Risk factors for cognitive impairment in middle-aged type 2 diabetic patients: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate risk factors for cognitive impairment (CI) and explore the relationship between obesity and cognition in hospitalised middle-aged patients with type 2 diabetes (T2DM). METHODS: Subjects were divided into normal cognitive function (NCF) (n=320) and CI (n=204) groups based on the results of the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). The risk factors for CI were determined by logistic regression analysis and generalised linear modelling. The associations between obesity parameters (body mass index (BMI) and waist circumference (WC)) and cognitive ability were studied with the use of linear regression analysis, piecewise regression modelling and interaction analysis. The receiver operating characteristic curve analysis was used to examine the diagnostic value of influencing factors for cc RESULTS: The prevalence of CI was 38.9% in hospitalised middle-aged T2DM patients (median age, 58 years). Age, WC, hypoglycaemic episode within past 3 months and cerebrovascular disease (CVD) were identified as independent risk factors for CI, while the independent protective factors were education, diabetic dietary pattern, overweight and obesity. BMI was a protective factor for the MoCA score within a certain range, whereas WC was a risk factor for the MMSE and MoCA scores. The area under the curve for the combination of BMI and WC was 0.754 (p<0.001). CONCLUSION: Age, education, diabetic dietary pattern, WC, overweight, obesity, hypoglycaemic episode in 3 months and CVD may be potential influencing factors for the occurrence of CI in hospitalised middle-aged population with T2DM. The combination of BMI and WC may represent a good predictor for early screening of CI in this population. Nevertheless, more relevant prospective studies are still needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".