[Study on the status of cognition among Parkinson's disease patients in Xi'an.].
Bibliographic record
Abstract
OBJECTIVE: To study the characteristics and influencing factors of cognition on patients with Parkinson's disease (PD) in Xi'an in order to provide evidence for early recognition and treatment of cognitive impairment on PD patients. METHODS: Clinically defined PD patients from 7 hospitals in Xi'an from Jan. to Apr. 2007 were assessed with mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA) for whole cognitive function. Furthermore, Fuld object memory test (FOM) was used to assess delayed memory while rapid verbal retrieve (RVR) was used to assess language fluency. Digit span subtest was used to assess attention and building blocks was used to assess visual space function respectively. RESULTS: 100 PD patients were recruited, including 52 men and 48 women, from 43 to 86 years old (65.6 +/- 17.1). MMSE scores was used as the standard for Recognition, PD with cognitive impairment accounted for 16%. According to MOCA scores, with PD cognitive disturbances accounted for 83%. Ability for calculation, short-term memory, visual space function, abstract capability, attention and language fluency dysfunction were main cognitive disturbances of PD. Analysis from single factor logistic regression showed that education, age of onset and gender were closely related to the occurrence of cognitive impairment on PD patients. CONCLUSION: Cognitive impairment was common in PD. Ability of calculation, short-term memory, visual space function, abstract capability, attention and language fluency dysfunction were main cognitive disturbances of PD. Cognitive impairment of PD was more likely to occur with low degree of education, late onset of PD, and being female.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".