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Record W2354640201

A clinical research of risk factors in type 2 diabetic patients with cognitive impairment

2013· article· en· W2354640201 on OpenAlexaboutno aff
Yan Yong

Bibliographic record

VenueChina Modern Doctor · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGlycated hemoglobinMontreal Cognitive AssessmentBody mass indexDiabetes mellitusCognitionType 2 diabetesCognitive impairmentInternal medicineRisk factorType 2 Diabetes MellitusPhysical therapyPediatricsEndocrinologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective To study the risk factors in type 2 diabetic patients with cognitive impairment and provide clini cal evidences for early prevention and treatment of type 2 diabetic patients with cognitive impairment.Methods A total of 211 cases of patients with type 2 diabetes were selected and their cognitive function had been assessed with the Chinese version of Montreal Cognitive Assessment(MOCA).Based on the MOCA scores,they were divided into the cognitive impairment group(CI) and the normal group(NC).Their gender,age,the level of education,the nature of the work,hypertension,body mass index,glycohemoglobin were recorded.Results There was a statistically significant difference(P 0.05) between the two groups in age,the level of education,body mass index,and glycohemoglobin.Multiple stepwise regression analysis showed that age,the level of education and the level of glycohemoglobin were in dependent risk factors for MOCA scores.Conclusion Elderly,high body mass index,and high glycated hemoglobin are risk factors for cognitive impairment in type 2 diabetic patients.Highly educated is a protective factor for cognitive impairment in type 2 diabetic patients.Effective controlling of blood glucose,body weight,and increasing the level of education may contribute to preventing or delaying the occurrence of cognitive impairment in type 2 diabetic patients.

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)0.001
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 score0.006
Threshold uncertainty score0.378

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 head0.079
GPT teacher head0.360
Teacher spread0.280 · 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
Published2013
Admission routes1
Has abstractyes

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