Heart Failure Risk Stratification and Efficacy of Sodium-Glucose Cotransporter-2 Inhibitors in Patients With Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Patients with type 2 diabetes mellitus (T2DM) are at increased risk of developing heart failure. Sodium-glucose cotransporter-2 inhibitors reduce the risk of hospitalization for heart failure (HHF) in patients with T2DM. We aimed to develop and validate a practical clinical risk score for HHF in patients with T2DM and assess whether this score can identify high-risk patients with T2DM who have the greatest reduction in risk for HHF with a sodium-glucose cotransporter-2 inhibitor. Methods: We developed a clinical risk score for HHF in 8212 patients with T2DM in the placebo arm of SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients With Diabetes Mellitus–Thrombolysis in Myocardial Infarction 53). Candidate variables were assessed using multivariable Cox regression, and independent clinical risk indicators achieving statistical significance of P <0.001 were included in the risk score. We externally validated the score in 8578 patients with T2DM in the placebo arm of DECLARE-TIMI 58 (Dapagliflozin Effect on Cardiovascular Events–Thrombolysis in Myocardial Infarction 58). The relative and absolute risk reductions in HHF with the sodium-glucose cotransporter-2 inhibitor dapagliflozin were assessed by baseline HHF risk. Results: Five clinical variables were independent risk predictors of HHF: prior heart failure, history of atrial fibrillation, coronary artery disease, estimated glomerular filtration rate, and urine albumin-to-creatinine ratio. A simple integer-based score (0–7 points) using these predictors identified a >20-fold gradient of HHF risk ( P for trend <0.001) in both the derivation and validation cohorts, with C indices of 0.81 and 0.78, respectively. Although relative risk reductions with dapagliflozin were similar for patients across the risk scores (25%–34%), absolute risk reductions were greater in those at higher baseline risk (1-sided P for trend=0.04), with high-risk (2 points) and very-high-risk (≥3 points) patients having 1.5% and 2.7% absolute reductions in Kaplan-Meier estimates of HHF risk at 4 years, respectively. Conclusions: Risk stratification using a novel clinical risk score for HHF in patients with T2DM identifies patients at higher risk for HHF who derive greater absolute benefit from sodium-glucose cotransporter-2 inhibition. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifiers: NCT01107886 and NCT01730534.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".