Positive correlation between cognitive impairment and renal microangiopathy in patients with type 2 diabetic nephropathy: a multicenter retrospective study
Bibliographic record
Abstract
OBJECTIVE: This study was performed to explore the correlation between cognitive impairment and renal microangiopathy in patients with type 2 diabetic nephropathy (T2DN) by detecting changes in cognitive function and cerebral metabolism in these patients with different stages of T2DN. METHODS: Prospectively maintained databases were reviewed from 2006 to 2017. Blood biochemical indexes and the urinary albumin excretion rate (UAER) were measured in all participants. Cognitive function was assessed by the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA). Cognitive impairment was the primary endpoint. Renal microangiopathy was the secondary endpoint. Pearson correlation analysis was used to assess correlations. RESULTS: Two hundred sixteen patients with type 2 diabetes mellitus (T2DM) were divided into three groups according to their UAER: T2DM without nephropathy (n=72), early T2DM with nephropathy (n=74), and the clinical stage of early T2DM with nephropathy (n=70). Healthy participants were selected as the normal control group (n=70). Pearson correlation analysis demonstrated that the total MMSE and MoCA score was negatively correlated with the UAER (r=-0.327) and positively correlated with the estimated glomerular filtration rate (r=0.428) in patients with T2DN. CONCLUSIONS: The present study showed a positive correlation between cognitive impairment and renal microangiopathy in patients with T2DN.
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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) | 0.000 | 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".