Biochemical and morphometric methods for assessing cognitive impairment in patients with type 2 diabetes
Bibliographic record
Abstract
Aim. To study the features of biochemical and morphometric parameters in patients with type 2 diabetes (T2D) and cognitive impairment (CI). Material and methods. The experimental group included 72 patients with CI and T2D, the control group − 20 patients with T2D and without CI. We used the Montreal Cognitive Scale (MoCA) to assess the presence of CI. We also evaluated the levels of 1,5-anhydroglucitol (1,5-AG), continuous glucose monitoring (CGM), and data of brain magnetic resonance imaging (MRI). Results. We revealed that patients with T2D and CI have high HbA1c levels, but there was no significant difference of 1,5-AG levels between the groups. In patients with CI, we also established a decrease in gray and white matter surface area, as well as subcortical structures (the hippocampus, nucleus accumbens and putamen on both sides; the amygdala and globus pallidus on the right). The severity of CI correlated with polyneuropathy severity. In patients with proliferative retinopathy, there was a decrease in the volume of the caudate nucleus, globus pallidus, putamen and nucleus accumbens. Conclusion. The study revealed that patients with T2D with CI have worse levels of carbohydrate metabolism parameters, as well as a decrease in the cortical and subcortical brain structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".