Cognitive decline in elderly patients with type 2 diabetes is associated with glycated albumin, ratio of Glycated Albumin to glycated hemoglobin, and concentrations of inflammatory and oxidative stress markers
Bibliographic record
Abstract
Objective To investigate the correlations of cognitive function with glycated albumin (GA), the ratio of GA to glycated hemoglobin (GA/HbA 1c ), and the concentrations of interleukin-6 (IL-6) and superoxide dismutase (SOD) in elderly patients with type 2 diabetes mellitus (T2DM). Methods A total of 44 elderly T2DM patients were evaluated for cognitive function using the mini-mental state examination (MMSE) and the Montreal cognitive assessment (MoCA). Patients were then divided into two groups based on the MMSE and MoCA scores: a cognitive dysfunction group and a normal cognitive function group. The correlations of the MMSE and MoCA scores with GA/HbA 1c , GA, IL-6, and SOD were analyzed. Logistic regression analysis was used to identify independent influential factors for cognitive dysfunction. The predictive value of GA and GA/HbA 1c for cognitive dysfunction in elderly T2DM patients was evaluated by receiver operating characteristic (ROC) curve analysis. Results Among these patients, 28 had cognitive impairment. They had significantly higher GA/HbA 1c , increased GA and IL-6 levels, and lower SOD concentrations than the normal cognitive function group (all P < 0.05). GA/HbA 1c was negatively correlated with the MMSE ( r = −0.430, P = 0.007) and MoCA ( r = −0.432, P = 0.007) scores. SOD was positively correlated with the MMSE ( r = 0.585, P= 0.014) and MoCA ( r = 0.635, P= 0.006) scores. IL-6 was negatively correlated with the MoCA score ( r = −0.421, P= 0.015). Age and GA/HbA 1c were independent factors contributing to cognitive dysfunction. The areas under the ROC curves of GA and GA/HbA 1c for the diagnosis of cognitive dysfunction were 0.712 and 0.720, respectively. Conclusions GA and GA/HbA 1c are related to cognitive dysfunction in elderly patients with T2DM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".