Abstract 19227: Weight History Influences the Likelihood of Subclinical Myocardial Injury
Bibliographic record
Abstract
Introduction: Obesity is associated with myocardial injury as reflected by levels of high-sensitivity cardiac troponin T (hs-cTnT), and the combination of obesity and elevated hs-cTnT is linked to markedly increased heart failure risk. The association of weight history with myocardial injury is unknown. Hypothesis: We hypothesized that prior obesity increases the likelihood of myocardial injury among individuals without clinical cardiovascular disease (CVD). Methods: We evaluated 9,472 participants (mean age 63 years) at ARIC Visit 4 (1996-99) with BMI ≥ 18.5 kg/m2 and without prior CVD. BMI (kg/m2) at Visit 4 and BMI calculated from self-reported weight at age 25 were categorized as normal weight (18.5-24.9), overweight (25-29.9) and obese (≥30). We then cross-tabulated BMI categories at Visit 4 and at age 25. A cumulative weight measure of “BMI years” was also calculated by taking the average of the BMI values at ARIC visits 1-4 and at age 25 (with BMI centered at 25 kg/m2) and multiplying the average by the number of years from age 25 to visit 4. The primary outcome was elevated hs-cTnT (≥14 ng/L) at Visit 4. Logistic regression was used to estimate the associations of cross-categories of BMI at the two time points and of BMI years with elevated hs-cTnT. Results: Within each Visit 4 BMI category, a higher BMI category at age 25 was associated with increased odds of elevated hs-cTnT, with the highest odds seen among those with obesity at both time points (OR 4.97 [95% CI: 3.39-7.29]) compared to those with normal weight at both time points. BMI years ranged from -307 to 1,205 ((kg/m2) x years). A graded positive association was seen between BMI years and myocardial injury (Figure), with each 100 higher BMI years linked to a 27% higher likelihood of elevated hs-cTnT. Conclusions: Prior obesity and greater cumulative weight from young adulthood increase the likelihood of subclinical myocardial injury, underscoring the importance of long-term weight control for reducing CVD risk.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".