Progression of diabetic kidney disease and trajectory of kidney function decline in Chinese patients with Type 2 diabetes

Autor: Guozhi Jiang, Andrea On Yan Luk, Claudia Ha Ting Tam, Fangying Xie, Bendix Carstensen, Eric Siu Him Lau, Cadmon King Poo Lim, Heung Man Lee, Alex Chi Wai Ng, Maggie Chor Yin Ng, Risa Ozaki, Alice Pik Shan Kong, Chun Chung Chow, Xilin Yang, Hui-yao Lan, Stephen Kwok Wing Tsui, Xiaodan Fan, Cheuk Chun Szeto, Wing Yee So, Juliana Chung Ngor Chan, Ronald Ching Wan Ma, Ronald C.W. Ma, Juliana C.N. Chan, Yu Huang, Si Lok, Brian Tomlinson, Stephen K.W. Tsui, Weichuan Yu, Kevin Y.L. Yip, Ting Fung Chan, Nelson L.S. Tang, Andrea O. Luk, Xiaoyu Tian, Claudia H.T. Tam, Cadmon K.P. Lim, Katie K.H. Chan, Alex C.W. Ng, Grace P.Y. Cheung, Ming-wai Yeung, Shi Mai, Fei Xie, Sen Zhang, Pu Yu, Meng Weng
Rok vydání: 2019
Předmět:
Zdroj: Kidney International. 95:178-187
ISSN: 0085-2538
DOI: 10.1016/j.kint.2018.08.026
Popis: Diabetes is a major cause of end stage renal disease (ESRD), yet the natural history of diabetic kidney disease is not well understood. We aimed to identify patterns of estimated GFR (eGFR) trajectory and to determine the clinical and genetic factors and their associations of these different patterns with all-cause mortality in patients with type 2 diabetes. Among 6330 patients with baseline eGFR >60 ml/min per 1.73 m2 in the Hong Kong Diabetes Register, a total of 456 patients (7.2%) developed Stage 5 chronic kidney disease or ESRD over a median follow-up of 13 years (incidence rate 5.6 per 1000 person-years). Joint latent class modeling was used to identify different patterns of eGFR trajectory. Four distinct and non-linear trajectories of eGFR were identified: slow decline (84.3% of patients), curvilinear decline (6.5%), progressive decline (6.1%) and accelerated decline (3.1%). Microalbuminuria and retinopathy were associated with accelerated eGFR decline, which was itself associated with all-cause mortality (odds ratio [OR] 6.9; 95% confidence interval [CI]: 5.6–8.4 for comparison with slow eGFR decline). Of 68 candidate genetic loci evaluated, the inclusion of five loci (rs11803049, rs911119, rs1933182, rs11123170, and rs889472) improved the prediction of eGFR trajectories (net reclassification improvement 0.232; 95% CI: 0.057-–0.406). Our study highlights substantial heterogeneity in the patterns of eGFR decline among patients with diabetic kidney disease, and identifies associated clinical and genetic factors that may help to identify those who are more likely to experience an accelerated decline in kidney function.
Databáze: OpenAIRE