Glycemic variability correlates with medial temporal lobe atrophy and decreased cognitive performance in patients with memory deficits
Bibliographic record
Abstract
Background In the past, researchers have observed a significant link between glycemia and dementia. Medial temporal atrophy (MTA) is regarded as a common marker of dementia. The correlation between glycemic variability and MTA is unclear, and it has not been determined whether glycemic variability can be utilized as a biomarker of MTA and cognitive performance. Methods The patients in a memory clinic who underwent brain MRI scans and cognitive assessments within the first week of their hospital visit, were enrolled. All participants underwent three fasting blood glucose and one HBA1c assessments on three self-selected days within 1 week of their first visit. The variability independent of the mean (VIM) was employed. Validated visual scales were used to rate the MTA results. The mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales were employed to assess the cognitive functions of the participants. Spearman’s correlation and regression models were used to examine the relationship between the MMSE and MoCA scales, and also determine the link between the MRI characteristics and cognitive status, where vascular risk factors, educational status, age, gender, and mean glucose parameters served as covariates. Results Four hundred sixty-one subjects completed the MMSE scale, while 447 participants completed the MoCA scale. Data analysis revealed that 47.72% of the participants were men (220/461), and the median age of the patients was 69.87 ± 5.37 years. The findings of Spearman’s correlation analysis exhibited a strong negative relationship between the VIM and MMSE score (r = −0.729, P < 0.01), and the MoCA score (r = −0.710, P < 0.01). The VIM was regarded as an independent risk factor for determining cognitive impairment in both the MMSE and MoCA assessments. The results were unaffected by sensitivity analysis. In addition, a non-linear relationship was observed between the VIM and MTA scores. Conclusion The variability in the blood glucose levels, which was presented as VIM, was related to the reduced cognitive function, which was reflected by MMSE and MoCA scales. The relationship between the VIM and the MTA score was non-linear. The VIM was positively related to the MTA score when the VIM was less than 2.42.
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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 | 0.002 |
| 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 | 0.001 |
| 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".