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Record W7066689804

Influencia de la reserva cognitiva sobre la función cognitiva en pacientes con Enfermedad de Parkinson en dos hospitales nacionales de Lima. Abril - Setiembre del 2013

2015· dissertation· en· W7066689804 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2015
Typedissertation
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionCognitive reservePopulationMontreal Cognitive AssessmentNeuropsychologyCognitive declineMultivariate analysisNeuropsychological test
DOInot available

Abstract

fetched live from OpenAlex

The aim of this study is to determine how much cognitive reserve influences on cognitive profile in patients with Parkinson’s disease (PD). Therefore, an analytic, observational and prospective study was designed. The study population was integrated by PD patients from Hospital Regional de Huacho and Hospital de Chancay. A structure questionnaire validated by experts in the field and a standardized neuropsychological test were utilized to collect the patient information. 
\nResults were based on 90 PD patients, 49 (54.4%) men, the mean of age was 66.5 (SD=11.7). Cognitive impairment was present in 75 patients (83.3%). Cognitive reserve was divided in low (26 patients), middle (44 patients) and high (20 patients). Correlation between cognitive profile and cognitive reserve was statistically significant when cognitive profile was evaluated by Minimental test (r = 0.43; p=0.001) as well as cognitive profile was evaluated by Montreal Cognitive Assessment test (MoCA) (r = 0.55; p=0.001). This correlation was better explained by univariate and multivariate regression analysis. 
\nConclusions of the study were, first, cognitive reserve influence positively on cognitive profile in patients with PD and, second, a high percentage of patients show cognitive compromise in any phase of the disease.
\n
\nKey words: cognitive reserve, cognitive profile, Parkinson’s disease, cognitive impairment.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.013
GPT teacher head0.346
Teacher spread0.333 · 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.

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
Published2015
Admission routes1
Has abstractyes

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