Abstract
Both nocturnal hypertension and nondipping pattern are associated with target organ damages (TODs); however, no data exist with respect to Chinese patients with chronic kidney disease (CKD). The authors recruited 1322 patients with CKD admitted to our hospital division and referred with data in this cross‐sectional study. Patients with nocturnal systolic hypertension had a lower estimated glomerular filtration rate (eGFR) and higher left ventricular mass index (LVMI) and carotid intima‐media thickness (cIMT) compared with patients with normal nocturnal systolic blood pressure (SPB; all, P<.001), while patients in the dipper and nondipper groups had similar levels of eGFR, LVMI, and cIMT when the patients had a similar nocturnal SBP. Factorial‐designed analysis of variance indicated that the main effect of nocturnal SBP was significant for all TOD differences (all, P<.001), but no significance existed with respect to the main effect of the dipper pattern and an interaction between the two factors (all, P>.05). Nocturnal systolic hypertension, rather than nondipping pattern, was an independent risk factor for TOD in CKD patients. Nocturnal hypertension, rather than a nondipping pattern, was better associated with TOD in CKD patients.
Chronic kidney disease (CKD) has become an important public health problem in China. The number of patients with CKD in China is approximately 119.5 million based on a prevalence of CKD in China of 10.8%.1 The prevalence of hypertension in patients with CKD is very high, escalating with diminishing renal function. High blood pressure (BP) is known to exacerbate all forms of CKD and increase the risk for progression to end‐stage renal disease and cardiovascular disease through excessive mechanical and oxidative stresses.2 Hypertension is an important modifiable risk factor for these complications3; therefore, regulation of BP may substantially reduce the risk of cardiovascular events and slow the decline of kidney function.4
Clinical trials that have evaluated different BP targets have utilized clinic BPs, which are also the main focus of current guidelines for the management of hypertension.5 More attention is now being paid to other forms of BP measurement, including ambulatory BP monitoring (ABPM), which allows for the assessment of BP throughout the day and night. ABPM can provide the following information: mean BP levels; diurnal BP levels; diurnal variation in BP; and short‐term BP variability. Nocturnal hypertension6, 7 and a nondipping BP pattern8, 9 are regarded as important predicting factors in the general population and patients with hypertension; however, both nocturnal hypertension and a nondipping pattern are often present together, thus confounding the association with risk and prognosis. There is only one report involving patients with hypertension from the Spanish Ambulatory Blood Pressure Monitoring Registry, which showed that a nondipping pattern is related to more advanced disease (reduced renal function and clinical evidence of cardiovascular disease), whereas nocturnal hypertension is associated with albuminuria.10
Patients with CKD were considered to be the “highest‐risk group” for subsequent cardiovascular events, and treatment recommendations based on stratification of CVD risk should take into account the highest‐risk status.11 Moreover, these CKD patients had a higher prevalence of nocturnal hypertension, a nondipping pattern, and a reversed dipping BP pattern,12, 13 thus we cannot consider the same phenomenon to exist in CKD patients as hypertensive patients and the general population. There are no reports regarding the relationship between nocturnal hypertension and a nondipping pattern in patients with CKD. We evaluated the association between nocturnal hypertension and a nondipping pattern, examined separately, and target organ damage (TOD). For this purpose, we analyzed patients with CKD by stratifying them into four groups depending on absolute nocturnal systolic blood pressure (SBP) and a nocturnal dipping pattern, which allowed us to specifically address those factors related to nocturnal hypertension in the absence of a nondipping pattern and those factors related to a nondipping pattern in the absence of nocturnal hypertension.
Materials and Methods
Study Population
The study protocol was approved by the ethics committee of the Third Hospital of Sun Yat‐Sen University (Guangdong, China). All of the study participants provided written informed consent to be included in the study.
From May 2010 to December 2014, 1793 consecutive CKD inpatients comprised the cohort for this cross‐sectional study. Exclusion criteria were: undergoing treatment with corticosteroids or hormones; acute changes in the estimated glomerular filtration rate (eGFR) >30% in the previous 3 months; pregnancy; history of abuse of drugs or alcohol; night work or shift‐work employment; acquired immunodeficiency syndrome; cardiovascular disorders (unstable angina pectoris, heart failure, life‐threatening arrhythmia, atrial fibrillation and grade III or IV retinopathy); intolerance to ABPM; inability to communicate and comply with all of the study requirements; on maintenance dialysis; and use of any antihypertensive drug in the previous month.
A total of 347 patients were ruled out because they had undergone some type of antihypertensive treatment. A total of 124 patients were excluded because of deficiency of clinical or ultrasonographic data.
Finally, 1322 CKD patients were enrolled in this study. In terms of causes of renal diseases, 749 patients had chronic glomerulonephritis, 168 cases had diabetic nephropathy, 67 had hypertensive nephropathy, 96 had lupus nephritis, and 242 had other causes of renal disease. We analyzed these patients with CKD by stratifying them into four groups depending on absolute nocturnal SBP and nocturnal dipping pattern: normal nocturnal SBP and dipper, normal nocturnal SBP and nondipper, nocturnal systolic hypertension (NSH) and dipper, and NSH and nondipper.
BP Measurements
BP was measured at the physician's office with a calibrated mercury sphygmomanometer after a 5‐minute rest in a sitting position. BP values were estimated as a minimum of three BP measurements at intervals of ≥1 minute. Reported values of clinic BP were the mean of values. These patients then underwent 24‐hour ABPM using a TM‐2430 Monitor (A&D, Tokyo, Japan). Cuff size was chosen based on arm circumference and fixed to the nondominant arm. BP readings were obtained in the morning at three points from 7 am to 10 am using a mercury sphygmomanometer by a physician who did not have access to ABPM values. BP was then recorded every 15 minutes from 7 am to 10 pm and every 30 minutes from 10 pm to 7 am. Monitoring was performed on a working day. Patients were asked to attend to their usual activities but to keep motionless at the time of measurement. Patients had no access to ABPM values. Strenuous physical activity was discouraged in all patients during the monitoring period, and their daily activities were comparable. BP series were eliminated from the analyses if: >30% of the measurements were lacking; they had missing data for >3‐hour spans; or they were collected from patients who were experiencing an irregular rest‐activity schedule or a nocturnal sleep span <6 hours or >12 hours during monitoring.
