Early Detection of White Matter Changes with Cognitive Decline in Parkinson's Patients
Bibliographic record
Abstract
Objective: The aim of this study was to detect changes in white matter in patients with Parkinson's disease applied by diffusion tensor imaging to predict cognitive impairment. Methods: Montreal cognitive assessment was applied to 50 Parkinson's disease patients to confirm cognitive decline (M: F = 41:9; age: 62.72±9.07 years) and to 20 Parkinson's disease patients with no cognitive impairment as a control (M: F =13:7; age 58.95±11.22). All patients underwent disease severity testing by using Modified Hoehn and Yahr Scale, Unified Parkinson disease rating scale and Diffusion tensor imaging (DTI) for the corpus callosum and cingulum including their involved parts to define affected tracts. Results: In PD with cognitive impairment subjects, the cognitive affection correlated with abnormal DTI parameters of the corpus callosum and cingulum. There were FA or MD differences in both the corpus callosum and cingulum pathways. These findings were independent of age, sex and total white matter volume. Conclusion: Patients with Parkinson's disease associated with cognition decline are detected by tractography changes of the corpus callosum and cingulum.
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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 | 0.001 | 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".