Study of cognitive functions and their association with depression in type II diabetes mellitus
Bibliographic record
Abstract
Introduction: Individuals with diabetes have higher risk of developing depression, cognitive impairment, and dementia compared to those who do not have diabetes. The present study aims to assess the level of cognitive functions and the presence of depression in diabetes patients and healthy controls. The study also explores the level of cognition among the normal control, diabetes without depression, and diabetes with depression. Methods: In the present study, the presence of depression and the level of cognitive functions of 59 cases of diabetes mellitus type-2 were compared with an age- and gender-matched control group of 40 individuals. Clinical and demographic details were recorded on a semi-structured performa. Montreal Cognitive Assessment (MoCA) and Patient Health Questionnaire-9 (PHQ-9) were applied to both diabetes patients and healthy controls to assess the level of cognitive functions and the presence of depression, respectively. Results: On applying odds ratio (OR), it was observed in the present study that there were 93.50% more chances [OR 1.935 with 95% confidence interval (CI) being 0.481-7.789] of depression among diabetic cases as compared to the control group. Similarly, the chance of MoCA score being less than 26 was twice among the diabetic group as compared to the control group (OR 2.208 with 95% CI being 0.702-6.946). On application of the Chi-square test, the association of depression was significant with HBA1C level, level of education, and presence of complications. Conclusions: Patients with diabetes had almost double the risk of developing depression and poor cognitive functions as compared to the healthy control. High HbA1C level, level of education, and presence of complication in diabetes had a positive statistical association with depression. Thus, it is advisable to investigate patients with diabetes for the presence of depression and cognitive dysfunction by applying simple tools.
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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 | 0.000 | 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".