1262-P: Effect of Cardiovascular Risk Factor Control on Mortality in Older Adults—Findings from the Costa Rican Longevity and Healthy Aging Study
Bibliographic record
Abstract
Introduction: The Costa Rican Longevity and Healthy Aging Study prospective cohort examined older adults' health status in Costa Rica. We investigated the influence of goal attainment on controlling cardiovascular risk factors (CVRFs): BMI, A1C, exercise, blood pressure, and smoking, along with their correlation with all-cause mortality. Methodology: Survival data from the initial 2005 visit to 2019 included 1943 participants. Categorization was based on meeting targets for five CVRFs. Hazard ratios for all-cause mortality were estimated, adjusting for age, sex, C-reactive protein category, and history of previous cardiovascular events. Results: The mean age for the cohort was 73.3 years, with 54.0% females. More than 2 hours of weekly exercise, controlled BMI, and A1C reduced all-cause mortality (aHR 0.77, 0.78, 0.72, respectively, p<0.001) (Figure 1a). Additionally, having 4 (aHR 0.50, p=0.035) or 5 (aHR 0.34, p=0.007) controlled CVRFs reduced overall mortality within the cohort. Conclusions: A controlled A1C and BMI and engaging in exercise correlated with reduced mortality in the Costa Rican elderly population. Additionally, aHRs for all-cause mortality decreased as more CVRFs were controlled, emphasizing the crucial role of managing these multiple factors in this population. Disclosure J. Calvo Marin: Speaker's Bureau; Novo Nordisk, AstraZeneca. G. Torrealba-Acosta: None. K. Ernest-Suarez: Advisory Panel; Janssen Pharmaceuticals, Inc. Consultant; Janssen Pharmaceuticals, Inc. Speaker's Bureau; Janssen Pharmaceuticals, Inc. Advisory Panel; Pfizer Inc. Speaker's Bureau; Pfizer Inc. Advisory Panel; AstraZeneca. Consultant; AstraZeneca. Speaker's Bureau; AstraZeneca. Advisory Panel; Takeda Canada. Speaker's Bureau; Sandoz.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".