Abstract 12923: Development of a Novel Biomarker-based Risk Score for Heart Failure in Patients With Diabetes
Bibliographic record
Abstract
Introduction: Heart failure (HF) is a prognostically important complication of T2DM, the risk of which can be reduced by SGLT2 inhibitors. Clinical factors and circulating biomarkers of myocardial injury and hemodynamic stress predict risk of hosp for HF (HHF) in pts with T2DM. Aim: We aimed to develop and validate a biomarker-based risk score for HHF in pts with T2DM and to assess whether this score can identify high-risk pts with T2DM who have the greatest reduction in HHF risk with SGLT2 inhibition. Methods: Blood samples were prospectively collected from pts enrolled in SAVOR-TIMI 53 and DECLARE-TIMI 58 at randomization; high-sensitivity troponin T (hsTnT) and N-terminal B-type natriuretic peptide (NT-proBNP) were measured. We derived a risk score in 6106 pts with T2DM in the placebo arm of SAVOR-TIMI 53. Candidate variables (n=27) were assessed using Cox regression. The strongest indicators of HHF risk (based on Wald χ;2 values) were selected for inclusion and assigned integer weights. We externally validated the score in 7251 T2DM pts in the placebo arm of DECLARE-TIMI 58. Hazard ratios (HR) and absolute risk reductions (ARR) in HHF with the SGLT2 inhibitor dapagliflozin were assessed by baseline risk group. Results: The strongest independent indicators of HHF risk were NT-proBNP and hsTnT concentrations, and prior HF (each p<0.001). A risk score using these 3 variables identified a strong gradient of HHF risk (p-trend <0.001) in both the derivation and validation cohorts, with c-indices of 0.87 and 0.84, respectively. HRs with dapagliflozin were similar across risk groups (p-int = 0.64); however, ARRs were greater in those at higher baseline risk (p-trend <0.001), with high- (10-13 points) and very high-risk (14+ points) pts having 3.2% and 4.4% ARRs in KM estimates of HHF at 4 yrs, respectively ( Fig ). Conclusions: A novel biomarker-based risk score for HHF in pts with T2DM identifies pts at higher risk of HHF who derive greater absolute benefit from SGLT2 inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".