Fenofibrate and Heart Failure Outcomes in Patients With Type 2 Diabetes: Analysis From ACCORD
Bibliographic record
Abstract
OBJECTIVE: Patients with type 2 diabetes (T2D) have a high risk for developing heart failure (HF), which is associated with poor prognosis. Fenofibrate may reduce HF events through multiple mechanisms. We sought to study the effect of fenofibrate (vs. placebo) in HF outcomes among patients with T2D receiving simvastatin enrolled in the Action to Control Cardiovascular Risk in Diabetes lipid trial (ACCORD Lipid). RESEARCH DESIGN AND METHODS: We used Cox regression analysis with background glucose-lowering strategy as the stratification variable. The median follow-up was 4.7 years. RESULTS: A total of 5,518 patients were included. Median age was 62 years, and 31% were women. Prior HF history was present in 5% of the patients. The composite outcome of HF hospitalization or cardiovascular death occurred in 190 (6.9%) patients in the fenofibrate group vs. 228 (8.3%) in the placebo group: HR 0.82, 95% CI 0.68-1.00 (P = 0.048). The beneficial effect of fenofibrate to reduce HF hospitalizations or cardiovascular death was present among patients receiving standard glucose-lowering strategy, HR 0.64, 95% CI 0.48-0.85, and not among patients receiving intensive glucose-lowering strategy, HR 1.02, 95% CI 0.79-1.33 (Pinteraction = 0.017). A similar pattern was observed for HF hospitalizations alone. The effect of fenofibrate on blood lipids was not influenced by background glucose-lowering therapy in a clinically important manner. Fenofibrate caused more transient worsening estimated glomerular filtration rate (eGFR) events but slowed long-term eGFR decline. CONCLUSIONS: In patients with T2D treated with simvastatin, fenofibrate reduced the composite of HF hospitalizations or cardiovascular mortality, an effect that was seen predominantly in patients with standard background glucose-lowering therapy.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".