Comparison of ambulatory blood pressure parameters of hypertensive patients with and without chronic kidney disease

Chronobiol Int. 2013 Mar;30(1-2):145-58. doi: 10.3109/07420528.2012.703083. Epub 2012 Oct 25.


There is strong association between chronic kidney disease (CKD) and increased prevalence of hypertension, risk of end-organ damage, and cardiovascular disease (CVD). Non-dipping, as determined by ambulatory blood pressure (BP) monitoring (ABPM), is frequent in CKD and has also been consistently associated with increased CVD risk. The reported prevalence of non-dipping in CKD is highly variable, probably due to relatively small sample sizes, reliance only on a single, low-reproducibility, 24-h ABPM evaluation per participant, and definition of daytime and nighttime periods by arbitrary fixed clock-hour spans. Accordingly, we assessed the circadian BP pattern of patients with and without CKD by 48-h ABPM to increase reproducibility of the results. This cross-sectional study involved 10 271 hypertensive patients (5506 men/4765 women), 58.0 ± 14.2 (mean ± SD) yrs of age, enrolled in the Hygia Project. Among the participants, 3227 (1925 men/1302 women) had CKD. At the time of recruitment, 568/2234 patients with/without CKD were untreated for hypertension. Patients with than without CKD were more likely to be men and of older age, have diagnoses of obstructive sleep apnea, metabolic syndrome, diabetes, and/or obesity, plus have higher glucose, creatinine, uric acid, and triglyceride, but lower cholesterol, concentrations. In patients with CKD, ambulatory systolic BP (SBP) was significantly elevated (p < .001), mainly during the hours of nighttime sleep, independent of presence/absence of BP-lowering treatment. In patients without CKD, ambulatory diastolic BP (DBP), however, was significantly higher (p < .001), mainly during the daytime. Differing trends for SBP and DBP between groups resulted in large differences in ambulatory pulse pressure (PP), it being significantly greater (p < .001) for the entire 24 h in patients with CKD. Prevalence of non-dipping was significantly higher in patients with than without CKD (60.6% vs. 43.2%; p < .001). The largest difference between groups was in the prevalence of the riser BP pattern, i.e., asleep SBP mean > awake SBP mean (17.6% vs. 7.1% in patients with and without CKD, respectively; p < .001). The riser BP pattern significantly and progressively increased from 8.1% among those with stage 1 CKD to a very high 34.9% of those with stage 5 CKD. Elevated asleep SBP mean was the major basis for the diagnosis of hypertension and/or inadequate BP control among patients with CKD; thus, among the uncontrolled hypertensive patients with CKD, 90.7% had nocturnal hypertension. Our findings document significantly elevated prevalence of a blunted nocturnal BP decline in hypertensive patients with CKD. Most important, prevalence of the riser BP pattern, associated with highest CVD risk among all possible BP patterns, was 2.5-fold more prevalent in CKD, and up to 5-fold more prevalent in end-stage renal disease. Patients with CKD also presented significantly elevated ambulatory PP, reflecting increased arterial stiffness and enhanced CVD risk. Collectively, these findings indicate that CKD should be included among the clinical conditions for which ABPM is mandatory for proper diagnosis and CVD risk assessment, as well as a means to establish the best therapeutic scheme to increase CVD event-free survival.

Publication types

  • Comparative Study
  • Multicenter Study
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Blood Pressure
  • Blood Pressure Monitoring, Ambulatory / methods*
  • Circadian Rhythm
  • Cross-Sectional Studies
  • Female
  • Humans
  • Hypertension / complications*
  • Hypertension / physiopathology*
  • Hypertension / therapy
  • Kidney Failure, Chronic / complications*
  • Kidney Failure, Chronic / physiopathology*
  • Male
  • Middle Aged
  • Models, Statistical
  • Prevalence
  • Risk Factors
  • Time Factors