The cohorts were divided into four groups depending on nocturnal SBP and dipping pattern: group 1 consisted of patients with normal nocturnal SBP (<120 mm Hg) and dipping (>10%), group 2 consisted of patients with normal nocturnal SBP and nondipping (≤10%), group 3 consisted of patients with NSH (nocturnal SBP ≥120 mm Hg) and dipping, and group 4 consisted of patients with both NSH and nondipping.10
Target Organ Assessment
Renal Assessment
Serum concentrations of creatinine (Scr) were measured by an enzymatic method traceable to isotope dilution mass spectrometry. The eGFR was calculated using a modified version of the Modification of Diet in Renal Disease (MDRD) equation based on data from Chinese patients with CKD as follows:14
Cardiac Assessment
Cardiac structure was assessed by two investigators trained for this purpose before starting the study. Left ventricular mass (LVM), systolic function, and diastolic function were assessed using two‐dimensional echocardiography. Linear measurements of end‐diastolic interventricular septal wall thickness (IVSd), end‐diastolic left ventricular internal dimension (LVIDd), and end‐diastolic posterior wall thickness (PWTd) were obtained from M‐mode tracings. LVM was calculated using the following formula:15
LVM index (LVMI) was obtained by calculating the ratio of LVM to body surface area.16
Carotid Ultrasonography
Carotid intima‐media thickness (cIMT) was assessed by two trained investigators before study commencement. A MicroMaxx Ultrasound system paired with a 5‐ to 10‐MHz multifrequency high‐resolution linear transducer (SonoSite, Bothell, WA) with Sono‐Calc IMT software was used for taking automatic measurements of cIMT. This was achieved by averaging three measurements taken on each carotid artery (anterior, lateral, and posterior directions) and measuring the distance between the leading edge of the lumen‐intima interface and the leading edge of the collagenous upper layer of the adventitia using high‐resolution B‐mode ultrasonography.
Collection of Other Data
We collected urine samples from 7 am to 7 am the next day to detect the extent of proteinuria and sodium levels over 24 hours. These patients were asked to void their bladders at 7 am. Proteinuria was measured by immunoturbidimetry. In addition, medical history, including demographic and laboratory data (hemoglobin, albumin, globulin, calcium, phosphate, intact parathyroid hormone [iPTH], serum fasting glucose, cholesterol, triglycerides [TGs], high‐density lipoprotein cholesterol [HDL‐C], low‐density lipoprotein cholesterol [LDL‐C], homocysteine, uric acid, serum cystatin C, blood urea nitrogen [BUN]) were obtained at the initial study visit. All these experimental data were measured using a 7180 Biochemistry Auto‐Analyzer (Hitachi, Tokyo, Japan).
Definitions
Clinic hypertension was defined as clinic BP ≥140/90 mm Hg and ambulatory was defined as 24‐hour BP ≥130/80 mm Hg.12
ABPM daytime and ABPM nocturnal were defined as time intervals from 7 am to 10 pm and from 10 pm to 7 am, respectively. These definitions were based on patients' schedule.
Nocturnal systolic hypertension was defined as nocturnal SBP ≥120 mm Hg and dipping was defined as a decline in the nocturnal SBP of >10%, whereas nondipping was defined as a decline in the nocturnal SBP of ≤10%.17
CKD was defined as the presence of kidney damage or decreased renal function (eGFR <60 mL/min per 1.73 m2) for ≥3 months according to guidelines set by the Kidney Disease Outcomes Quality Initiative.18
Diabetes mellitus (DM) was defined as the need for antidiabetic drugs or meeting the diagnostic criteria for DM specified by Chinese Guidelines for Diabetes Prevention and Treatment: (1) symptoms of DM and casual blood glucose >11.1 mmol/L and (2) fasting blood glucose >7.0 mmol/L.19
TOD was defined as having any of three conditions. First, in terms of kidney disease, an eGFR <60 mL/min per 1.73 m2 was regarded as impaired renal function.20 Second, with regard to heart disease, patients with an LVMI >115 g/m2 (man) and >95 g/m2 (woman) were diagnosed as having left ventricular hypertrophy (LVH).16 Third, with respect to large‐vessel disease, cIMT >1 mm was regarded as an abnormal value.21
Statistical Analyses
Descriptive statistics were presented as mean±standard deviation for continuous variables and as median and interquartile range for nonparametric variables. Frequency and percentage were used for categorical variables. The log transformation for eGFR in two‐way analysis of variance (ANOVA) and proteinuria in multivariate logistic regression analysis was performed in view of the skewed distribution of these data.
Comparisons of continuous variables between groups were evaluated by Student t test, ANOVA or nonparametric test (Kruskal‐Wallis H test for several independent samples and Mann‐Whitney U test for two independent samples). Differences among categorical variables were analyzed using chi‐square test or the two‐tailed Fisher exact test, as appropriate. P value for multiple comparisons was corrected according to the Bonferroni method (six comparisons). Differences of TODs (eGFR, LVMI, and cIMT) were analyzed by two‐way, factorial‐designed ANOVA to assess the effects of nocturnal SBP vs dipping pattern.
Predictors associated with NSH and a nondipping pattern were explored by multivariate logistic regression analysis. Variables included age, sex, course, diabetes mellitus, current smoker, alcohol intake, body mass index (BMI), hemoglobin, albumin, calcium, phosphate, iPTH, serum fasting glucose, cholesterol, triglycerides, HDL‐C, LDL‐C, uric acid, Lg (proteinuria), urinary sodium excretion, eGFR, clinic SBP, and clinic DBP.
Multivariate logistic regression models were employed to study the association of indices of renal function (eGFR) and cardiovascular damage (LVH and cIMT) with age, sex, NSH, nondipping pattern, and other variables, with a P<.05 explored in univariate logistic regression analysis.
All values were two‐tailed and a P<.05 was considered statistically significant. Data were analyzed using SPSS statistical software (version 20.0 for Windows; IBM, Armonk, NY).
Results
Demographic and Clinical Characteristics of the Study Population
The mean age of the cohort was 44.03 years, and 59.38% were men. A total of 239 patients had DM (18.08%), 19.36% were current smokers, and 8.77% consumed alcohol.
