Lijun Zhao1,2,3, Yutong Zou1,2, Lin Bai4, Li Zhou4, Honghong Ren1,2, Yucheng Wu1,2, Yiting Wang1,2, Shuangqing Li5, Qiaoli Su5, Linqiao Tang4, Yuancheng Zhao1,2, Huan Xu6, Lin Li6, Zhonglin Chai7, Mark E Cooper7, Nanwei Tong8, Jie Zhang4, Fang Liu9,10. 1. Department of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China. 2. Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, Chengdu, Sichuan, China. 3. Department of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China. 4. Histology and Imaging Platform, Core Facility of West China Hospital, Chengdu, Sichuan, China. 5. Division of General Practice, West China Hospital of Sichuan University, Chengdu, Sichuan, China. 6. Division of Pathology, West China Hospital of Sichuan University, Chengdu, Sichuan, China. 7. Department of Diabetes, Central Clinical School, Monash University, Melbourne, Australia. 8. Division of Endocrinology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, Sichuan, China. tongnw@scu.edu.cn. 9. Department of Nephrology, West China Hospital of Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China. liufangfh@163.com. 10. Laboratory of Diabetic Kidney Disease, Centre of Diabetes and Metabolism Research, West China Hospital of Sichuan University, Chengdu, Sichuan, China. liufangfh@163.com.
Abstract
PURPOSE: To investigate the prognostic value of metabolic syndrome (MetS) and its relationship with renal structure changes in patients with type 2 diabetes and associated diabetic nephropathy (DN). METHODS: 411 Chinese patients with type 2 diabetes and biopsy-confirmed DN were enrolled in this retrospective study. MetS was defined according to the modified criteria of the 2005 International Diabetes Federation. Baseline demographics and clinical information at the time of renal biopsy were extracted from the hospital's electronic medical records system. Renal pathological findings were assessed according to Renal Pathology Society system. Univariate and multivariate logistic regression analyses were performed to define the pathological covariates associated with MetS. A competing risk model, with death as the competing risk, was used to estimate the sub-distribution hazard ratio (SHR) of MetS for end-stage kidney disease (ESKD). RESULTS: 224 (55%) patients had MetS. Patients with MetS had poor renal function and more severe interstitial fibrosis tubular atrophy scores (IFTA) than those without MetS. Multivariate logistic regression analysis revealed that IFTA was significantly associated with MetS (odds ratio per score increase 1.45, 95% confidence interval [CI] 1.02-2.05). Of the patients with DN at risk, 40% of patients progressed to ESKD. After adjusting for renal function and pathological parameters, the presence of MetS was an independent predictor for progression to ESKD (SHR 1.93, 95% CI 1.34-2.79). The SHRs for progression to ESKD also increased as the number of MetS components increased. Additionally, adding the IFTA scores improved the prognostic power of a model that only contained MetS and clinical covariates for predicting future ESKD. CONCLUSION: MetS is an independent prognostic predictor of ESKD in patients with T2D and DN, while adding the IFTA scores increased the prognostic value of MetS for renal outcome.
PURPOSE: To investigate the prognostic value of metabolic syndrome (MetS) and its relationship with renal structure changes in patients with type 2 diabetes and associated diabetic nephropathy (DN). METHODS: 411 Chinese patients with type 2 diabetes and biopsy-confirmed DN were enrolled in this retrospective study. MetS was defined according to the modified criteria of the 2005 International Diabetes Federation. Baseline demographics and clinical information at the time of renal biopsy were extracted from the hospital's electronic medical records system. Renal pathological findings were assessed according to Renal Pathology Society system. Univariate and multivariate logistic regression analyses were performed to define the pathological covariates associated with MetS. A competing risk model, with death as the competing risk, was used to estimate the sub-distribution hazard ratio (SHR) of MetS for end-stage kidney disease (ESKD). RESULTS: 224 (55%) patients had MetS. Patients with MetS had poor renal function and more severe interstitial fibrosis tubular atrophy scores (IFTA) than those without MetS. Multivariate logistic regression analysis revealed that IFTA was significantly associated with MetS (odds ratio per score increase 1.45, 95% confidence interval [CI] 1.02-2.05). Of the patients with DN at risk, 40% of patients progressed to ESKD. After adjusting for renal function and pathological parameters, the presence of MetS was an independent predictor for progression to ESKD (SHR 1.93, 95% CI 1.34-2.79). The SHRs for progression to ESKD also increased as the number of MetS components increased. Additionally, adding the IFTA scores improved the prognostic power of a model that only contained MetS and clinical covariates for predicting future ESKD. CONCLUSION: MetS is an independent prognostic predictor of ESKD in patients with T2D and DN, while adding the IFTA scores increased the prognostic value of MetS for renal outcome.
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