Impact of Mild Cognitive Impairment on Health-Related Quality of Life in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND/AIMS: To assess the impact of mild cognitive impairment (MCI) or cognitive decline on health-related quality of life (HR-QOL) in Parkinson's disease (PD). METHODS: HR-QOL measured by the Parkinson Disease Quality of Life Questionnaire (PDQ-39), MCI according to Movement Disorder Society Task Force criteria and cognitive decline from premorbid baseline were assessed in non-demented PD patients at 6 movement disorder clinics. RESULTS: Among 137 patients, after adjusting for education, gender, disease duration, and Movement Disorder Society Unified Parkinson's Disease Rating Scale total score, MCI was associated with worse scores within the PDQ-39 dimension of communication (p = 0.008). Subjects were divided into tertiles of cognitive decline from premorbid level. Scores in the dimension of stigma were worst in the second tertile of cognitive decline (p = 0.03). MCI was associated with worse social support scores in the second tertile of cognitive decline (p = 0.008). CONCLUSION: MCI and cognitive decline from premorbid baseline are associated with reduced HR-QOL in communication, stigma, and social support domains. The cognitive decline from premorbid baseline modifies the association between MCI and HR-QOL in PD and knowing both will allow a better appreciation of difficulties patients face in daily life.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".