Risk factors of mild cognitive impairment in elderly type 2 diabetes mellitus
Bibliographic record
Abstract
Objective To analyze the risk factors of mild cognitive impairment(MCI)in elderly type 2 diabetic patients.Methods Montreal cognitive assessment scale(MoCA)and clinical dementia rating scale(CDR)were used as cognition assessment tool.200 elderly type 2 diabetic patients with MCI(MCI group)and 60 elderly type 2 diabetic patients with normal cognitive function(control group)were enrolled as subjects.Information of disease history,blood pressure,BMI,FBG,HbA1 c,blood lipid,serum creatinine,plasma homocysteine(HCY),folic acid and vitamin B12 of all subjects were collected.ResultsThere were statistically significant differences in the age,level of education,course of diabetes,HbA1 c,history of hypertension,course of hypertension,systolic blood pressure,level of HCY,folic acid and vitamin B12 between the MCI group and control group.No statistically significant differences were found in the gender composition,BMI,diastolic blood pressure,fasting blood glucose,blood lipid levels,serum creatinine levels between the MCI group and control group.MoCA scores were positively correlated with level of education and folic acid,and were negatively correlated with the age,HbA1 c,history of hypertension,course of hypertension,systolic blood pressure,level of HCY.Multiple regression analysis showed that age,HbA1 c,the history of hypertension and the level of HCY were independent risk factors for the MoCA scores.Conclusions Older age,poor blood glucose control,hypertension,hyperhomocysteinemia might be risk factors for MCI in elderly type 2 diabetic patients.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".