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Record W2422702913 · doi:10.1590/0004-282x20160060

Presence or absence of cognitive complaints in Parkinson’s disease: mood disorder or anosognosia?

2016· article· en· W2422702913 on OpenAlexaboutno aff
Pollyanna Celso Felipe de Castro, Camila Aquino, André C. Felício, Flavia Doná, Leonardo Mariano Inácio Medeiros, Sônia M. C.A. Silva, Henrique Ballalai Ferraz, Paulo Henrique Ferreira Bertolucci, Vanderci Borges

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2016
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMoodCognitionPsychologyAnosognosiaVerbal fluency testParkinson's diseaseDepression (economics)Beck Depression InventoryClinical psychologyPsychiatryApathyMontreal Cognitive AssessmentRating scaleAnxietyNeuropsychologyDiseaseMedicineInternal medicineCognitive impairmentDevelopmental psychology

Abstract

fetched live from OpenAlex

We intended to evaluate whether non-demented Parkinsons's disease (PD) patients, with or without subjective cognitive complaint, demonstrate differences between them and in comparison to controls concerning cognitive performance and mood. We evaluated 77 subjects between 30 and 70 years, divided as follows: PD without cognitive complaints (n = 31), PD with cognitive complaints (n = 21) and controls (n = 25). We applied the following tests: SCOPA-Cog, Trail Making Test-B, Phonemic Fluency, Clock Drawing Test, Boston Naming Test, Neuropsychiatric Inventory, Hospital Anxiety and Depression Scale (HADS) and Beck Depression Inventory. PD without complaints presented lower total score on Scales for outcome of Parkinson's disease-cognition as compared to controls (p = 0.048). PD with complaints group showed higher scores on HADS (p = 0.011). PD without complaints group showed poorer cognitive performance compared to controls, but was similar to the PD with complaints group. Moreover, this group was different from the PD without complaints and control groups concerning mood.

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)0.002
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 score0.012
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.293
Teacher spread0.268 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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