Abstract 3640: Diabetes Mellitus is Associated with Increased Risk of Fatal and Non-Fatal Cardiovascular Events in Heart Failure Patients with Preserved Ejection Fraction - Findings From the Irbesartan in Heart Failure with Preserved Systolic Function Trial
Bibliographic record
Abstract
Background: Diabetes mellitus (DM), present in about a quarter of heart failure (HF) patients with reduced ejection fraction (HF-REF), is associated with increased risk of fatal and non-fatal cardiovascular (CV) events. Less is known about the prevalence and impact of DM in HF patients with preserved ejection fraction (HF-PEF). The prevalence and effect of DM on clinical outcomes were examined in patients enrolled in the Irbesartan in Heart Failure with Preserved Systolic Function Trial (I-PRESERVE). Methods: The I-PRESERVE trial randomized 4128 HF-PEF patients (EF≥45%) to receive irbesartan or placebo. The primary outcome of time to all-cause mortality or CV hospitalization (myocardial infarction [MI], stroke, worsening HF, atrial or ventricular arrhythmia or unstable angina) was compared between patients with and without DM over one year of follow-up. A combined HF endpoint (HF mortality and hospitalization) was also evaluated. Comparison of the outcomes between patients with and without DM was expressed as a hazard ratio (HR). The independent predictive role of DM was examined in a multivariable model (which included symptoms, signs, clinical history, CV examination, biochemical, and hematological findings). Results: In I-PRESERVE 27% had a history of DM at baseline. DM patients more often had a body mass index ≥30 (51% vs 38%), history of stroke (12% vs 9%), history of MI (28% vs 22%), estimated glomerular filtration rate <60 ml/min/1.73m 2 (34% vs 29%), and pulmonary congestion on chest x-ray (46% vs 38%). In patients with DM, 17% and 11% had primary and HF events, respectively within 1 year; for patients without DM, 11% and 6% had primary and HF events. In a multivariate analysis DM remained a significant predictor of primary events (HR 1.48; 95% CI 1.22, 1.79) or HF events (HR 1.67; 95% CI 1.32, 2.12). Conclusions: The prevalence of DM in HF-PEF is similar to that reported in HF-REF. HF-PEF patients with DM have a significantly worse outcome than those without DM and this increased risk is independent of other factors associated with a worse prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".