Patients in the normal nocturnal SBP and nondipping pattern group had a lower prevalence of current smokers, BMI, and albumin compared with patients with normal nocturnal SBP and a dipping pattern (P<.05). Patients with NSH had the following characteristics compared with patients with normal nocturnal SBP: advanced age; higher prevalence of DM; higher levels of calcium, phosphate, iPTH, homocysteine, uric acid, serum cystatin C, serum urea nitrogent, and Scr; and lower levels of hemoglobin, HDL‐C, and E/A ratio (P<.05). Patients in the NSH and nondipping pattern group had lower levels of hemoglobin and albumin compared with patients in the NSH and dipping pattern group (P<.05; Table 1).
Table 1.
Differences of Demographic and Clinical Characteristics in Chinese CKD Patients With Normal Nighttime SBP or Nocturnal Systolic Hypertension and Dipper or Nondipper Pattern
| Total (N=1322) | Normal Nighttime SBP and Dipper (n=274) | Normal Nighttime SBP and Nondipper (n=258) | NSH and Dipper (n=129) | NSH and Nondipper (n=661) | P Value | |
|---|---|---|---|---|---|---|
| Age, y | 44.03±16.57 | 38.24±15.19 | 37.07±14.92 | 45.93±14.93a , b | 48.78±16.38a , b | <.001 |
| Male:female ratio | 785:537 | 169:105 | 128:130a | 96:33b | 392:269c | <.001 |
| Course, mo | 6 (1–24) | 4 (1–24) | 6 (1–24) | 6 (1–36) | 8 (1–24) | .048 |
| Diabetes mellitus, No. (%) | 239 (18.08) | 23 (8.39) | 18 (6.98) | 25 (19.38)a , b | 173 (26.17)a , b | <.001 |
| Current smoker, No. (%) | 256 (19.36) | 60 (21.90) | 31 (12.02)a | 27 (20.93) | 138 (20.88)b | .011 |
| Alcohol intake, No. (%) | 116 (8.77) | 25 (9.12) | 11 (4.26) | 18 (13.95)b | 62 (9.38) | .011 |
| BMI, kg/m2 | 22.98±3.53 | 23.00±3.72 | 22.05±3.27a | 23.73±3.27b | 23.18±3.54b | <.001 |
| Hemoglobin, g/L | 113.81±28.98 | 128.49±23.20 | 122.20±23.91 | 113.60±28.19a , b | 104.50±29.63a , b , c | <.001 |
| Albumin, g/L | 33.81±8.35 | 34.89±9.25 | 32.95±9.11a | 35.55±7.52b | 33.35±7.71c | .002 |
| Globulin, g/L | 23.74±5.19 | 23.65±4.98 | 23.15±5.29 | 23.59±4.91 | 24.04±5.28 | .135 |
| Calciuma phosphate, mg2/dL2 | 38.15±11.28 | 34.86±8.38 | 35.29±9.23 | 39.41±11.15a , b | 40.35±12.46a , b | <.001 |
| iPTH, pg/mL | 69.40 (36.78–224.43) | 40.55 (28.29–73.53) | 45.26 (28.29–108.45) | 83.93 (41.26–292.81)a , b | 110.33 (48.09–277.24)a , b | <.001 |
| Serum fasting glucose, mmol/L | 5.22±1.58 | 5.07±1.26 | 4.90±1.38 | 5.09±1.52 | 5.44±1.76a , b | <.001 |
| Cholesterol, mmol/L | 5.69±2.62 | 6.04±2.59 | 5.80±2.82 | 5.58±2.42 | 5.52±2.59 | .056 |
| Triglyceride, mmol/L | 1.93±1.34 | 1.84±1.14 | 1.72±1.31 | 2.11±1.47 | 2.01±1.39b | .010 |
| HDL‐C, mmol/L | 1.20±0.44 | 1.29±0.47 | 1.29±0.44 | 1.13±0.40a , b | 1.14±0.42a , b | <.001 |
| LDL‐C, mmol/L | 3.72±2.12 | 4.00±2.07 | 3.79±2.25 | 3.73±2.11 | 3.58±2.08 | .059 |
| Homocysteine, μmol/L | 18.08±10.37 | 14.72±8.43 | 15.58±10.02 | 18.95±9.39a , b | 20.26±10.88a , b | <.001 |
| Uric acid, mmol/L | 462.04±138.47 | 419.59±123.97 | 417.00±132.52 | 518.11±124.92a , b | 486.06±139.38a , b | <.001 |
| Proteinuria, g/24 h | 1.51 (0.46–3.97) | 1.00 (0.26–3.42) | 0.87 (0.32–3.52) | 1.64 (0.56–3.36) | 1.99 (0.77–4.25)a , b | <.001 |
| Urinary sodium excretion, mmol/24 h | 128.27±75.47 | 132.16±82.36 | 130.62±80.64 | 141.70±67.47 | 122.77±71.23 | .195 |
| Serum cystatin C, mg/L | 2.58±1.96 | 1.52±1.19 | 1.78±1.65 | 2.83±1.70a , b | 3.30±2.05a , b | <.001 |
| Blood urea nitrogen, mmol/L | 8.86 (5.41–19.43) | 5.76 (4.20–8.63) | 5.76 (4.18–10.37) | 11.78 (6.72–20.61)a , b | 14.16 (7.38–24.22)a , b | <.001 |
| Serum creatinine, μmol/L | 139.00 (79.30–469.80) | 89.00 (66.63–139.83) | 87.00 (62.23–155.43) | 229.40 (101.00–542.00)a , b | 246.70 (105.33–646.75)a , b | <.001 |
| LVEF, % | 67.30±6.68 | 68.93±5.26 | 67.74±5.31 | 67.26±6.42 | 66.56±7.46 a | .001 |
| E/A ratio | 1.11±0.45 | 1.24±0.41 | 1.27±0.46 | 0.99±0.58a , b | 1.03±0.40a , b | <.001 |
Abbreviations: A, peak mitral filling velocity at atrial contraction; BMI, body mass index; cIMT, carotid intima‐media thickness; E, early mitral inflow filling velocity; HDL‐C, high‐density lipoprotein cholesterol; iPTH, intact parathyroid hormone; LDL‐C, low‐density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; NSH, nocturnal systolic hypertension. P value for analysis of variance or χ2 test between these four groups; P value for multiple comparisons was corrected according to the Bonferroni method (six comparisons). aComparison with the normal nighttime systolic blood pressure (SBP) and dipper groups (P<.05). bComparison with the normal nighttime SBP and nondipper groups (P<.05). cComparison with the nocturnal systolic hypertension and dipper groups (P<.05).
