Prognostic value of morning blood pressure surge in chronic kidney disease

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Prognostic value of morning blood pressure surge in chronic kidney disease

https://doi.org/10.21203/rs.3.rs-1982297/v1

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Objective: To investigate the prognostic value of morning blood pressure surge (MBPS) in chronic kidney disease (CKD).

Methods: We investigated the occurrence of a composite endpoints (coronary events, stroke, and heart failure requiring hospitalization, end-stage renal disease, death) in 153 patients (aged ³18 years) with a diagnosis of in CKD. Based on MBPS defined as ≥35 mmHg, patients were divided into a two groups: with MBPS (n = 50) and without MBPS (n = 103). The follow-up period was ³10 months. Baseline demographic, laboratory and follow-up data were collected. The clinical characteristics of the two groups were compared. The relationships between MBPS and endpoint events were analyzed using the Kaplan–Meier method and Cox regression model.

Results: In total, 153 patients ( mean age 41.8 years; 56.86% males) were included in this study. During the follow-up period (mean 4.3 years), 34 endpoint events occurred. After adjustment for the covariates, the risk of Cardiovascular and cerebrovascular events, end-stage renal disease and death remained significantly higher in patients with MBPS [hazard ratio (HR) and 95% confidence interval (CI) 3.124 (1.096–9.130)]. Among the other variables, 24-h systolic blood pressure, and night-time and daytime pulse pressures remained significantly associated with outcome in patients of CKD [1.789 (1.205–2.654), 1.710 (1.200–2.437), and 1.318 (1.096–1.586), respectively].

Conclusion: MBPS was identified as an independent prognostic factor for composite endpoint events (coronary events, stroke, and heart failure requiring hospitalization, end-stage kidney disease) patients with chronic kidney disease patients.

morning blood pressure surge

24-h ambulatory blood pressure

chronic kidney disease

end-stage renal disease

prognosis

Chronic kidney disease (CKD) is an irreversible change in the structure and function of the kidney caused by a variety of pathogenic factors. This condition can last for months or years and is a severe public health problem worldwide, with a prevalence of 10·8% in China. Approximately 120 million adults aged ³18 years have CKD, although only 12·5% are aware that they are affected by the condition ^[1]. Strategies to delay the progress of CKD and effectively protect kidney function are urgently required. Previous studies have shown that hypertension is not only a factor that promotes the progression of CKD to end-stage renal disease (ESRD), but is also a risk factor for cardiovascular and cerebrovascular events ^[2].

Studies of CKD patients with hypertension have revealed that blood pressure variability is an independent risk factor for cardiovascular and cerebrovascular events in CKD patients^[3,4]. Morning blood pressure surge (MBPS) is a typical manifestation of increased blood pressure variability,the mortality and disability rates are high, which poses a great threat to the normal life and health of people^[5]. Previous studies have shown that increased MBPS is associated with stroke, left ventricular (LV) hypertrophy, ischemic heart disease and arterial stiffness in patients with sustained hypertension^[4-8].In addition, studies of middle-aged and elderly untreated and treated hypertensive patients^[9,10], old treated hypertensive patients^[11-13], And old untreated and treated hypertensive individuals^[14,15]. Recent research demonstrated that MBPS levels correlated with deterioration of diastolic function parameters in patients with masked hypertension^[16]. However, the impact of MBPS on CKD patients remains to be fully clarified. In this study, we hypothesized that MBPS has a negative impact on CKD and increases the risk of cardiovascular and cerebrovascular events. We also evaluated the prognostic value of MBPS in chronic kidney disease.

2.1 Patients

A total of 153 CKD patients of Ningxia Medical University General Hospital with 24-h ambulatory blood pressure monitoring (ambulatory blood pressure monitoring, ABPM) records between January 2012 and December 2017 were analyzed retrospectively. The following inclusion criteria were applied: age ≥18 years; complete clinical data; follow-up period ≥10 months. The exclusion criteria were as follows: severe liver disease and tumor disease; maintenance dialysis patients (hemodialysis, peritoneal dialysis).The study received full ethical approval from the Ningxia Medical University General Hospital Medical Research Ethics Review Committee(Reference KYLL-2022-0883) and was conducted following the principles of the Declaration of Helsinki. All participants gave informed consent for their participation.

