Influencing factors of cognitive function in middle-aged patients with type 2 diabetes mellitus
Bibliographic record
Abstract
Objective To study the influencing factors of cognitive function in middle-aged patients with type 2 diabetes mellitus.Methods Montreal cognitive assessment(MoCA)(Beijing version) was applied for assessment of cognitive function.One hundred and ninety-nine type 2 diabetes patients(40-69 years old) were enrolled.Disease course,family history of diabetes,and data of body mass index(BMI),waist-hip ratio(WHR),fasting plasma glucose(FPG),hemoglobin A1c(HbA1c),blood pressure,blood lipids and carotid ultrasound were collected.Results Patients with duration of diabetes 5 years had lower MoCA score than those ≤5 years.Cognitive function was positively correlated with years of education,and negatively correlated with the history of hypertension,WHR,FPG,HbA1c,carotid artery intima-media thickness and carotid artery resistant index(RI)(P0.05).Multiple regression analysis showed that history of hypertension,carotid artery RI and HbA1c were the significant independent determinants for MoCA score.Conclusions Years of education,history of hypertension,carotid artery RI and glucose regulation were the influencing factors of cognitive function in middle-aged type 2 diabetes 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.
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) | 0.001 | 0.000 |
| 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 | 0.000 | 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".