Characteristics of ABPM in CKD Patients
A total of 274 (20.73%) patients had normal nocturnal SBP and a dipping pattern and 258 (19.52%) patients had a normal nocturnal SBP and nondipping pattern, while only 129 (9.76%) CKD patients had NSH and a dipping pattern and 661 (50.00%) patients had NSH and a nondipping pattern.
Patients in the normal nocturnal SBP and nondipping pattern group had a lower prevalence of ambulatory hypertension compared with patients in the normal nocturnal SBP and dipping pattern group (P<.05). Moreover, the prevalence of clinic and ambulatory hypertension in patients with NSH were higher than patients in the normal nocturnal SBP group (P<.05), while the prevalence of ambulatory hypertension in patients in the NSH and nondipping pattern group were lower than patients in the NSH and dipping pattern group (P<.05). Patients in the normal nocturnal SBP and nondipping group had a lower clinic SBP, 24‐hour SBP/DBP, daytime SBP/DBP, and nocturnal SBP/DBP compared with patients in the normal nocturnal SBP and dipping pattern group (P<.05). Patients with NSH had higher clinic SBP/DBP, 24‐hour SBP/DBP, daytime SBP/DBP, and nocturnal SBP/DBP compared with patients with normal nocturnal SBP (P<.05), while patients in the NSH and nondipping pattern group had lower clinic DBP, 24‐hour DBP, daytime SBP/DBP, and higher nocturnal SBP/DBP when compared with patients in the NSH and dipping pattern group (P<.05; Table 2).
Table 2.
Differences of ABPM Characteristics in Chinese CKD Patients With Normal Nighttime SBP or Nocturnal Systolic Hypertension and Dipper or Nondipper Pattern
| Total (N=1322) | Normal Nighttime SBP and Dipper (n=274) | Normal Nighttime SBP and Nondipper (n=258) | NSH and Dipper (n=129) | NSH and Nondipper (n=661) | P Value | |
|---|---|---|---|---|---|---|
| Clinic hypertension, No. (%) | 784 (59.30) | 106 (38.69) | 74 (28.68) | 109 (84.50)a , b | 495 (74.89)a , b | <.001 |
| Ambulatory hypertension, No. (%) | 802 (60.67) | 58 (21.17) | 16 (6.20)a | 128 (99.22)a , b | 600 (90.77)a , b , c | <.001 |
| Clinic SBP, mm Hg | 143.77±24.22 | 132.30±18.82 | 126.20±16.78a | 157.44±21.91a , b | 152.72±23.08a , b | <.001 |
| Clinic DBP, mm Hg | 86.50±14.11 | 82.30±11.86 | 80.52±12.00 | 94.29±14.41a , b | 89.05±14.30a , b , c | <.001 |
| 24‐h SBP, mm Hg | 133.49±18.63 | 118.89±9.68 | 113.75±7.91a | 146.98±11.22a , b | 144.62±14.38a , b | <.001 |
| 24‐h DBP, mm Hg | 79.60±10.55 | 72.68±7.26 | 70.41±5.92a | 87.72±7.28a , b | 84.45±9.36a , b , c | <.001 |
| SBP daytime, mm Hg | 135.32±18.29 | 123.38±10.39 | 115.17±8.34a | 151.88±11.82a , b | 144.90±14.39a , b , c | <.001 |
| DBP daytime, mm Hg | 80.91±10.45 | 75.62±7.61 | 71.56±6.16a | 90.40±7.57a , b | 84.91±9.44a , b , c | <.001 |
| SBP nighttime, mm Hg | 127.81±21.76 | 104.83±8.73 | 109.19±7.34a | 132.08±10.02a , b | 143.77±16.20a , b , c | <.001 |
| DBP nighttime, mm Hg | 75.45±12.47 | 63.41±7.11 | 66.73±6.61a | 79.25±7.65a , b | 83.10±10.53a , b , c | <.001 |
| SBP nocturnal decline, % | 5.77±7.82 | 14.98±4.18 | 5.13±3.91a | 13.19±2.65a , b | 0.75±6.04a , b , c | <.001 |
| DBP nocturnal decline, % | 6.86±8.78 | 15.97±5.95 | 6.67±6.48a | 12.45±5.50a , b | 2.07±7.34a , b , c | <.001 |
Abbreviations: ABPM, ambulatory blood pressure monitoring; DBP, diastolic blood pressure; NSH, nocturnal systolic hypertension; SBP, systolic blood pressure. P value for analysis of variance or χ2 test between these four groups; P value for multiple comparisons was corrected according to the Bonferroni method (six comparisons). aComparison with the normal nighttime SBP and dipper groups (P<.05). bComparison with the normal nighttime SBP and nondipper groups (P<.05). cComparison with the nocturnal systolic hypertension and dipper groups (P<.05).
Comparison of TOD in Different Groups
Patients with NSH had a lower eGFR and higher LVMI and cIMT compared with patients with a normal nocturnal SBP, while the nocturnal SBP, level of eGFR, LVMI, and cIMT was similar between the dipper and nondipper groups. The factorial‐designed ANOVA indicated that the main effect of nocturnal SBP was significant for all of the TOD differences (all P<.001), but no significance was shown in the main effect of the dipping pattern and interaction between the two factors (all P>.05; Table 3).
Table 3.