2.2 Diagnostic criteria

The diagnosis of CKD was based on the 2012 KDIGO^[17] guidelines. MBPS was calculated as the average BP value within 2 h after waking up minus the minimum value during night sleep (average of 1 h including the lowest value) ^[18]. Based on MBPS defined as ≥35 mmHg, patients were divided into a two groups: with MBPS (n = 50) and without MBPS (n = 103). The clinical characteristics and laboratory indicators of the two groups were compared.

2.3 ABPM

All of the patients underwent 24-h ABPM on a typical working day. BP was recorded every 30 min during the day (between 06:00 and 22:00) and every 30 min at night (between 22:00 and 06:00) using the oscillometric method with an automatic monitoring device (Welch Allyn ABPM 6100) and the data were analyzed using the associated software (I.E.M. GmbH). The mean values of daytime and night-time BP, and 24-h SBP and DBP were calculated for each patient on the basis of hourly averages of ABPM recordings. When wearing the detector, patients were asked to maintain normal life activities and avoid influential factors such as strenuous activities and emotional instability.

2.4 Echocardiography

Ventricular septal thickness (IVST), left ventricular posterior wall (LVPW) thickness, left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVDd) values, and systolic function and diastolic function of the LV were assessed using two-dimensional echocardiography. LV mass (LVM) was calculated using the ASE formula[19] as follows: 0.8 ×{1.04 ×[(IVSd + LVEDd + PWTd)3- LVEDd3]) + 0.6}. LVM index (LVMI) was calculated as the LVM/the body surface area (BSA). BSA was calculation using Stevenson’s formula [20] as follows: BSA=0.0128×weight (kg)+0.0061×height.(cm)-0.1529.

2.5 Estimated glomerular filtration rate

The estimated glomerular filtration rate (eGFR) was calculated according to the CKD-EPI ^[21]formula.

2.6 Follow-up

Patients were followed up in our hospital outpatient clinic. The occurrence of cardiovascular and cerebrovascular events and end-stage kidney disease were recorded during follow-up visits or by telephone interview of the patient followed by a clinical visit. The primary endpoint of our study was all-cause death. Secondary endpoints were as follows: (i) Cardiovascular and cerebrovascular events, including fatal and non-fatal myocardial infarction, heart failure requiring hospitalization, and fatal and non-fatal stroke. (ii) ESRD including peritoneal dialysis, hemodialysis or eGFR <15 ml/min/173 m². The follow-up deadline was December, 2018; the study endpoint was reached.

2.7 Statistical analysis

SPSS 19.0 software was used for all the statistical analysis. The normal distribution of measurement data were expressed as mean ± standard deviation (SD) and differences between groups were compared using independent sample t-tests. Non-normally distributed measurement data were represented by quartiles and differences between groups were compared using non-parametric tests. Sample rate (%) was used for counting data, and c² tests were used to compare differences between groups. Cox regression analysis was used to estimate univariate and multivariate associations of factors with outcome. In the univariate analysis, put the index of P < 0.1 into the multivariate Cox regression model analysis with results expressed as a risk ratio with corresponding 95% confidence interval. Survival curves were estimated using the Kaplan–Meier product-limit method and compared with the log-rank test. P < 0.05 was set as the threshold for statistical significance.

In total, 153 patients ( mean age 41.8 years; 56.86% males) were included in this study. Renal biopsy was performed in 62 cases of renal biopsy, including 16 cases of IgA nephropathy. Based on MBPS defined as ≥35 mmHg, patients were divided into a two groups: with MBPS (n = 50) and without MBPS (n = 103). Demographic data, risk factors and blood pressure measurements of the patients in the two groups are presented in Table 1 and Table 2. Body mass index and creatinine levels were Significantly higher in patients with MBPS. In addition, 24-h systolic BP and 24-h PP as well as daytime systolic and diastolic BP were significantly higher in CKD patients with MBPS, while HDL levels were significantly lower. Hypertension was also more common in CKD patients with MBPS.

Table 1

Comparison of general data for CKD patients with or without MBPS.

