Psychological and Radiological Study of Cognitive Impairment among Diabetic Patients (A Comparative Cross-Sectional Study)
Bibliographic record
Abstract
Objective of the study: To assess the cognitive impairment among diabetic patients and explore the potential alterations in various areas of the brain in a sample of diabetic patients in comparison to normal control subjects. Study Design: Cross-sectional study. Place and Duration of Study: Neuropsychiatry Department, Tanta University and Centre of Psychiatry, Neurology and Neurosurgery-Tanta University, at the Diabetes& endocrinology unit in the department of internal Medicine, Tanta University Hospitals and at the radiology department, Tanta University Hospitals during the interval from September 2018 to September 2019. This study was conducted on two groups Group A (60) diabetic patients compared to Group B (20) normal healthy individuals free from any cognitive impairment matched age and sex using psychometric scales e.g. Structured Clinical Interview (SCID) (American psychiatric association, 1994), Stanford-Binet Intelligence quotient (I.Q) fourth edition, Mini mental state examination (MMSE) or Folstein test, The Montreal Cognitive Assessment (MOCA) test, Trail making test (Part A& part B)& Stroop color_word test (Computerized version).and diffusion tensor imaging. All subjects aged from (18-65) years old. Results: patients with cognitive impairment represented 53.3% of the diabetic patients. Most of them presented with MCI (45%), while (8.3%) of them presented with dementia. The most affected executive functions in diabetic patients with impaired cognitive functions are delayed recall, attention, naming and language as assessed by MMSE& MOCA scales. There was negative correlation between HBA1C levels and fractional anisotropy in most of areas of interest of statistically significant value. Conclusion: The higher HBA1C levels (uncontrolled diabetes mellitus), the more cognitive deficits recorded through psychometric tests& DTI.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".