Characteristics of Cognitive Impairment and Their Relationship With Total Cerebral Small Vascular Disease Score in Parkinson’s Disease
Bibliographic record
Abstract
Background: This study aimed to investigate the characteristics of cognitive dysfunctions and their relationship with total cerebral small vascular disease (CSVD) in Parkinson's disease (PD). Methods: A total of 174 idiopathic PD patients who underwent brain magnetic resonance imaging (MRI) were recruited. Demographic information, vascular disease risk factors, motor function (MDS-UPDRS III score), and cognitive level (MoCA, MMSE) were collected for these patients. The total CSVD burden was scored based on lacunes, enlarged perivascular spaces (EPVS), high-grade white matter hyperintensities (WMH), and cerebral microbleeds (CMBs) for each subject. Results: Cognitive scores on MoCA for language, delayed recall, and orientation were significantly reduced in PD patients with CSVD burden ≥ 1 than in those with CSVD burden = 0. Educational level, PDQ 39, and CSVD burden were significantly associated with MoCA scores in individuals with PD. For the whole group, the full model accounted for 33.6% variation in total MoCA scores. In which, CSVD burden explained 2.7% of the results, and the detection of lacunes, WMH, EPVS, and strictly lobar CMBs were significantly correlated with MoCA scores. The stability of the outcomes was confirmed by sensitivity analysis. Conclusion: CSVD can independently contribute to cognitive decline in PD and cause damage in specific cognitive domains. Promoting neurovascular health may help preserve cognitive functions in PD.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".