Abstract MP47: Diabetes, Prediabetes, and Short-Term Cardiovascular Risk and Death in Older Adults
Bibliographic record
Abstract
Background: Studies in middle-age adults have established prediabetes and diabetes as major cardiovascular disease (CVD) risk factors. Whether these associations persist among older adults is less clear. Methods: Older adults in the Atherosclerosis Risk in Communities (ARIC) Study who attended visit 5 (2013-2015; n = 5,791; ages 66-90) were followed for recurrent global CVD events (fatal or non-fatal myocardial infarction, stroke, and heart failure) and all-cause mortality. We used Cox proportional hazards and negative binomial regression to quantify and compare the independent associations of prediabetes (hemoglobin A1c [A1c]: 5.7-6.3%) and diabetes (prior diagnosis, medication use, or A1c ≥ 6.4%), traditional CVD factors, subclinical CVD (assessed using high sensitivity cardiac troponin [hs-cTnT]), and short-term risk of clinical outcomes in this older population. Results: Over a median follow-up of 4.6 years, there were 5,442 global CVD events (32% with at least one event) and 660 deaths. Diabetes, but not prediabetes, was significantly associated with both outcomes ( Table ). After adjustment for traditional risk factors, diabetes of shorter duration was no longer significantly associated with global CVD; however, diabetes of longer duration, renal disease, and subclinical CVD remained significantly associated with both outcomes. Higher risks of global CVD events and mortality were observed in Blacks compared to Whites. Conclusions: Prediabetes and short-term diabetes were not major independent predictors of short-term CVD events or death in older adults, especially compared to hypertension, kidney disease, long-term diabetes, and subclinical and prevalent CVD. Our results support focusing on these latter risk factors in older adults.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".