[Correlation between cognitive impairment and diabetic nephropathy in patients with Type 2 diabetes mellitus].
Bibliographic record
Abstract
OBJECTIVE: To explore the correlation between diabetic nephropathy (DN) and cognitive impairment through examining the cognitive function and the metabolism of the cerebrum in Type 2 diabetes mellitus patients at different stages of renal function. METHODS: Eighty six patients with Type 2 diabetes mellitus (T2DM) were enrolled for this study. According to the urinary albumin excretion rate (UAER), the patients were divided into a T2DM without DN group (DM group, n=33), an early DN group (DN-III group, n=26) and a clinical stage group (DN-IV group, n=27). Thirty healthy adults were selected as a control group (NC group). Biochemical indexes and UAER were measured, and glomerular filtration rate (GFR) was detected by single-photon emission computed tomography (SPECT). The cognitive function was measured by Montreal Cognitive Assessment (MoCA, Beijing version) and mini-mental state examination (MMSE). The peak areas of N-acetylasparte (NAA), creatine (Cr), choline-containing compounds (Cho) were detected by proton magnetic resonance spectroscopy (1H-MRS). RESULTS: 1) There was no statistical difference in MMSE scores between the DM group and the control group. The scores of MoCA in the DN-III group or in the DN-IV group were significant less than that in the NC group (F=3.66, P<0.05); 2) There was significant difference in left N-acetylaspartate (LNAA), left choline (LCho) among the diabetes groups. Compared with the DM group, the level of LNAA was decreased significantly (t=3.826, P<0.05) while the LCho was increased significantly (t=4.373, P<0.05) in the DN groups, with statistic difference between the 2 groups (t=3.693, P<0.05); 3) The MoCA scores of T2DM patients were negatively correlated with UAER (r=-0.285, P<0.05), while positively correlated with GFR (r=0.379, P<0.05); 4) Logistic regression analysis indicated that UAER and GFR were the major risky factors for diabetic cognitive impairment. CONCLUSION: Diabetic cognitive impairment is closely correlated with the nephropathy in patients with Type 2 diabetes. With the decline in glomerular filtration function, the cognitive disorder tends to be aggravated. The hippocampal brain metabolism may have some changes in left side of Cho/Cr in patients with diabetic nephropathy.
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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) | 0.002 | 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".