Prevalence of Cognitive Decline in Type 2 Diabetes Mellitus Patients: A Real-World Cross-Sectional Study in Mysuru, India
Bibliographic record
Abstract
The goal of this research is to study the prevalence of cognitive impairment in diabetes mellitus (DM) patients and establish the necessity of detecting and treating it early in these patients. A cross-sectional study was conducted at a tertiary care hospital in Mysuru for 4 months examined diabetic patients (test) and nondiabetic subjects (control) for cognitive decline using the Montreal Cognitive Assessment (MoCA) tool. Cognitive functions such as visuospatial/executive function, naming, attention, language, abstraction, delayed recall, and orientation were assessed in both groups. The diabetic group showed a significantly lower total MoCA score than the non-diabetic group (18.99 ± 0.48 and 26.21 ± 0.46, respectively; p < 0.001). Assessment of scores in diabetic patients demonstrated the significant influence of age demographics on cognitive impairment (p-value < 0.001). Furthermore, a higher proportion of diabetic patients displayed cognitive impairment despite a higher score in a single subdomain, making it evident that diabetes is diverse and multifactorial in origin, where oxidative stress and inflammatory responses play a predominant role. This study suggested that the local T2DM population residing in Mysuru (India) has a high prevalence of cognitive impairment, evident from poor performance in almost all cognitive domains assessed by MoCA. Future studies could examine the generalizability of cognitive function findings in diabetic patients across diverse geographic regions and ethnic groups, as well as investigate interventions such as lifestyle modifications and medication to prevent or delay cognitive decline in those with diabetes.
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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 | 0.001 | 0.003 |
| 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 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".