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Clinical investigation of mild cognitive impairment in patients with Parkinson's disease

2008· article· en· W3031901020 on OpenAlexaboutno aff
Haibing Xiao, Xu Cao, Xi-Feng Wang, Xian Qiao, Shenggang Sun

Bibliographic record

VenueChin J Neurol · 2008
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNeuropsychologyDementiaDepression (economics)Rating scaleStroop effectClinical Dementia RatingCognitive impairmentMontreal Cognitive AssessmentMedicinePsychologyParkinson's diseasePsychiatryInternal medicineCognitionDiseasePhysical therapy

Abstract

fetched live from OpenAlex

Objective To describe the prevalence and neuropsychological character of mild cognitive impairment (MCI) associated with Parkinson' s disease(PD-MCI). Methods One hundred and three PD patients and a control group of 32 healthy old subjects were chosen. Psychometric assessment included the Mini Mental State Examination, the Dementia Rating Scale and a series of neuropsychol ogicaltests. The Hamilton Rating Scale of Depression was used to assess depression in PD patients. Results (1)Twenty-one (20.4%) PD patients was diagnosed with dementia, 45 (43.7%) had a MCI and only 37(35.9%) had no cognitive impairment; (2) Subjects with PD-MCI were older, had a later onset of the PD,and displayed more severe motor symptoms compared with those without cognitive impairment; (3) The prevalence and neuropsychological profile of PD-MCI were thought to correlate with the dominating side and subtype of Parkinsonian symptoms, for patients with left-sided dominant symptoms had a significantly higher chance of suffering MCI than those with right-sided dominant symptoms, the ratio being 74.2% vs 42.2%,χ<'2 =7. 589,P <0.05; The tremor-dominant group took less time than the mixed group for Stroop word test measurement ((80.8±39.9) s vs (94.4±30.0) s,t=3.332,P<0.01). Conclusion Identification of MCI is of important clinical significance, which helps to treat patients differently and thus predict the prognosis. Key words: Pakinson disease;  Congnition disorders;  Prevalence;  Neuropsychological tests

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.274
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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