Differences of Target Organ Damages and Results of Factorial Design ANOVA in Chinese CKD Patients With Normal Nighttime SBP or Nocturnal Systolic Hypertension and Dipper or Nondipper Pattern
| Total (N=1322) | Normal Nighttime SBP | NSH | By ANOVA, P Value for Effects of | |||||
|---|---|---|---|---|---|---|---|---|
| Dipper (n=274) | Nondipper (n=258) | Dipper (n=129) | Nondipper (n=661) | Nighttime SBP | Dipper Pattern | Interaction | ||
| eGFR‐MDRD, mL/min/1.73 m2 | 47.29 (10.35–98.64) | 84.32 (45.30–120.53) | 89.15 (39.02–122.84) | 27.75 (8.13–73.48) | 20.50 (6.38–65.59) | <.001 | .165 | .471 |
| LVMI, g/m2 | 107.81±32.53 | 89.40±21.81 | 86.75±23.51 | 113.67±27.42 | 120.43±32.85 | <.001 | .402 | .056 |
| cIMT, mm | 0.74±0.29 | 0.66±0.22 | 0.62±0.19 | 0.77±0.25 | 0.81±0.33 | <.001 | .985 | .196 |
Abbreviations: CI, confidence interval; cIMT, carotid intima‐media thickness; CKD, chronic kidney disease; LVMI, left ventricular mass index; MDRD, Modification of Diet in Renal Disease; NSH, nocturnal systolic hypertension; OR, odds ratio; SBP, systolic blood pressure. Estimated glomerular filtration rate (eGFR) was transformed into Lg (eGFR) in the factorial design analysis of variance (ANOVA).
In addition, patients with the same nocturnal SBP had a similar prevalence of impaired renal function, LVH, and abnormal cIMT between the dipping and nondipping groups (P>.05), while patients with NSH had a higher prevalence of impaired renal function and LVH than patients with normal nocturnal SBP (P<.05). Patients in the NSH and nondipping group had a higher prevalence of abnormal cIMT compared with patients in the normal nocturnal SBP and dipping or nondipping groups (P<.05; Figure).
Figure 1.
Comparison of target organ damages in four groups with normal nocturnal systolic blood pressure (SBP) or nocturnal systolic hypertension and dipper or nondipper pattern (by Bonferroni method [six comparisons]). *Comparison with the normal nocturnal SBP and dipper groups (P<.05). #Comparison with the normal nocturnal SBP and nondipper groups (P<.05). $Comparison with the nocturnal systolic hypertension and dipper groups (P<.05). LVH indicates left ventricular hypertrophy; cIMT, carotid intima‐media thickness.
Predictors of NSH and a Nondipping Pattern
Multivariate logistic regression analysis showed that NSH was mainly determined by age, serum uric acid, Lg (proteinuria), eGFR, and clinic SBP (Table 4), while age, hemoglobin, and serum albumin were associated with a nondipping pattern in Chinese CKD patients (Table 5).
Table 4.
Univariate and Multivariate Logistic Regression Analysis for Nocturnal Systolic Hypertensiona in Chinese CKD Patients
| Univariate Regression Analysis | Multivariate Regression Analysis | |||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Age, per 1 y | 1.043 (1.035–1.051) | <.001 | 1.017 (1.005–1.029) | .005 |
| Sex (male=1; female=2) | 0.782 (0.626–0.978) | .031 | ||
| Course (per 1 month) | 1.003 (1.000–1.005) | .021 | ||
| Diabetes mellitus (no=0, yes=1) | 3.942 (2.757–5.637) | <.001 | ||
| Alcohol intake (no=0, yes=1) | 1.562 (1.037–2.353) | .033 | ||
| BMI, per 1 kg/m2 | 1.062 (1.025–1.100) | .001 | ||
| Hemoglobin, per 1 g/L | 0.974 (0.970–0.979) | <.001 | ||
| Calcium*phosphate, per 1 mg2/dL2 | 1.049 (1.036–1.062) | <.001 | ||
| iPTH, per 1 pg/mL | 1.004 (1.003–1.005) | <.001 | ||
| Serum fasting glucose, per 1 mmol/L | 1.200 (1.103–1.304) | <.001 | ||
| Uric acid, per 1 mmol/L | 1.004 (1.003–1.005) | <.001 | 1.003 (1.001–1.004) | <.001 |
| Lg (proteinuria), per 1/g/24 h | 1.771 (1.462–2.145) | <.001 | 1.802 (1.401–2.318) | <.001 |
| eGFR‐MDRD, per 1 mL/min/1.73 m2 | 0.982 (0.979–0.984) | <.001 | 0.991 (0.987–0.995) | <.001 |
| Clinic SBP, per 1 mm Hg | 1.059 (1.052–1.067) | <.001 | 1.049 (1.039–1.059) | <.001 |
| Clinic DBP, per 1 mm Hg | 1.050 (1.041–1.060) | <.001 | ||
Abbreviations: CI, confidence interval; MDRD, Modification of Diet in Renal Disease; OR, odds ratio. Adjusted variables: age and sex. Variables of univariate regression analysis include course, diabetes mellitus (no=0, yes=1), current smoker (no=0, yes=1), alcohol intake (no=0, yes=1), body mass index (BMI), hemoglobin, albumin, calcium*phosphate, intact parathyroid hormone (iPTH), serum fasting glucose, cholesterol, triglyceride, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), uric acid, Lg (proteinuria), urinary sodium excretion, estimated glomerular filtration rate (eGFR), clinic systolic blood pressure (SBP), and clinic diastolic blood pressure (DBP). All variables with significant associations were included in multivariate regression analysis. a1=nighttime SBP <120 mm Hg; 2=nighttime SBP ≥120 mm Hg.
Table 5.