Characteristics	Morning blood pressure surge group (n = 50)	Normal morning blood pressure surge group (n = 103)	t/c²	P
Age (y)	41.74±12.53	41.72±13.21	-0.10	0.992
Sex (male %)	32 (64.0%)	55 (53.4%)	1.079	0.299
BMI (kg/m²)	25.55±3.37	24.30±3.79	-1.983	0.049*
Hypertension (%)	35 (85.46%)	38 (36.89%)	14.788	0.000*
CKD pathological classification IgA nephropathy Other classification			5.070 0.024*
	13(26.0%)	12(11.6%)
	38(74.51%)	90(88.23%)
BUN ( mmol/l)	5.57 (4.69, 7.40)	5.51 (4.27, 7.90)	0.695	0.719
Creatinine (mmol/l)	106.0 (85.2, 127.3)	88.4 (65.0, 128.0)	1.477	0.025*
Uric acid (mmol/L)	388.32±98.85	366.58±105.30	-1.221	0.224
Phosphorus (mmol/L)	1.20±0.36	1.17±0.37	-0.439	0.661
Calcium (mmol/L)	2.27±0.17	2.24±0.20	-0.725	0.470
Glucose (mmol/L)	5.41±1.41	5.53±1.92	0.385	0.701
eGFR (ml/min/1.73/m²)	73.4 (48.6, 92.8)	83.6(47.5, 113.2)	1.168	0.245
Albumin (g/L)	35.5 (29.4, 39.1)	33.3 (21.7, 38.3)	1.311	0.064
Hemoglobin (g/L)	142 (128, 153)	135 (123, 150)	0.973	0.300
Total chol. (mmol/L)	2.12 (1.30, 3.15)	1.90 (1.15, 2.65)	0.864	0.446
Triglyceride (mmol/L)	4.94 (4.09, 6.37)	4.92 (4.06, 6.69)	0.490	0.970
HDL (mmol/L)	1.00±0.26	1.16±0.60	2.345	0.020*
LDL (mmol/L)	2.92±1.55	3.20±1.75	0.958	0.340
24-h Urine protein (g/24 h)	1.70 (0.80, 2.94)	1.59 (0.72, 3.57)	0.765	0.602
24-h SBP (mmHg)	122.5 (116.0, 135.3)	116.0 (107.0, 129.0)	1.547	0.017*
dSBP (mmHg)	125.0 (117.8, 138.0)	119.0 (109.0, 132.0	1.395	0.041*
nSBP (mmHg)	117.90±14.63	115.75±19.34	-0.696	0.488
24-h DBP (mmHg)	78.26±8.60	74.79±11.42	-1.903	0.059
dDBP (mmHg)	80.48±8.50	76.74±11.41	-2.058	0.041*
nDBP (mmHg)	72.94±9.47	72.92±12.90	-0.009	0.993
24-h PP(mmHg)	45.5 (40.0, 50.3)	40.0 (36.0, 49.0)	1.431	0.033*
dPP (mmHg)	46.0 (40.0, 50.3)	41.0 (37.0, 50.0)	1.431	0.033*
nPP (mmHg)	44.0 (38.8, 51.3)	40.0 (36.0, 48.0)	1.301	0.068
BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; DBP, diastolic blood pressure; dDBP, daytime DBP; nDBP, night-time DBP; SBP, systolic blood pressure; dSBP, daytime SBP; nSBP, night-time SBP; PP, pulse pressure; nPP, night-time PP; dPP, daytime PP.

Table 2
Comparison of heart function index in CKD patients with or without MBPS.

	Morning blood pressure surge group (n = 50)	Normal morning blood pressure surge group (n = 103)	t/c²	P
IVST (mm)	9.02±0.96	8.73±0.92	-1.815	0.071
LVPW (mm)	9.0 (8.0, 9.3)	9.0 (8.0, 9.0)	0.625	0.829
LVEF (%)	69.1 (65.7, 72.6)	69.0 (65.9, 71.2)	0.783	0.572
LVDd (mm)	48.0 (45.8, 50.0)	48.0 (45.0, 50.0)	0.629	0.824

*,means P <0.05; IVST, ventricular septal thickness; LVPW, left ventricular posterior wall thickness; LVDd, left ventricular end-diastolic diameter; LVEF, left ventricular ejection fraction; LVMI, left ventricular mass index.

During the follow-up (mean 4.3 years, range 1–6.7 years), 34 patients (19 males) experienced endpoint events (Table 3). In the group without MBPS, eight cardiovascular events and five strokes occurred with an incidence rate of 16.5%, including two deaths. In the group with MBPS, there were 17 endpoint events (6 cardiovascular events, 3 strokes, and 8 ESRD), with an incidence rate of 34%.

