Assessment implement and its related factors in type 2 diabetic patients with mild cognitive impairment
Bibliographic record
Abstract
Objective To study the assessment implement and its related factors in type 2 diabetic patients with mild cognitive impairment(MCI).Methods Montreal Cognitive Assessment(MoCA)(Beijing Version)was chosen as cognition assessment implement.58 type 2 diabetic patients with MCI were enrolled as the research group and 30 type 2 diabetic patients with normal cognitive function as control.HbA_(1C),blood lipid,urine microalbumin,liver and renal functions were measured in all subjects.Results Compared with control group,the blood levels of HbA_(1C)[(10.48±2.38 vs 9.28±2.19)%,P<0.05],total cholesterol[(4.87±1.18 vs 4.18±1.04)mmol/L,P<0.01],and low-density lipeprotein-cholesterol[LDL-C,(2.97±0.87 vs 2.37±0.61)mmol/L,P<0.01]increased,and high-density lipoprotein-cholesterol decreased[(1.084±0.34 vs 1.25±0.33)mmoL/L,P<0.05]in MCI group.There were significant differences in the duration of diabetes mellitus,diabetic retinopathy,body mass index,and abdominal circumference between MCI group and control group(all P<0.05).There were no significant differences in blood triglycerides,alanine aminotransferase(ALT),aspartate aminotransferase(AST),creatinine,and urine microalbumin between the two groups.MoCA scores were negatively correlated with HbA_(1C)(r=-0.396,P=0.002)and LDL-C(r=-0.275,P=0.036)in MCI group.Multiple regression analysis showed that HbA_(1C) was a significantly independent determinant for the MoCA scores.Conclusion The risk factors such as longer duration of diabetes mellitus.more diabetea mellitus complications,obesity,dyslipidemia,and inefficient control of blood glucoge all contribute to the development and aggravation of cognitive impairment.Therefore,good control of blood glucose and lipids,and reduction of complication and body weight may help to improve the cognitive function. Key words: Diabetes mellitus; type 2; Mild cognitive impairment; Montreal Cognitive Assessment
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".