by 52.96%, P < 0.001). The average pulse width, frequency and amplitude at 5 years were 75.0 ± 18.21 μs, 138.5 ± 19.34 Hz, and 2.68 ± 0.43 V, respectively. CONCLUSIONS: STN DBS is an effective intervention for PD, although associated with a slightly diminished efficacy after 5 years. Compared with other studies, patients in our study required lower voltage and medication for satisfactory symptom control.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it