Univariate and Multivariate Logistic Regression Analysis for Nondipper Patterna in Chinese CKD Patients
| Univariate Regression Analysis | Multivariate Regression Analysis | |||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Age, per 1 y | 1.018 (1.011–1.025) | <.001 | 1.011 (1.002–1.020) | .020 |
| Sex (male=1; female=2) | 1.473 (1.155–1.880) | .002 | ||
| Diabetes mellitus (no=0, yes=1) | 1.903 (1.352–2.678) | <.001 | ||
| Hemoglobin, per 1 g/L | 0.982 (0.978–0.986) | <.001 | 0.984 (0.978–0.989) | <.001 |
| Albumin, per 1 g/L | 0.973 (0.958–0.987) | <.001 | 0.966 (0.951–0.981) | <.001 |
| Calcium*phosphate, per 1 mg2/dl2 | 1.023 (1.011–1.035) | <.001 | ||
| iPTH, per 1 pg/mL | 1.002 (1.001–1.003) | <.001 | ||
| Serum fasting glucose, per 1 mmol/L | 1.098 (1.011–1.193) | .027 | ||
| Lg (proteinuria), per 1/g/24 h | 1.420 (1.167–1.728) | <.001 | ||
| eGFR‐MDRD, per 1 mL/min/1.73 m2 | 0.993 (0.991–0.996) | <.001 | ||
| Clinic‐SBP, per 1 mm Hg | 1.009 (1.004–1.014) | .001 | ||
Abbreviations: CI, confidence interval; CKD, chronic kidney disease; OR, odds ratio. Adjusted variables: age and sex. Variables of univariate regression analysis include course, diabetes mellitus, current smoker (no=0, yes=1), alcohol intake (no=0, yes=1), body mass index (BMI), hemoglobin, albumin, calcium*phosphate, intact parathyroid hormone (iPTH), serum fasting glucose, cholesterol, triglyceride, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), uric acid, Lg (proteinuria), urinary sodium excretion, estimated glomerular filtration rate (eGFR), clinic systolic blood pressure (SBP) and clinic diastolic blood pressure (DBP). All variables with significant associations were included in multivariate regression analysis. a1=nocturnal SBP decline >10%; 2=nocturnal SBP decline ≤10%.
NSH Independently Associated With TOD
Univariate and multivariate logistic regression analyses were performed to clarify whether NSH or a nondipping pattern was better associated with TOD. Univariate logistic regression analyses showed that NSH and a nondipping pattern were associated with impaired renal function and LVH, and only NSH was correlated with an abnormal cIMT. All these correlations persisted when adjusted for age and sex, whereas only NSH was correlated with impaired renal function and LVH when variables included age, sex, NSH, and nondipping.
Multivariate logistic regression analyses showed that the nondipping pattern was associated with impaired renal function and LVH when traditional risk factors without NSH were included; however, NSH, rather than a nondipping pattern, was correlated with impaired renal function, LVH, and abnormal cIMT when traditional risk factors and NSH were included in multivariate models (Table 6).
Table 6.
Univariate and Multivariate Logistic Regression Analysis: Relationship Between Impaired Renal Function, LVH, and Abnormal cIMT With Nocturnal Systolic Hypertension and Nondipper Pattern in Chinese CKD Patients
| Model | NSH (0=no, 1=yes) | Nondipper (0=no, 1=yes) | ||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Dependent variable: impaired renal function (1=eGFR ≥60 mL/min per 1.73 m2; 2=eGFR <60 mL/min per 1.73 m2) | ||||
| Model 1 | 5.348 (4.190–6.826) | <.001 | 1.983 (1.558–2.526) | <.001 |
| Model 2 | 3.681 (2.829–4.790) | <.001 | 1.763 (1.346–2.309) | <.001 |
| Model 3 | 3.559 (2.681–4.723) | <.001 | 1.101 (0.816–1.486) | .528 |
| Model 4 | – | – | 1.513 (1.052–2.175) | .025 |
| Model 5 | 2.726 (1.870–3.973) | <.001 | 1.089 (0.735–1.612) | .670 |
| Dependent variable: LVH (1=no; 2=yes) | ||||
| Model 1 | 7.382 (5.131–10.620) | <.001 | 2.550 (1.832–3.549) | <.001 |
| Model 2 | 6.094 (4.148–8.953) | <.001 | 2.319 (1.632–3.295) | <.001 |
| Model 3 | 5.512 (3.676–8.265) | <.001 | 1.340 (0.906–1.984) | .143 |
| Model 4 | – | – | 1.799 (1.169–2.767) | .008 |
| Model 5 | 2.997 (1.864–4.819) | <.001 | 1.265 (0.794–2.016) | .322 |
| Dependent variable: abnormal cIMT (1=cIMT ≤1 mm; 2=cIMT >1 mm) | ||||
| Model 1 | 3.524 (1.973–6.295) | <.001 | 1.511 (0.897–2.545) | .121 |
| Model 2 | 1.999 (1.073–3.722) | .029 | – | – |
| Model 5 | 2.100 (1.075–4.104) | .030 | – | – |
Abbreviations: CI, confidence interval; cIMT, carotid intima‐media thickness; OR, odds ratio; SBP, systolic blood pressure. Model 1: univariate, respectively; model 2: age‐ and sex‐adjusted, respectively; model 3: age, sex, nocturnal systolic hypertension (NSH) and nondipper; model 4: multivariable‐adjusted without NSH; model 5: multivariable‐adjusted including NSH. Variables of univariate regression analysis for impaired renal function include age, sex (male=1, female=2), course, diabetes mellitus (no=0, yes=1), current smoker (no=0, yes=1), alcohol intake (no=0, yes=1), body mass index (BMI), hemoglobin, albumin, calcium*phosphate, intact parathyroid hormone (iPTH), uric acid, cholesterol, triglycerides, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), urinary sodium excretion, Lg (proteinuria), NSH, and nondipper. Variables of univariate regression analysis for left ventricular hypertrophy (LVH) and abnormal cIMT include age, sex (male=1, female=2), course, diabetes mellitus (no=0, yes=1), current smoker (no=0, yes=1), alcohol intake (no=0, yes=1), BMI, hemoglobin, albumin, cholesterol, triglyceride, HDL‐C, LDL‐C, urinary sodium excretion, Lg (proteinuria), estimated glomerular filtration rate (eGFR), NSH, and nondipper. All variables with significant associations were included in model 4 and 5 multivariate regression analysis.
Discussion
In the present cross‐sectional study with Chinese CKD patients, we investigated the role of nocturnal hypertension and a nondipper pattern in TOD in Chinese patients with CKD. We found that patients in the nondipping group had similar TOD compared with patients in the dipping group when they had a similar nocturnal SBP level, while patients with NSH had a higher prevalence of TOD than patients with a normal nocturnal SBP. We also showed that NSH is an independent risk factor for poor renal function, LVH, and an abnormal cIMT, while a nondipping pattern was a risk factor for poor renal function and LVH‐dependent NSH. All these results suggest that nocturnal hypertension, rather than a nondipping pattern, was better associated with TOD in Chinese CKD patients. We should pay special attention to nocturnal hypertension, rather than a nondipping pattern in patients with CKD in clinic practice.
