APATHY & COGNITIVE SYMTOMS IN DEEP BRAIN STIMULATION
Bibliographic record
Abstract
Objective: The aim of this research was to elucidate the effect of deep brain stimulation on apathy, and cognitive functions in the pre and post-operative period. Materials & Methods: This study was conducted in Adana City Training & Research Hospital, Parkinson and Movement Disorders Center between January to December 2022. Individuals were evaluated by a multidisciplinary commission consisting of neurology, neurosurgery and psychiatrists. Thirty six, aged between 18–70 years who underwent Deep Brain Stimulation at the neurosurgery clinic were included in the study. Hamiltonanxiety and depression, apathy assessment, standard mini-mental test and Montreal Cognitive Assessment scales are applied to the patients. Results: The mean Apathy Score at the pre-op was 47.77±15.83 in patients who had undergone DBS operation while it was 30.83±13.59 in the post–op. This decrease was statistically significant (p<0.003) and indicated clinical improvement. The average Hamilton Anxiety scale scores at the pre–op was 11.50±5.14, and s 10.22±5.57 at the post-op with no clinical significance (p=0.28). The UPDRS-ON value was determined as 22.55±7.53 in the pre–op and 14.50±6.99 in the post–op significantly (p<0.001). UPDRS-OFF was found to be significant with pre–op 37.44±9.85, compared to post–op 23.44±7.86 (p<0.001). Conclusion: Regarding the results of this study, it was found that sub – thalamic stimulation led to stabilization of both motor and non-motor complications. Additionally DBS ameliorated apathy and Parkinson’s Disease symptoms of patients significantly. Future studies with larger sample size that focus on both pharmacological and non-pharmacological treatments might provide better clinical aspects.
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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 | 0.000 |
| 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".