Analysis of the relationship between MCI and metabolic syndrome‐related factors in community residents over 50 years old
Bibliographic record
Abstract
Abstract Background Current studies had shown that cognitive impairment related to metabolic syndrome, but the relationship between the two has not determined absolutely. Mild Cognitive impairment (MCI) has a high incidence in cognitive impairment and is the early stage of dementia. The analysis of the correlation between MCI and metabolic syndrome related factors can help prevent and cure mild cognitive impairment in the early stag, and reduce the occurrence of dementia and reduce the social burden. Method We enrolled 235 cases in community over the age of 50 years. We used the Montreal Cognitive Assessment (MoCA) to assess cognitive function, screening the patients with mild cognitive impairment, and Analyzed the cognitive function and factors associated with metabolic syndrome, such as creatinine (CREA), urea(UA), blood glucose (GLU), low density lipoprotein cholesterol (LDL), very low density lipoprotein cholesterol (VLDL), body mass index (BMI), waist hip ratio (WHR), systolic blood pressure (SBP), diastolic blood pressure(DBP). Result The prevalence of mild cognitive impairment was about 79.2%)n=187( among community residents over 50 years old. Comparing to normal cognitive function group and mild cognitive impairment group, the blood glucose and systolic blood pressure showed significant differences( (P<0.05)),and no significant differences in CREA,UA,LDL,VLDL,BMI,WHR,DBP. Compared to normal blood glucose group, the score of executive, calculation and naming in high blood glucose were decreased, and the differences were significant (P<0.05). Compared to normal systolic blood pressure group, the Score of letter fluency in high systolic blood pressure was decreased, and the differences was significant (P<0.05). Conclusion The incidence of MCI in community residents over the age of 50 was high, which was closed related to blood glucose and systolic blood pressure. High blood glucose can reduce the patient’s ability of executive, calculation and language, and high systolic blood pressure can reduce letter fluency. Control the metabolic syndrome related factors, can reduce the incidence of mild cognitive impairment, benefit to the life quality of community residents.
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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 | 0.002 |
| 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".