Dysglycemia and Cognitive Dysfunction and Ill Health in People With High CV Risk: Results From the ONTARGET/TRANSCEND Studies
Bibliographic record
Abstract
CONTEXT: Avoidance of death, disability, dementia, and cognitive dysfunction (DDCD) are high priorities for people in aging societies. Evidence is mounting that these conditions are associated with impaired glycemic control. OBJECTIVE: The aim of this study was to assess the strength of relationship between the degree of glucose elevation and the development of the composite elements of DDCD that impede successful/healthy aging in a population at high risk for cardiovascular disease. DESIGN, SETTING, PARTICIPANTS, AND MAIN OUTCOME MEASURE: The relationship between baseline fasting plasma glucose values and DDCD was determined among 31 227 participants of the Ongoing Telmisartan Alone and in combination with Ramipril Global Endpoint Trial/Telmisartan Randomized Assessment Study in ACE intolerant Subjects With Cardiovascular Disease studies followed up for a median of 4.7 years. Several statistical models were used for the entire cohort and for those with and without normal fasting plasma glucose (ie, < 5.6 mmol/L) or a history of diabetes mellitus. RESULTS: After adjusting for age and sex, a diagnosis of diabetes mellitus was associated with an approximately 1.6 greater odds of DDCD; every 1 mmol/L higher baseline fasting plasma glucose value was associated with a 1.09 (95% confidence interval 1.07, 1.10) greater odds. These associations persisted in the multivariate models (a 1.08 95% confidence interval 1.07, 1.1 greater odds after adjustment for age, sex, education, and depression). CONCLUSION: In individuals with high cardiovascular risk, a direct relationship exists between levels of dysglycemia and the risk of DDCD. Further research is needed to understand the mechanisms underlying such an association and whether benefits can be derived from preventative strategies.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".