Bibliographic record
Abstract
Objective To investigate the related influencing factors of Parkinson disease dementia (PDD).Methods A controlled study was conducted in Outpatient Department of Parkinson disease from 2006 to 2007.There were 48 PDD patients (PDD group) and 72 Parkinson disease (PD) patients (PD group).In PDD patients,dementia was found at least 2 or more than 2 years after occurrence of PD. Questionnaire,including baseline information was performed.The grade of PD was diagnosed in accordance with UK Parkinson Disease Society Brain Bank Clinical Criteria.Dementia diagnosis was based on Diagnostic and Statistical Manual of Mental Disorders Forth Edition(DSM-Ⅳ). PD was evaluated by Unified Parkinson Disease Rating Scale (UPDRS).Cognitive condition was assessed by Mini-Mental State Examination(MMSE),Montreal Cognitive Assessment(MoCA),Rapid Verbal Retrieve Test (RVR) and Clock Drawing Test (CDT).Single unconditioned logistic regression analysis and multiple logistic regression model were applied.Results The mean age was (75.44±8.97) years old in PDD group and (70.35±11.34) years old in PD group.In simple factor analysis,age and UPDRS Ⅲ score in PDD group were all higher than those in PD group (P0.05,for all).The probability of dementia in tremor type PD was comparably lower (OR=0.364,95%CI:0.139-0.953).Depression was found to be a high risk factor for PDD (OR=2.647,95% CI:0.963-7.000).Multivariate analysis showed that age,educational degree,UPDRS Ⅲ score and tremor type were factors entered in regression equation (OR=1.203,0.790, 4.264,0.065,respectively).Conclusion Age,educational degree,UPDRS Ⅲ score,tremor type and depression are the related influencing factors for PDD.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".