Evaluation of Neurocognitive Disorder in Patients with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Diabetes mellitus (DM) is a syndrome characterized by hyperglycemia due to absolute or relative deficiency of insulin or both. In India, an estimated 40 million people suffered from diabetes in 2007 and are expected to rise to 70 million by 2025 as per the Indian Diabetes Study 2011. Individuals with type 2 diabetes are at 60% greater risk for development of dementia compared to those without diabetes. For vascular dementia, but not for nonvascular dementia, the additional risk is that it is greater in women. Aim and Objective: To assess cognitive impairment among type 2 DM patients. Methods: In this cross-sectional study, 67 patients with type 2 DM and 66 control attending Put patient department (OPD) services between October 2018 and September 2020 were included. Both these groups were scored on the Montreal Cognitive Assessment (MoCA). The scores ranged from zero to 30. The scores of ≥26 were considered normal. A score of ≤22.1 in these people was considered as mild cognitive. Categorical data were represented in the form of frequencies and proportions. Chi-square test or Fischer exact test were used as test of significance for qualitative data. Correlations were performed with Pearson correlation coefficient. The P -value < 0.05 was considered as statistically significant after assuming all the rules of statistical tests. Results: Age and duration of diabetes had positive correlation with MoCA score which was not statistically significant. The body mass index (BMI) and waist circumference had negative correlation with MoCA score which was not statistically significant. Hemoglobin A1C (HbA1c) had negative correlation with MoCA score which was statistically significant. Conclusion: Older individuals with longer duration of DM and higher HbA1c levels showed higher cognitive impairment with MoCA score correlation. This study also highlights the early screening for all DM patients with easily available MoCA scores. Thus, helping in early recognition of mild cognitive impairment and preventing it from proceeding to 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".