Kaplan-meier survival analysis showed that the incidence of Cardiovascular and cerebrovascular events, end-stage renal disease and death in the morning peak blood pressure group was significantly higher (log rank=4.124,P＜0.05) than those in the normal morning peak blood pressure group in Figure 1. Cox regression univariate analysis showed that Hypertension，phosphorus，calcium，Creatinin，eGFR，Albumin，Hemoglobin，24HSBP，dSBP，nSBP，MBPS,dPP，nPP,Ventricular septal thickness，left ventricular posterior wall thickness，left ventricular end-diastolic diameter and left ventricular mass index were significantly associated with increased cardiovascular, Cerebrovascular,end-stage renal disease and death risk in Table 4. We performed cox regression multivariate analyses including Age，calcium， Hypertension，phosphorus，Creatinin，eGFR，Albumin，Hemoglobin，24HSBP，dSBP，nSBP，MBPS，24hPP，dPP，nPP，Ventricular septal thickness，left ventricular posterior wall thickness，left ventricular end-diastolic diameter and left ventricular mass index. Results of multivariate analyses are reported in Table 5. After adjustment for these covariates, the risk of Cardiovascular and cerebrovascular events, end-stage renal disease and death remained significantly higher in patients with MBPS [hazard ratio (HR) and 95% confidence interval (CI) 3.124 (1.096–9.130)]. Among the other variables, 24-h SBP, nPP, and dPP remained significantly associated with outcome in patients of CKD [1.789 (1.205–2.654), 1.710 (1.200–2.437), and 1.318 (1.096–1.586), respectively].

Table 3

Endpoint events in the two groups during the follow-up.

Table 4

Risk of endpoint events in univariate analysis.

	Univariate regression analysis
	Odds ratio	95% CI	P
Age, y	1.02	0.10–1.05	0.087
Males, n (%)	1.08	0.55–2.135	0.817
Hypertension (yes)	2.238	1.11–4.53	0.025*
Phosphorus ( mmol/L)	3.520	2.17–5.71	0.000*
Calcium ( mmol/L)	-0.022	0.01–0.08	0.000*
Glucose ( mmol/L)	1.142	0.96–1.36	0.136
BUN ( mmol/L)	1.073	1.05–1.10	0.000*
Creatinine ( mmol/L	1.001	1.001–1.002	0.000*
eGFR ( ml/min/1.73/m²)	0.973	0.960–0.980	0.000*
Uric Acid ( mmol/L)	1.003	1.0–1.006	0.000*
Albumin ( g/L)	0.908	0.88–0.94	0.000*
Hemoglobin ( g/L)	0.956	0.94–0.97	0.000*
MBPS ( 10 mmHg)	1.979	1.01–3.89	0.047*
24-h SBP ( 10 mmHg)	1.022	1.00–1.04	0.047*
dSBP ( 10 mmHg)	1.022	1.00–1.04	0.047*
nSBP ( 10 mmHg)	1.020	1.00–1.04	0.050
24-h DBP ( 10 mmHg)	1.026	0.99–1.06	0.166
dDBP ( 10 mmHg)	0.359	1.017–1.98	0.155
nDBP ( 10 mmHg)	1.023	1.00–1.05	0.105
24-hPP ( 10 mmHg)	1.026	0.97–1.06	0.090
dPP ( 10 mmHg)	1.043	1.01–1.08	0.013*
nPP ( 10 mmHg)	1.042	1.01–1.08	0.012*
IVST (mm)	1.607	1.24–2.08	0.000*
LVPW (mm)	1.599	1.24–2.10	0.000*
LVEF (%)	0.979	0.95–1.009	0.172
LVDd (mm)	1.280	1.14–1.44	0.000*
LVMI (g/m²)	1.033	1.02–1.05	0.000*

*,means P <0.05; CI, confidence interval; BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; DBP, diastolic blood pressure; dDBP, daytime DBP; nDBP, night-time DBP; SBP, systolic blood pressure; dSBP, daytime SBP; nSBP, night-time SBP; PP, pulse pressure; nPP, night-time PP; dPP, daytime PP; IVST, ventricular septal thickness; LVPW, left ventricular posterior wall thickness; LVDd, left ventricular end-diastolic diameter; LVEF, left ventricular ejection fraction; LVMI, left ventricular mass index.

