The Protective Role of Cognitive Reserve: A Preliminary Study on Parkinsonian Patients Undergoing Deep Brain Stimulation
Bibliographic record
Abstract
Background/Objectives: High cognitive reserve (CR) has been shown to have beneficial effects on global cognition, cognitive decline, and risk of dementia in Parkinson’s disease (PD). We evaluated the influence of CR on the long-term cognitive outcomes of patients with PD who underwent subthalamic nucleus deep brain stimulation (STN-DBS). Methods: Twenty-five patients with PD underwent neuropsychological screening using the Montreal Cognitive Assessment (MoCA) at baseline, 1 year, and 5 years after bilateral STN-DBS. CR was assessed using the Cognitive Reserve Index questionnaire. According to CR score, patients were assigned to two different groups (LowCR group ≤ 130, HighCR group > 130). Results: Our data showed that patients in the HighCR group obtained a better performance with the MoCA total score at long-term follow-up compared to those in the LowCR group ([mean ± SE] LowCR group: 21.4 ± 1.2 vs. HighCR group: 24.5 ± 1.3, p = 0.05). The cognitive profile of the HighCR group remained unchanged over time. Conversely, the LowCR group had worse global cognition 5 years after surgery (T0: 25.3 ± 0.6 vs. T2: 21.4 ± 1.2, p = 0.02). Cognitive decline was not associated with mood, demographics, or clinical variables. Conclusions: These preliminary findings suggest that higher CR may be protective in PD cognition after STN-DBS. Specifically, a high CR may help cope with long-term decline in the context of surgical treatment. Quantifying a patient’s CR could lead to more personalized medical care, tailoring postoperative support and monitoring for those at higher risk of cognitive decline.
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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 | 0.001 | 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".