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Correlation analysis of cognitive dysfunction and ischemic leukodystrophy in elderly patients

2018· article· en· W3031266888 on OpenAlexaboutno aff
Jinhui Wu, Xiwei Zhang, Xiaolong Shen

Bibliographic record

VenueCentral Plains Medical Journal · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCognitionMontreal Cognitive AssessmentInternal medicineLogistic regressionDiabetes mellitusExecutive dysfunctionMultivariate analysisCorrelationDiseasePhysical therapyCognitive impairmentPsychiatryNeuropsychologyEndocrinology

Abstract

fetched live from OpenAlex

Objective To study and analyze the correlation between cognitive dysfunction and ischemic leukodystrophy in elderly patients. Methods Eighty-eight elderly patients with ischemic leukodystrophy hospitalized in Pingmei Shenma Medical Group General Hospital from March 2016 to October 2017 were selected as research group. In addition, 30 healthy elderly patients who underwent physical examination in the same hospital were selscted as control group. The scores of the Montreal cognitive assessment (MoCA) of the two groups were analyzed and compared, and the relationship between the severity of disease and scores of MoCA scale was analyzed. Patients in research group were divided into cognitive dysfunction group (54 cases) and non-cognitive dysfunction group (34 cases), according to cognitive dysfunction development, for comparison on the basic data by multivariate Logistic regression analysis. Results The total score, visual space and executive function, attention, calculation, language, delayed recall and directional score of research group were lower than those of control group, and the differences were statistically significant (all P<0.05). The total score, delayed recall, directional score all showed a trend of gradually reduction in mild group, moderate group and medium group, contrast differences between groups were statistically significant (all P<0.05). The age, proportion of hypertension and diabetes in cognitive dysfunction group was higher than those in non-cognitive impairment group, and the difference was statistically significant (all P<0.05). Multivariate logistic regression analysis revealed that age, hypertension and diabetes were the independent risk factors of cognitive dysfunction in elderly patients with ischemic leukodystrophy (all P<0.05). Conclusions Cognitive dysfunction in the elderly is closely related to ischemic leukodystrophy, and with the increase of the severity of ischemic leukodystrophy, the more obvious the cognitive dysfunction is. Key words: Ischemic leukodystrophy; Cognitive dysfunction; Elderly; Correlation analysis

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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)0.001
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 score0.141
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.014
GPT teacher head0.247
Teacher spread0.234 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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