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Dopaminergic and Cholinergic Brain Activity and Performance on MMSE and MoCA in Parkinson's Disease (P03.127)

2012· article· en· W1997596710 on OpenAlexaboutno aff
Audrey Lenhart, Nicolaas I. Bohnen, Robert A. Koeppe, Kelvin L. Chou

Bibliographic record

VenueNeurology · 2012
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsDopaminergicParkinson's diseaseNeuroscienceCholinergicMedicinePsychologyDiseaseDopamineInternal medicine

Abstract

fetched live from OpenAlex

Objective: To investigate the relationship between performance on the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Exam (MMSE) and PET measures (dopaminergic/cholinergic) of brain activity. Background Executive dysfunction seen in early Parkinson9s disease (PD) is believed to result from striatal dopaminergic denervation, while the degree of cognitive impairment in PD dementia is thought to correlate with cortical cholinergic activity. Because it contains tasks that evaluate executive function, performance on the MoCA may correlate more strongly with striatal dopaminergic activity, while performance on the MMSE may better correlate with cortical cholinergic activity. Design/Methods: 19 non-demented men with PD (mean age 66.4 ± 7.5; mean disease duration 5.7 ± 3.5 years) underwent (+)-[ 11 C] dihydrotetrabenazine (DTBZ) vesicular monoamine transporter 2 and [ 11 C]methyl-4-piperidinyl propionate (PMP) acetylcholinesterase (AChE) PET imaging as well as the Unified PD Rating Scale (UPDRS), MoCA and MMSE. Results: Stepwise regression analysis was performed, with MoCA or MMSE as the dependent variable and the PET measures (cortical PMP, basal ganglia, putamen and caudate DTBZ) as regressors. Results for the MOCA show that cortical PMP was the only variable that met entry criteria in the model (F=6.12, P=0.024). The DTBZ measures did not meet entry criteria. Similar results were seen for the MMSE, with the cortical PMP variable as the only significant variable in the model (F=5.76, P=0.028). Conclusions: Both MoCA and MMSE performance were associated with cortical AChE activity in PD patients. Surprisingly, we did not find a significant relationship between the MoCA and striatal dopaminergic denervation, but we may not have had the power to detect such a relationship. Nevertheless, these findings suggest that both the MoCA and the MMSE may be reliable measures of the cognitive decline attributable to cortical cholinergic denervation seen in early PD. Supported by: NIH P01 NS15655, NIH R01 NS070856 (PI), and a grant from the Department of Veterans Affairs. Disclosure: Dr. Lenhart has nothing to disclose. Dr. Bohnen has nothing to disclose. Dr. Koeppe has nothing to disclose. Dr. Chou has received personal compensation for activities with Medtronic, Inc. and Merz Pharma.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.284
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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