Both nocturnal hypertension6, 7 and a nondipping BP pattern8, 9 have been established as important predicting factors in the general population and patients with hypertension. The most important problem when addressing the importance of these two ABPM‐derived estimates on the association with cardiovascular risk and prognosis is that the ABPM‐derived estimates are not independent of each other.22 The nondipping profile is frequently accompanied by enhanced nocturnal BP; however, both nocturnal BP phenotypes are not always concomitantly present because the pathophysiologic and clinical significance of each may differ. We analyzed these patients with CKD by stratifying the patients into four groups depending on absolute nocturnal SBP and a nocturnal dipping pattern and found that patients with a nondipping pattern had similar TOD as patients with a dipping pattern independent of the nocturnal SBP level, while patients with NSH had more severe TOD than patients with a normal nocturnal SBP, independent of dipping and nondipping patterns. Previously, we showed that a reversed BP pattern was an independent risk factor for TOD in CKD patients based on multivariate logistic regression analysis with traditional risk factors.13 These significant correlations were lost when the analysis was performed with traditional risk factors and night SBP levels. These results suggest that nocturnal SBP levels, rather than a nondipping pattern, contributed to TOD in Chinese CKD patients. The nature of this finding was related to BP alone (nocturnal BP better represents the baseline BP of a patient) or with the method of measurement (nocturnal BP is usually measured while the patient is in the supine position and subjected to less variability). One recent report has also shown that there were no differences between dipping and nondipping in patients with nocturnal hypertension with respect to LVM, cIMT, or urinary albumin excretion.23 In contrast, nocturnal hypertension, even with a normal dip, was associated with TOD, especially microalbuminuria.24 These findings suggest that the level of SBP at rest (nocturnal SBP is probably the closer estimate to resting BP) is directly translated to organs, and the elevation is responsible for promoting organ damage (kidney and heart).
With respect to the comparative importance of absolute nocturnal BP values over nondipping status on TOD in CKD patients, nocturnal BP should have a better association with clinic outcomes, which could be explained by the fact that the absolute nocturnal BP is expressed more accurately than the real nocturnal hemodynamic load responsible for the hypertension‐guided TOD and better reflects the basal BP.22 In contrast, the role of nondipping status on TOD could be explained by the fact that it is associated with sleep disruption, autonomic dysfunction, and abnormal sodium handling.25, 26 These associations reflect dysfunction of fundamental regulatory BP mechanisms operating beyond the imposed hemodynamic load at the target organ level. We found different predictors of nocturnal hypertension and nondipping pattern based on clinic parameters: nocturnal systolic hypertension was mainly determined by age, serum uric acid, Lg (proteinuria), eGFR, and clinic SBP, while age, hemoglobin, and serum albumin were associated with a nondipping pattern in Chinese CKD patients.
TOD is a reversible subclinical condition that may precede major cardiovascular events. TOD has been shown to be a complex, multifactorial process that is not dependent on BP reduction alone.11 Exploring the risk factors of TOD in CKD patients is important because CKD patients have a higher occurrence of cardiovascular events.27 We can lower clinical risk by identifying new risk factors and being proactive in reducing risk. We chose eGFR (an important index for the assessment of renal function), LVH (independently associated with mortality in CKD patients28), and cIMT (a marker of the presence and severity of arteriosclerosis, which has been associated with risk factors for all CVDs29) as indices of TOD that reflect the main changes in key organs in CKD patients. We showed that nocturnal hypertension, rather than a nondipping pattern, was an independent risk factor for impaired renal damage, LVH, and abnormal cIMT. These results indicat that lowering nocturnal hypertension might reduce the onset of a clinical end point. Chronotherapy based on the pharmacokinetic properties of antihypertensive drugs might be a possible option in CKD patients because such drugs could reduce the nocturnal BP level more efficiently when applied in the evening. Our previous study showed that bedtime treatment is the most cost‐effective and simplest strategy for achieving adequate reduction of nocturnal BP, and we previously showed that valsartan at a “bedtime” dose could decrease nocturnal SBP to a greater degree compared with an “awakening” dose.30
Study Strengths and Limitations
The present study had strengths and limitations. First, we attempted to lower the effect on the analysis by any drugs because patients who received an antihypertensive drug in the previous month were excluded; however, we could not rule out the effect of Chinese medications. Second, the population of the study was large. Third, all CKD patients underwent comprehensive assessments. Fourth, all CKD patients were admitted to our hospital division. These patients had severe proteinuria or severe renal damage, thus some CKD patients with non‐severe proteinuria or non‐severe renal damage might have been excluded, leading to a difference from general CKD patients. Fifth, all patients had a fixed schedule, which expedited BP monitoring, but this arrangement might have led to different results from monitoring in the outpatient setting. Finally, we cannot set a cause‐effect relationship based on this associative and cross‐section study. Good‐quality, long‐term, large longitudinal trials to validate the role of nocturnal hypertension and a nondipping BP pattern in clinical practice for Chinese patients with CKD are needed.
Conclusions
We have provided the first evidence that nocturnal hypertension rather than a nondipping BP pattern is better associated with TOD in CKD patients. Further studies are needed to determine whether lower nocturnal hypertension or normalizing a nocturnal dipper pattern will reduce the risk of decline in renal function, cardiovascular disease, and mortality.
Disclosures
No conflicts of interest, financial or otherwise, are declared by the authors.
Acknowledgments
We would like to thank all of the patients and their families for participating in this study.
J Clin Hypertens (Greenwich). 2015:792–801. DOI: 10.1111/jch.12589. © 2015 Wiley Periodicals, Inc.
Cheng Wang, Wen‐Jie Deng, and Wen‐Yu Gong contributed equally to this work.
