Abstract 14726: Serial Assessment of Cardiac Biomarkers and Risk of Cardiovascular Death or Hospitalization for Heart Failure in DECLARE-TIMI 58
Bibliographic record
Abstract
Introduction: Circulating cardiovascular (CV) biomarkers, including N-terminal pro-B type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT), are associated with risk of heart failure (HF) events in patients (pts) with type 2 diabetes (T2D). Less is known about the prognostic significance of changes in these biomarkers over time or the early effects of the SGLT2i dapagliflozin (dapa) on these markers. Methods: DECLARE-TIMI 58 was a randomized, placebo-controlled trial of dapa in 17,160 pts with T2D (median f/u = 4.2y). NT-proBNP & hsTnT (Roche) were measured at baseline & 6 mo. The outcome of interest was CV death (CVD) or hosp for HF (HHF). Outcome analyses were performed from a landmark of the 6-mo study visit with pts categorized by change in each biomarker over the first 6 mo. Hazard ratios were adjusted for baseline biomarker value, randomized treatment, age, sex, race, smoking, eGFR, prior HF, BMI, T2D duration, insulin use, CAD, prior MI, ischemic stroke, PAD, dyslipidemia, & hypertension. Linear mixed models were used to assess the effect of dapa on log-transformed NT-proBNP & hsTnT. Results: Serial NT-proBNP & hsTnT values were available in 13,459 pts (78%). Among pts allocated to placebo (n=6,698), NT-proBNP was more dynamic than hsTnT (≥20% change from baseline in 71% vs. 33% of pts; p<0.001). In the full cohort, independent of randomized treatment, there was a stepwise graded relationship between change in NT-proBNP & hsTnT and risk of CVD/HHF, whereby increases in either biomarker were associated with higher risk and decreases in either biomarker were associated with lower risk (p-trend for adj-HR <0.001 for each). Considered together, changes in the 2 markers were complementary ( Fig ; p<0.001). Dapa significantly reduced NT-proBNP (relative LS mean change, -6% [-4% to -8%]; p<0.001) but not hsTnT (0% [-1% to +1%]; p=0.92) over 6 mo. Conclusions: Early changes in hsTnT & NT-proBNP are associated with subsequent risk of CVD/HHF in pts with T2D.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".