Understanding the Association Between Type 2 Diabetes Mellitus and Cognitive Impairment: A Single-centre Experience
Bibliographic record
Abstract
Background: The global prevalence of diabetes mellitus has been increasing, leading to a rise in morbidity associated with the disease. While diabetic nephropathy, retinopathy and neuropathy are routinely screened in diabetic patients, the cognitive decline associated with diabetes is often overlooked. Purpose: The purpose of this study is to investigate the prevalence of cognitive impairment and its associated risk factors among patients with type 2 diabetes mellitus (T2DM). Methods: An observational cross-sectional study was conducted for two months. The Montreal Cognitive Assessment (MoCA) test, which consists of 30 questions, was used to assess cognitive function. In-depth clinical history along with glycaemic parameters were collected. The chi-square test was used to find out the association between categorical variables and cognitive impairment. Pearson's correlation test was performed to determine the correlation between glycaemic parameters and cognitive impairment. Results: A total of 96 patients participated in the study. The mean HbA1c (%) was 9.08 ± 1.73, and the mean MoCA score was 25.14 ± 1.63. Mild cognitive impairment (MCI) was noted in 56% patients. Attention was the most common cognitive domain defect found in all MCI patients-100%. Delayed recall and memory were the second most common cognitive domain defect found-92.5%. Higher HbA1c, high FBS and higher PPBS were found to be statistically associated with MCI. A negative correlation was found between glycaemic parameters (HbA1c, FBS and PPBS levels) and MoCA scores. Conclusion: More than half of our study participants reported mild cognitive impairment. It highlights the need for the implementation of routine cognitive testing for diabetes patients. There is a strong negative correlation between MoCA scores and parameters of glycaemic control; higher levels of HbA1c, FBS, and PPBS are seen in people with a lower MoCA score, indicating mild cognitive impairment. Further studies are needed to evaluate whether improving glucose levels helps in improving cognition or not.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".