Icosapent ethyl reduces CVD risk in cardiovascular-kidney-metabolic syndrome: REDUCE-IT CKM
Bibliographic record
Abstract
Abstract Background/Introduction Cardiovascular-kidney-metabolic (CKM) syndrome is a recently defined disorder linking metabolic syndrome (MetS) risk factors to chronic kidney disease and cardiovascular disease (CVD). REDUCE-IT (Reduction of Cardiovascular Events with Icosapent Ethyl-Intervention Trial), an international multicenter, double-blind, placebo-controlled trial, randomized statin-treated patients with hypertriglyceridemia (150-499 mg/dL) to icosapent ethyl (IPE) or placebo (4 grams/day). IPE therapy yielded a 25% reduction in major adverse CVD outcomes compared with placebo. The present analysis examined the incremental CVD risk of CKM in secondary prevention patients with MetS but without diabetes at baseline (n=2860) and the associated benefit of IPE therapy. Purpose To examine CVD risk associated with CKM (beyond MetS) and the effect of IPE treatment. Methods Efficacy analyses of treatment with IPE versus placebo were performed using the eGFR cutoffs of 90 and 60 mL/min/1.73 m2 in secondary prevention patients with MetS without diabetes in REDUCE-IT. Groups were identified with normal eGFR (≥ 90 mL/min/1.73 m2; n=609), eGFR < 90 mL/min/1.73 m2 (n=2251), and eGFR < 60 mL/min/1.73 m2 (n=565). Results In the placebo arm, CKM was associated with increased risk of the primary composite endpoint at eGFR < 90 mL/min/1.73 m2 (Hazard Ratio [HR], 1.44 [95% CI, 1.05, 1.96]; P=0.02) and at eGFR < 60 mL/min/1.73 m2 (HR, 1.87 [95% CI, 1.31, 2.69]; P=0.0005) compared with patients with normal renal function (eGFR ≥ 90 mL/min/1.73 m2). In patients with CKM (eGFR < 90 mL/min/1.73 m2), treatment with IPE compared with placebo was associated with significant reductions in the primary composite endpoint (HR, 0.72 [95% CI, 0.60, 0.87]; P=0.0005) and in total events (Rate Ratio [RR], 0.57 [95% CI, 0.46, 0.71]; P<0.0001). At eGFR < 60 mL/min/1.73 m2, the reduction in the primary composite endpoint and in total events was even more pronounced with IPE treatment (Figure); the numbers needed to treat to prevent an initial event in patients randomized to IPE with eGFR < 90 and < 60 mL/min/1.73 m2 were 18 and 9, respectively. Conclusions In REDUCE-IT secondary prevention patients, the CKM syndrome was associated with incremental CVD risk compared with MetS without diabetes and normal renal function. IPE treatment further reduced CVD risk in patients with CKM, thereby supporting a role for this therapy in affected patients. .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".