The Relationship Between Memory Impairment and Health Indicators of the Elderly With Parkinson Disease
Bibliographic record
Abstract
Objectives Parkinson Disease (PD) is a progressive neurodegenerative disorder affecting motor and cognitive functions.Cognitive impairments are related to different causes such as health indicators.This study aimed to examine the relationship between cognitive impairment and health indicators of patients with PD.Methods & Materials This study was a cross-sectional and descriptive study.By convenience sampling method, a total of 30 PD patients 60-70 years old, diagnosed by a neurologist, were recruited.Cognitive Montreal Test was administrated to measure their global cognitive function.Rey visual test was used to determine their visual memory and the Wechsler test (adult memory) was used to assess their verbal memory.Their sleep quality was assessed by the Pittsburgh Sleep Quality Index.Demographic information and health indicators such as blood pressure were collected via interview.The obtained data were analyzed in SPSS 22. ResultsThe results showed significant relationship between some indicators such as blood pressure with verbal memory (r=-0.514,P=0.004), and sleep disorder (r=-0.421,P=0.031), and visual memory (r=0.368,P=0.045).Conclusion This research revealed that blood pressure and sleep disturbances can affect memory function.Therefore, the cognitive problems in people with PD can be postponed by screening these factors and controlling them with early medical interventions.
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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 | 0.001 |
| 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".