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Record W3019206424 · doi:10.1155/2020/4591938

Risk Factors for Cognitive Impairment in Patients with Type 2 Diabetes

2020· article· en· W3019206424 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Diabetes Research · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersDepartment of Science and Technology of Jilin ProvincePeople's Government of Jilin Province
KeywordsType 2 diabetesCognitive impairmentDiabetes mellitusMedicineCognitionPsychiatryEndocrinology

Abstract

fetched live from OpenAlex

Objectives . To investigate the risk factors for cognitive impairment in Chinese type 2 diabetes mellitus (T2DM) patients of advanced age and to identify effective biomarkers of mild cognitive impairment (MCI) in these patients. Methods . Chinese T2DM patients (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>120</mml:mn></mml:math>) aged 50–70 years were divided into groups with impaired (mild, moderate, and severe) and normal cognitive function based on Montreal Cognitive Assessment and Mini-Mental State Examination scores. Data regarding demographic characteristics, clinical features of diabetes, biochemical markers, and metabolomics were collected. Results . Age, educational level, duration of diabetes, fasting blood glucose (FBG), HbA1c, total cholesterol (TC), triglyceride (TG), and 24-hour urine protein were significantly associated with cognitive impairment in T2DM patients of advanced age. The severity of fundus retinopathy and the incidence of macrovascular disease also differed significantly among the groups (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>P</mml:mi><mml:mo>&lt;</mml:mo><mml:mn>0.05</mml:mn></mml:math>). Metabolomics analysis suggested that increased levels of glutamate (Glu), phenylalanine (Phe), tyrosine (Tyr), proline (Pro), and homocysteine (Hcy) and a decreased level of glutamine (Gln) were significantly associated with cognitive impairment in the T2DM patients (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>P</mml:mi><mml:mo>&lt;</mml:mo><mml:mn>0.05</mml:mn></mml:math>). Receiver operating characteristic curve analysis demonstrated that Glu, Gln, Phe, and Pro levels were significant predictors of cognitive impairment in the T2DM patients. Conclusions . Age, educational level, duration of diabetes, and the levels of FBG, HbA1c, TC, TG, and 24-hour urine protein were considered as independent risk factors for cognitive impairment in older T2DM patients. Macrovascular and microvascular diseases also were closely associated with cognitive impairment in these patients. Together, Glu and Gln levels may represent a good predictive biomarker for the early diagnosis of cognitive impairment in T2DM 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.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.036
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.350
Teacher spread0.313 · 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