Objective: Kidney transplantation (KT) improves survival compared with dialysis, but kidney transplant recipients (KTRs) remain at high cardiovascular (CV) risk. Insulin resistance is a key contributor to CV morbidity. The Metabolic Score for Insulin Resistance (METS-IR) has shown promise for CV risk stratification, but data in KTRs are limited. This study evaluated METS-IR for predicting fatal and nonfatal CV events (a composite of myocardial infarction (MI), unstable angina or revascularization, stroke, and hospitalization for heart failure) in KTRs. Design and method: Adult KTR with more than 12 months post-transplant follow-up and at least two visits 6 months apart were included. Of 323 eligible patients, 272 without prior or incident CV disease were analyzed. Clinical and laboratory data were collected at baseline and follow-up. METS-IR was calculated using the standard formula. Continuous and categorical variables were compared using standard tests. Event-free survival was assessed by Kaplan–Meier analysis. Event-free survival was assessed by Kaplan–Meier analysis. The optimal METS-IR cut-off was determined by the Youden index and the predictive value was evaluated using ROC curves. Associations with CV outcomes were analyzed using Cox proportional hazards models. Results are reported as hazard ratios with 95% confidence intervals, P values 40 was associated with a twofold higher risk of fatal or nonfatal CV events (HR 2.1, 95% CI 1.16–3.80; P=0.01), confirmed by Kaplan–Meier analysis (log-rank P=0.01, Figure 1). METS-IR remained independently associated with CV outcomes after multivariable adjustment (Harrell's c 0.80–0.82).Conclusions: Our results support METS-IR as a practical tool for CV stratification in KTRs. Based on routine clinical parameters, it can be easily applied to identify high-risk patients early and guide interventions to reduce CV complications.
Picciotto et al. (Fri,) studied this question.