Seokhun Yang1, Soongu Kwak1, You-Hyun Song1, Seung Seok Han2, Hye Sun Lee3, Shinae Kang4, Seung-Pyo Lee1. 1. Division of Cardiology and Cardiovascular Center, Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea. 2. Division of Nephrology, Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea. 3. Biostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, Seoul, South Korea. 4. Division of Endocrinology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea.
Abstract
OBJECTIVE: To analyze the relationship between time-serial changes in insulin resistance and renal outcomes. RESEARCH DESIGN AND METHODS: A prospective cohort of subjects from the general population without chronic kidney disease (CKD) underwent a biennial checkup for 12 years (n = 5,347). The 12-year duration was divided into a 6-year exposure period, where distinct HOMA for insulin resistance (HOMA-IR) trajectories were identified using latent variable mixture modeling, followed by a 6-year event accrual period, from which the renal outcome data were analyzed. The primary end point was adverse renal outcomes, defined as a composite of estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 in two or more consecutive checkups or albumin ≥1+ on urine strip. RESULTS: Two distinct groups of HOMA-IR trajectories were identified during the exposure period: stable (n = 4,770) and increasing (n = 577). During the event accrual period, 449 patients (8.4%) developed adverse renal outcomes, and the risk was higher in the increasing HOMA-IR trajectory group than in the stable group (hazard ratio 2.06, 95% CI 1.62-2.60, P < 0.001). The results were similar after adjustment for baseline clinical characteristics, comorbidities, anthropometric and laboratory findings, eGFR, and HOMA-IR. The clinical significance of increasing HOMA-IR trajectory was similar in three or four HOMA-IR trajectories. The increasing tendency of HOMA-IR was persistently associated with a higher incidence of adverse renal outcomes, irrespective of the prevalence of diabetes. CONCLUSIONS: An increasing tendency of insulin resistance was associated with a higher risk of adverse renal outcomes. Time-serial tracking of insulin resistance may help identify patients at high risk for CKD.
OBJECTIVE: To analyze the relationship between time-serial changes in insulin resistance and renal outcomes. RESEARCH DESIGN AND METHODS: A prospective cohort of subjects from the general population without chronic kidney disease (CKD) underwent a biennial checkup for 12 years (n = 5,347). The 12-year duration was divided into a 6-year exposure period, where distinct HOMA for insulin resistance (HOMA-IR) trajectories were identified using latent variable mixture modeling, followed by a 6-year event accrual period, from which the renal outcome data were analyzed. The primary end point was adverse renal outcomes, defined as a composite of estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 in two or more consecutive checkups or albumin ≥1+ on urine strip. RESULTS: Two distinct groups of HOMA-IR trajectories were identified during the exposure period: stable (n = 4,770) and increasing (n = 577). During the event accrual period, 449 patients (8.4%) developed adverse renal outcomes, and the risk was higher in the increasing HOMA-IR trajectory group than in the stable group (hazard ratio 2.06, 95% CI 1.62-2.60, P < 0.001). The results were similar after adjustment for baseline clinical characteristics, comorbidities, anthropometric and laboratory findings, eGFR, and HOMA-IR. The clinical significance of increasing HOMA-IR trajectory was similar in three or four HOMA-IR trajectories. The increasing tendency of HOMA-IR was persistently associated with a higher incidence of adverse renal outcomes, irrespective of the prevalence of diabetes. CONCLUSIONS: An increasing tendency of insulin resistance was associated with a higher risk of adverse renal outcomes. Time-serial tracking of insulin resistance may help identify patients at high risk for CKD.