ArticleLipids in health and disease2025
Insulin resistance surrogates predict major adverse cardiovascular events in patients with heart failure with preserved ejection fraction and chronic kidney disease: a retrospective cohort study.
Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Biomarkers for Screening and Diagnosis of Heart Failure in Cardiovascular-Kidney-Metabolic Syndrome: A Narrative Review.International journal of molecular sciences · 2026Review
- Hypertriglyceridemia in chronic kidney disease: pathophysiological mechanisms, cardiovascular risk, and emerging therapeutics.Lipids in health and disease · 2026Review
- Insulin Resistance at the Crossroads of Metabolic Inflammation, Cardiovascular Disease, Organ Failure and Cancer.Biomolecules · 2025Review
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Abstract
backgroundHeart failure with preserved ejection fraction (HFpEF) and chronic kidney disease (CKD) frequently coexist and portend a poor prognosis. Insulin resistance (IR) is implicated in cardiorenal pathophysiology, but practical surrogate IR indices for predicting risk in this high-risk and understudied population are lacking. This study evaluated and compared the prognostic value of four IR indices for major adverse cardiovascular events (MACE) in patients with HFpEF and CKD, and assessed their incremental value over the established Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score.
methodsThis retrospective analysis included 2412 patients admitted with HFpEF and CKD from 2012 to 2023. Baseline metabolic parameters computed four IR indices: triglyceride-glucose (TyG) index, TyG-body mass index (TyG-BMI), atherogenic index of plasma (AIP), and Metabolic Score for Insulin Resistance (METS-IR). The composite primary endpoint was MACE, defined as all-cause mortality or first heart failure hospitalization. Associations were evaluated using Kaplan-Meier analysis, multivariable Cox proportional hazards regression, and restricted cubic splines. Predictive capability was assessed using the area under the receiver operating characteristic curve (AUC), continuous net reclassification improvement (cNRI), and integrated discrimination improvement (IDI).
resultsOver a median follow-up of 1.58 years, 1122 (46.52%) MACE events occurred. Unadjusted analyses showed that all four IR indices were significantly associated with MACE risk. The TyG index demonstrated the strongest association (Q4 vs. Q1: adjusted hazard ratio [HR] = 2.60, 95% confidence interval [CI] 2.05-3.29, P < 0.001) and the best discrimination (AUC = 0.676). After adjustment, AIP (adjusted HR = 2.07) and METS-IR (adjusted HR = 1.42) remained significant predictors, whereas TyG-BMI did not (P = 0.09). TyG significantly outperformed the other indices in AUC, cNRI, and IDI (all P < 0.001). All IR indices added significant incremental prognostic value to the MAGGIC score (AUC 0.560), with TyG providing the largest improvement (AUC = 0.679, IDI = 0.052, cNRI = 0.189; all P < 0.001). These associations were consistent across prespecified subgroups.
conclusionIn patients with coexisting HFpEF and CKD, surrogate IR indices independently predicted MACE risk. The TyG index exhibited the strongest association and best predictive performance, offering significant incremental utility beyond the MAGGIC score. Integrating the TyG index into clinical practice could enhance risk stratification and management, directly improving patient outcomes by identifying those at highest risk for MACE.
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