Insulin resistance drives cognitive impairment in hypertensive pre-diabetic frail elders: the CENTENNIAL study
Bibliographic record
Abstract
AIMS: Pre-diabetes is a condition that confers an increased cardiovascular risk. Frailty is very common in hypertensive patients, and insulin resistance has been linked to frailty in older adults with diabetes. On these grounds, our aim was to evaluate the association between insulin resistance and cognitive impairment in hypertensive and pre-diabetic and frail older adults. METHODS AND RESULTS: We studied consecutive pre-diabetic and hypertensive elders with frailty presenting at the Avellino local health authority of the Italian Ministry of Health (ASL AV) from March 2021 to March 2022. All of them fulfilled the following inclusion criteria: a previous diagnosis of hypertension with no clinical or laboratory evidence of secondary causes, a confirmed diagnosis of pre-diabetes, age >65 years, Montreal Cognitive Assessment (MoCA) Score <26, and frailty. We enrolled 178 frail patients, of which 141 successfully completed the study. We observed a strong inverse correlation (r = -0.807; P < 0.001) between MoCA Score and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). The results were confirmed by a linear regression analysis using MoCA Score as dependent variable, after adjusting for several potential confounders. CONCLUSION: Taken together, our data highlight for the first time the association between insulin resistance and global cognitive function in frail elders with hypertension and pre-diabetes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".