Cognitive Impairment in Frail Hypertensive Elderly Patients: Role of Hyperglycemia
Bibliographic record
Abstract
Endothelial dysfunction is a key hallmark of hypertension, which is a leading risk factor for cognitive decline in older adults with or without frailty. Similarly, hyperglycemia is known to impair endothelial function and is a predictor of severe cardiovascular outcomes, independent of the presence of diabetes. On these grounds, we designed a study to assess the effects of high-glucose and metformin on brain microvascular endothelial cells (ECs) and on cognitive impairment in frail hypertensive patients. We tested the effects of metformin on high-glucose-induced cell death, cell permeability, and generation of reactive oxygen species in vitro, in human brain microvascular ECs. To investigate the consequences of hyperglycemia and metformin in the clinical scenario, we recruited frail hypertensive patients and we evaluated their Montreal Cognitive Assessment (MoCA) scores, comparing them according to the glycemic status (normoglycemic vs. hyperglycemic) and the use of metformin. We enrolled 376 patients, of which 209 successfully completed the study. We observed a significant correlation between MoCA score and glycemia. We found that hyperglycemic patients treated with metformin had a significantly better MoCA score than hyperglycemic patients treated with insulin (18.32 ± 3.9 vs. 14.94 ± 3.8; p < 0.001). Our in vitro assays confirmed the beneficial effects of metformin on human brain microvascular ECs. To our knowledge, this is the first study correlating MoCA score and glycemia in frail and hypertensive older adults, showing that hyperglycemia aggravates cognitive impairment.
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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 | 0.000 | 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) | 0.001 | 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".