References
- 1. Zhang L, Wang F, Wang L, et al. Prevalence of chronic kidney disease in China: a cross‐sectional survey. Lancet. 2012;379:815–822. [DOI] [PubMed] [Google Scholar]
- 2. Portaluppi F, Boari B, Manfredini R. Oxidative stress in essential hypertension. Curr Pharm Des. 2004;10:1695–1698. [DOI] [PubMed] [Google Scholar]
- 3. Drawz PE, Abdalla M, Rahman M. Blood pressure measurement: clinic, home, ambulatory, and beyond. Am J Kidney Dis. 2012;60:449–462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Sarafidis PA, Khosla N, Bakris GL. Antihypertensive therapy in the presence of proteinuria. Am J Kidney Dis. 2007;49:12–26. [DOI] [PubMed] [Google Scholar]
- 5. Chobanian AV, Bakris GL, Black HR, et al. The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 Report. JAMA. 2003;289:2560–2572. [DOI] [PubMed] [Google Scholar]
- 6. Clement DL, De Buyzere ML, De Bacquer DA, et al. Prognostic value of ambulatory blood‐pressure recordings in patients with treated hypertension. N Engl J Med. 2003;348:2407–2415. [DOI] [PubMed] [Google Scholar]
- 7. Vinyoles E, Felip A, Pujol E, et al. Clinical characteristics of isolated clinic hypertension. J Hypertens. 2008;26:438–445. [DOI] [PubMed] [Google Scholar]
- 8. Brotman DJ, Davidson MB, Boumitri M, Vidt DG. Impaired diurnal blood pressure variation and all‐cause mortality. Am J Hypertens. 2008;21:92–97. [DOI] [PubMed] [Google Scholar]
- 9. De la Sierra A, Redon J, Banegas JR, et al. Prevalence and factors associated with circadian blood pressure patterns in hypertensive patients. Hypertension. 2009;53:466–472. [DOI] [PubMed] [Google Scholar]
- 10. De la Sierra A, Gorostidi M, Banegas JR, et al. Nocturnal hypertension or nondipping: which is better associated with the cardiovascular risk profile? Am J Hypertens. 2014;27:680–687. [DOI] [PubMed] [Google Scholar]
- 11. Sarnak MJ, Levey AS, Schoolwerth AC, et al. Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Circulation. 2003;108:2154–2169. [DOI] [PubMed] [Google Scholar]
- 12. Pogue V, Rahman M, Lipkowitz M, et al. Disparate estimates of hypertension control from ambulatory and clinic blood pressure measurements in hypertensive kidney disease. Hypertension. 2009;53:20–27. [DOI] [PubMed] [Google Scholar]
- 13. Wang C, Zhang J, Liu X, et al. Reversed dipper blood‐pressure pattern is closely related to severe renal and cardiovascular damage in patients with chronic kidney disease. PLoS One. 2013;8:e55419. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Ma YC, Zuo L, Chen JH, et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol. 2006;17:2937–2944. [DOI] [PubMed] [Google Scholar]
- 15. Devereux RB, Alonso DR, Lutas EM, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol. 1986;57:450–458. [DOI] [PubMed] [Google Scholar]
- 16. European Society of Hypertension‐European Society of Cardiology Guidelines Committee . ESH/ESC Guidelines for the management of arterial hypertension: the Task Force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2013;31:1281–1357. [DOI] [PubMed] [Google Scholar]
- 17. Li Y, Wang JG. Isolated nocturnal hypertension: a disease masked in the dark. Hypertension. 2013;61:278–283. [DOI] [PubMed] [Google Scholar]
- 18. Levey AS, Coresh J, Balk E, et al. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med. 2003;139:137–147. [DOI] [PubMed] [Google Scholar]
- 19. Department of Disease Control, Ministry of Health, China, the Chinese Diabetes Society. The Chinese guideline of diabetes prevention and treatment. Chin J Prev Contr Chron Non‐commun Dis. 2004;12:283–285. [Google Scholar]
- 20. Bidani AK, Griffin KA, Epstein M. Hypertension and chronic kidney disease progression: why the suboptimal outcomes? Am J Med. 2012;125:1057–1062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Simon A, Megnien JL, Chironi G. The value of carotid intima‐media thickness for predicting cardiovascular risk. Arterioscler Thromb Vasc Biol. 2010;30:182–185. [DOI] [PubMed] [Google Scholar]
- 22. Redon J, Lurbe E. Nocturnal blood pressure versus nondipper pattern. What do they mean? Hypertension. 2008;51:41–42. [DOI] [PubMed] [Google Scholar]
- 23. Cuspidi C, Sala C, Valerio C, et al. Nocturnal hypertension and organ damage in dippers and nondippers. Am J Hypertens. 2012;25:869–875. [DOI] [PubMed] [Google Scholar]
- 24. Oliveras A, Armario P, Martell‐Claros N, et al. Urinary albumin excretion is associated with nocturnal systolic blood pressure in resistant hypertensives. Hypertension. 2011;57:556–560. [DOI] [PubMed] [Google Scholar]
- 25. Redon J, Plancha E, Swift PA, et al. Nocturnal blood pressure and progression to end‐stage renal disease or death in nondiabetic chronic kidney disease stages 3 and 4. J Hypertens. 2010;28:602–607. [DOI] [PubMed] [Google Scholar]
- 26. Tsioufis C, Kasiakogias A, Thomopoulos C, et al. Managing hypertension in obstructive sleep apnea: the interplay of continuous positive airway pressure, medication and chronotherapy. J Hypertens. 2010;28:875–882. [DOI] [PubMed] [Google Scholar]
- 27. Ruilope LM, Bakris GL. Renal function and target organ damage in hypertension. Eur Heart J. 2011;32:1599–1604. [DOI] [PubMed] [Google Scholar]
- 28. Van Eps CL, Jeffriess L, Haluska B, et al. Cardiac and vascular structure and function parameters do not improve with alternate nightly home hemodialysis: an interventional cohort study. BMC Nephrol. 2011;12:51–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Preston E, Ellis MR, Kulinskaya E, et al. Association between carotid artery intima‐media thickness and cardiovascular risk factors in CKD. Am J Kidney Dis. 2005;46:856–862. [DOI] [PubMed] [Google Scholar]
- 30. Wang C, Zhang J, Liu X, et al. Effect of valsartan with bedtime dosing on chronic kidney disease patients with nondipper blood pressure pattern. J Clin Hypertens (Greenwich). 2013;15:48–54. [DOI] [PMC free article] [PubMed] [Google Scholar]