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Prognostic value of visit-to-visit systolic blood pressure variability related to diabetic kidney disease among patients with type 2 diabetes

Yu, Zhe-Bina,*; Wang, Jian-Binga,c,*; Li, Diea; Chen, Xue-Yua; Lin, Hong-Bob; Chen, Kuna,c,d

doi: 10.1097/HJH.0000000000002038

Background: This study aimed to evaluate the impact of visit-to-visit variability (VVV) of blood pressure on the risk of diabetic nephropathy and whether it provides additional predictive information among patients with type 2 diabetes mellitus (T2DM) in China.

Methods: We included 12 630 T2DM patients during January 2008–December 2012 using a retrospective cohort design. VVV of SBP was assessed as standard deviation, coefficient of variation and variation independent of mean of the blood pressure readings during the measurement period. Hazard ratios and 95% confidence intervals were estimated for the associations of variability in SBP with risk of diabetes nephropathy by using Cox proportional hazards regression models. Risk prediction ability was assessed using C statistic, integrated discrimination improvement (IDI) and net reclassification index (NRI).

Results: We found a dose–response relationship across quartiles of VVV SBP (P trend < 0.001). Hazard ratio in the highest quartile of SD SBP (≥9.2 mmHg) was 1.49 (1.16–1.93) as compared with the lowest quartile (<4.8 mmHg) after adjusted for mean SBP values, max SBP values and other covariates. Addition of SD SBP significantly improved risk prediction for diabetic kidney disease (DKD) [C statistic (from 0.664 to 0.673), IDI (0.0011, 95% CI: 0.0003–0.0104) and NRI (0.053, 95% CI: 0.0017–0.113)]. Results remained similar across different subgroups, sensitivity analyses or using coefficient of variation and variance independent of mean.

Conclusion: VVV of SBP is a significant risk factor of DKD among T2DM patients on top of mean and max BP values, which provides additional significant predictive information.

aDepartment of Epidemiology and Health Statistics, School of Public Health, Zhejiang University, Hangzhou

bCenter for Disease Control and Prevention of Yinzhou District, Ningbo

cResearch Center for Air Pollution and Health

dCancer Institute, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China

Correspondence to Dr Kun Chen, Department of Epidemiology and Health Statistics, Zhejiang University School of Public Health, 866 Yuhangtang Road, Hangzhou 310058, China. Tel: +86 0571 88208190; e-mail:

Abbreviations: ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor blocker; CCB, calcium channel blockers; DKD, diabetic kidney disease; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; IDI, integrated discrimination improvement; NRI, net reclassification index; SD, standard deviation; T2DM, type 2 diabetes mellitus; VIM, variance independent of mean; VVV, visit-to-visit variability

Received 7 October, 2018

Revised 19 November, 2018

Accepted 5 December, 2018

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