Sehoon Park1,2, Semin Cho3, Soojin Lee4, Yaerim Kim5, Sanghyun Park6, Yong Chul Kim3, Seung Seok Han3,7,8, Hajeong Lee3,8, Jung Pyo Lee7,8,9, Kwon Wook Joo3,7,8, Chun Soo Lim7,8,9, Yon Su Kim1,3,7,8, Kyungdo Han10, Dong Ki Kim11,7,8. 1. Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea. 2. Department of Internal Medicine, Armed Forces Capital Hospital, Gyeonggi-do, Korea. 3. Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea. 4. Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Seoul, Korea. 5. Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea. 6. Department of Medical Statistics, College of Medicine, Catholic University of Korea, Seoul, Korea. 7. Kidney Research Institute, Seoul National University, Seoul, Korea. 8. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea. 9. Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea. 10. Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea. 11. Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea dkkim73@gmail.com hkd917@naver.com.
Abstract
BACKGROUND: The association between variabilities in body mass index (BMI) or metabolic parameters and prognosis of patients with CKD has rarely been studied. METHODS: In this retrospective observational study on the basis of South Korea's national health screening database, we identified individuals who received ≥3 health screenings, including those with persistent predialysis CKD (eGFR <60 ml/min per 1.73 m2 or dipstick albuminuria ≥1). The study exposure was variability in BMI or metabolic parameters until baseline assessment, calculated as the variation independent of the mean and stratified into quartiles (with Q4 the highest quartile and Q1 the lowest). We used Cox regression adjusted for various clinical characteristics to analyze risks of all-cause mortality and incident myocardial infarction, stroke, and KRT. RESULTS: The study included 84,636 patients with predialysis CKD. Comparing Q4 versus Q1, higher BMI variability was significantly associated with higher risks of all-cause mortality (hazard ratio [HR], 1.66; 95% confidence interval [95% CI], 1.53 to 1.81), P [for trend] <0.001), KRT (HR, 1.20; 95% CI, 1.09 to 1.33; P<0.001), myocardial infarction (HR, 1.19; 95% CI, 1.05 to 1.36, P=0.003), and stroke (HR, 1.19; 95% CI, 1.07 to 1.33, P=0.01). The results were similar in the subgroups divided according to positive or negative trends in BMI during the exposure assessment period. Variabilities in certain metabolic syndrome components (e.g., fasting blood glucose) also were significantly associated with prognosis of patients with predialysis CKD. Those with a higher number of metabolic syndrome components with high variability had a worse prognosis. CONCLUSIONS: Higher variabilities in BMI and certain metabolic syndrome components are significantly associated with a worse prognosis in patients with predialysis CKD.
BACKGROUND: The association between variabilities in body mass index (BMI) or metabolic parameters and prognosis of patients with CKD has rarely been studied. METHODS: In this retrospective observational study on the basis of South Korea's national health screening database, we identified individuals who received ≥3 health screenings, including those with persistent predialysis CKD (eGFR <60 ml/min per 1.73 m2 or dipstick albuminuria ≥1). The study exposure was variability in BMI or metabolic parameters until baseline assessment, calculated as the variation independent of the mean and stratified into quartiles (with Q4 the highest quartile and Q1 the lowest). We used Cox regression adjusted for various clinical characteristics to analyze risks of all-cause mortality and incident myocardial infarction, stroke, and KRT. RESULTS: The study included 84,636 patients with predialysis CKD. Comparing Q4 versus Q1, higher BMI variability was significantly associated with higher risks of all-cause mortality (hazard ratio [HR], 1.66; 95% confidence interval [95% CI], 1.53 to 1.81), P [for trend] <0.001), KRT (HR, 1.20; 95% CI, 1.09 to 1.33; P<0.001), myocardial infarction (HR, 1.19; 95% CI, 1.05 to 1.36, P=0.003), and stroke (HR, 1.19; 95% CI, 1.07 to 1.33, P=0.01). The results were similar in the subgroups divided according to positive or negative trends in BMI during the exposure assessment period. Variabilities in certain metabolic syndrome components (e.g., fasting blood glucose) also were significantly associated with prognosis of patients with predialysis CKD. Those with a higher number of metabolic syndrome components with high variability had a worse prognosis. CONCLUSIONS: Higher variabilities in BMI and certain metabolic syndrome components are significantly associated with a worse prognosis in patients with predialysis CKD.
Authors: Jun Ling Lu; Kamyar Kalantar-Zadeh; Jennie Z Ma; L Darryl Quarles; Csaba P Kovesdy Journal: J Am Soc Nephrol Date: 2014-03-20 Impact factor: 10.121
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Authors: K G M M Alberti; Robert H Eckel; Scott M Grundy; Paul Z Zimmet; James I Cleeman; Karen A Donato; Jean-Charles Fruchart; W Philip T James; Catherine M Loria; Sidney C Smith Journal: Circulation Date: 2009-10-05 Impact factor: 29.690
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