Reduced Serum Levels of Klotho are Associated with Mild Cognitive Impairment in Patients with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Objective: The study objective was to investigate the serum levels of Klotho in patients with type 2 diabetes mellitus (T2DM) who had moderate cognitive impairment (MCI) and those without MCI and to determine its prediction of MCI in older patients with T2DM. Methods: Patients with diabetes were examined for MCI in 292 cases (using the Montreal Cognitive Assessment: MoCA score). Biomarkers and biochemical parameter data were accumulated. Results: Comparing T2DM patients with MCI (91 patients) and without MCI (101 patients), patients with MCI considerably reduced serum Klotho levels were observed. In all 292 hospitalized patients, serum Klotho levels were negatively correlated with age (r=-0.184, P=0.002), body mass index (BMI) (r=-0.151, P=0.010), glycosylated hemoglobin (HbA1c) (r=-0.197, P=0.001), creatinine (r=-0.178, P=0.002), and C-reactive protein (CRP) (r=-0.319, P<0.001). On the other hand, it is positively correlated with education (r=0.319, P<0.001) and high-density lipoprotein cholesterol (HDL-C) (r=0.272, P<0.001). Considering the findings of the multivariate logistic regression models, patients with type 2 diabetes who had reduced levels of serum Klotho (OR=0.987, 95% CI=0.980-0.994; P<0.001), lower HDL-C, increased levels of HbA1c, creatinine, and CRP, and limited years of formal education and a longer duration of T2DM, increase the risk of developing MCI. Conclusion: The results showed that diabetic patients with MCI have lower serum Klotho levels than diabetic patients without MCI. It might be possible to do a more extensive population-based prospective investigation to confirm the correlation between serum Klotho levels and cognitive impairment or dementia.
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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) | 0.001 | 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".