Table 5

Risk of endpoint events in multivariate analysis.

	Multivariate regression analysis
	Odds ratio	HR (95% CI)	P
Age ( years)	——	——	——
Hypertension (yes)	——	——	——
Phosphorus (↑mmol/L)	——	——	——
Calcium (↑mmol/L)	——	——	——
Glucose (↑mmol/L)	——	——	——
BUN (↑mmol/L)	——	——	——
Creatinine (↑mmol/L	——	——	——
eGFR (↑ml/min/1.73/m²)	——	——	——
Uric acid (↑mmol/L)	——	——	——
Albumin (↑g/L)	——	——	——
Hemoglobin (↑g/L)	——	——	——
MBPS (↑10 mmHg)	3.124	3.124 (1.096–9.130)	0.037*
24-h SBP (↑10 mmHg)	1.789	1.789 (1.205–2.654)	0.004*
24-h PP (↑10 mmHg)	——	——	——
dPP (↑10 mmHg)	1.710	1.710 (1.200–2.437)	0.003*
nPP (↑10 mmHg)	1.318	1.318 (1.096–1.586)	0.003*
IVST (mm)	——	——	——
LVPW (mm)	——	——	——
LVEF (%)	——	——	——
LVDd (mm)	——	——	——
LVMI (g/m²)	——	——	——

*,means P <0.05.

Recent studies have shown that MBPS is closely related to damage in target organs such as the heart, brain and kidney^[22-24]. In this study, we investigated the prognostic value of MBPS to better manage the risk of adverse events in patients with CKD. We found that MBPS in patients with CKD is associated with increased risk of composite endpoint events (coronary events, stroke, heart failure requiring hospitalization, ESRD) independently of other ambulatory BP parameters and risk markers.

According to our results,the high-density lipoprotein in the MBPS group was significantly lower than that in the non-MBPS group.High-density lipoprotein is related to anti-atherosclerosis and improving vascular endothelial function, thereby reducing the occurrence of cardiovascular and cerebrovascular diseases. In this study, the incidence of end-point events in patients with increased morning peak blood pressure was significantly higher, so it cannot be ruled out that high-density lipoprotein has an effect on endpoint events.In addition,there were no significant differences in ventricular septal thickness, LVPW thickness, ejection fraction, left ventricular end-diastolic inner diameter, and LVMI between the groups of CKD patients with and without MBPS. Other reports suggestion, LVMI levels were significantly higher in the MBPS^[25]. These discrepancies may be due to differences in the design of the studies. In this study, we included a small sample of relatively young patients with CKD, with a short follow-up time, and no obvious ventricular remodeling.

Some limitations of our study should be noted. First, this was an observational, retrospective study. Second, we studied only Asian individuals and patients with CKD; therefore, our results cannot be applied to other ethnic groups or patient populations. Third, since patients were treated with different combinations of antihypertensive agents, it is not possible to evaluate the effect of each drug on MBPS. Fifth, determination of MBPS may be affected by the waking time of patients and these data were not available.

We have demonstrated for the first time that MBPS is independently associated with increased risk of composite endpoint events (coronary events, stroke, and heart failure requiring hospitalization, end-stage kidney disease, death) risk in CKD patients. Therefore, MBPS is implicated as an important parameter that can be monitored to determine clinical management strategies and prevent organ damage in patients with CKD.

Data availability

The data extracted from included studies and used for analyses are available upon reasonable request from the authors.

Acknowledgements

The author thanks each member of the team for their contribution and the great efforts of teachers from the Department of Kidney Medicine at Ningxia Medical University.

Author contributions

Zhilan Ma.Formal analysis,Writing the first draft.Yan Wang.Data Curation.Xiaoyan Guo:Data Curation and investigation.Lan Ma.Visualization.Yonghua Liu.Software and resources.Xiaoling Zhou. Conceptualization, Methodology,Writing-Review and editing,Funding acquisition. All authors reviewed the manuscript.

Funding

This work was supported by: 1. Ningxia Natural Science Foundation 2019A0288; 2. First-Class Discipline Construction Founded Project of NingXia Medical University and the School of Clinical Medicine, NXYLXK2017A05; 3. Foundation for Returned Scholars of Ningxia 2017659.

Competing interests

The authors declare no competing interests.

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No competing interests reported.

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Prognostic value of morning blood pressure surge in chronic kidney disease

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