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The Prognostic Significance of Body Mass Index and Metabolic Parameter Variabilities in Predialysis CKD: A Nationwide Observational Cohort Study
Author(s) -
Sehoon Park,
Semin Cho,
Soojin Lee,
Yaerim Kim,
SangHyun Park,
Yong Chul Kim,
Seung Seok Han,
Hajeong Lee,
Jung Pyo Lee,
Kwon Wook Joo,
Chun Soo Lim,
Yon Su Kim,
Kyungdo Han,
Yon Su Kim
Publication year - 2021
Publication title -
journal of the american society of nephrology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.451
H-Index - 279
eISSN - 1533-3450
pISSN - 1046-6673
DOI - 10.1681/asn.2020121694
Subject(s) - medicine , body mass index , quartile , proportional hazards model , observational study , cohort , cohort study , retrospective cohort study , confidence interval
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 m 2 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.

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