Prevalence and pattern of cognitive dysfunction in young adults and middle-aged patients with type-2 diabetes
Bibliographic record
Abstract
A BSTRACT Background and Aims: With the world’s aging population, twin epidemics of type-2 diabetes (T2D) and dementia take a great toll on the healthcare burden. T2D carries a 2–3 times greater risk of developing cognitive impairment than controls. Early identification of cognitive impairment is important as it impairs diabetes self-management, making patients prone to complications. However, data about the assessment of cognitive impairment in T2D using a comprehensive cognitive battery is sparse in India. This study was undertaken to estimate the prevalence and pattern of cognitive impairment among young and middle-aged patients with T2D. Materials and Methods: A cross-sectional observational study was conducted in a tertiary care teaching hospital in Kolkata (2022–2024) among 125 Bengali-speaking T2D patients with formal education > class IV, aged between 20 and 60 years. The cognitive evaluation was done using the clinical dementia rating scale, mini-mental status examination (MMSE), Montreal cognitive assessment (MoCA), and Addenbrooke’s cognitive examination (ACE)-III. Statistical analyses were done by Jeffrey’s Amazing Statistics Program version 0.19 with appropriate tests (Chi-squared test, Mann–Whitney U test, Spearman correlation statistics, and logistic regression). P value < 0.05 was considered significant. Results: T2D patients reported a more subjective sensation of forgetfulness compared to the control group ( P = 0.001). MMSE was an insufficient screening tool to distinguish between these two groups. On MoCA and ACE-III, there was a significant difference in total scores between case and control groups (MoCA, P = 0.012 and ACE-III, P < 0.001). Based on ACE-III, 59.20% of T2D patients had cognitive impairment ( P < 0.001). The odds of having cognitive impairment in T2D were 3.72 times higher than in the control group ( P < 0.001). There was significant impairment of memory ( P < 0.001), fluency ( P = 0.020), and visuospatial ability ( P = 0.032). Females ( P = 0.010), less education ( P < 0.001), lower socioeconomic status ( P < 0.001), BMI < 23 kg/m 2 ( P = 0.049), peripheral neuropathy ( P = 0.001), hypothyroidism ( P = 0.007), anxiety ( P < 0.001), and depression ( P < 0.001) were significantly associated with cognitive impairment in diabetes. Conclusion: This is the first study from Eastern India to use a comprehensive cognitive scale validated in the local vernacular. Cognitive impairment is prevalent among a significant portion of middle-aged, educated individuals with T2D. Cognitive evaluation should be incorporated into diabetes management from the onset, with a focus on addressing modifiable factors.
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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 | 0.001 | 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".