The relationships between atherosclerosis, heart disease, type 2 diabetes and dementia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Type 2 diabetes in the elderly is associated with increased incidence of vascular disease, particularly, atherosclerosis of large blood vessels. Together with other risk factors such as dyslipidemia, atherosclerosis increases the risk for coronary heart disease and stroke. Most studies that have examined the impact of type 2 diabetes and other heart disease risk factors on cognitive functions do not provide evidence that heart disease risk factors (with the possible exception of triglycerides) further increase the likelihood of observing cognitive deficits in diabetic patients. However, none of these studies used imaging techniques to evaluate atherosclerosis or evidence of cerebrovascular disease, such as infarctions. The few studies that have included brain imaging suggest that evidence of cerebrovascular disease further increases the risk for dementia in diabetic patients. The results of longitudinal studies suggest that diabetes is an independent risk factor for cognitive decline and dementia. The pattern of neuropsychological performance observed in type 2 diabetic patients appears to be the result of multiple interacting processes developing over time. In addition to the detrimental effects of protracted impaired glucose regulation on the central nervous system, type 2 diabetes pathology also encompasses the detrimental effects of associated complications such as cerebrovascular disease, which is likely the main cause of the observed processing speed/reaction time decrements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it