Skip to main content

Main menu

  • Online first
    • Online first
  • Current issue
    • Current issue
  • Archive
    • Archive
  • Submit a paper
    • Online submission site
    • Instructions for authors
  • About the journal
    • About the journal
    • Editorial board
    • Instructions for authors
    • FAQs
    • Chinese Stroke Association
  • Help
    • Contact us
    • Feedback form
    • Reprints
    • Permissions
    • Advertising
  • BMJ Journals

User menu

  • Login

Search

  • Advanced search
  • BMJ Journals
  • Login
  • Facebook
  • Twitter
Stroke and Vascular Neurology

Advanced Search

  • Online first
    • Online first
  • Current issue
    • Current issue
  • Archive
    • Archive
  • Submit a paper
    • Online submission site
    • Instructions for authors
  • About the journal
    • About the journal
    • Editorial board
    • Instructions for authors
    • FAQs
    • Chinese Stroke Association
  • Help
    • Contact us
    • Feedback form
    • Reprints
    • Permissions
    • Advertising
Open Access

Ambulatory blood pressure profile and stroke recurrence

Jie Xu, Fei Jiang, Anxin Wang, Hui Zhi, Yuan Gao, Junping Tian, Jinglin Mo, Zimo Chen, An-Ding Xu, Benyan Luo, Bo Hu, Yuqing Zhang, Xingquan Zhao, Yilong Wang, Hao Li, Haipeng Shen, Yongjun Wang
DOI: 10.1136/svn-2020-000526 Published 28 September 2021
Jie Xu
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jie Xu
Fei Jiang
3 Department of Statistics and Actuarial Sciences, University of Hong Kong, Hong Kong, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Anxin Wang
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Anxin Wang
Hui Zhi
4 Biostatistics and Clinical Research Methodology Unit, Faculty of Medicine, University of Hong Kong, Hong Kong, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yuan Gao
5 Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Junping Tian
6 Department of Cardiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jinglin Mo
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zimo Chen
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
An-Ding Xu
7 Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for An-Ding Xu
Benyan Luo
8 Department of Neurology and Brain Medical Centre, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bo Hu
9 Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Bo Hu
Yuqing Zhang
10 Division of Hypertension, National Center for Cardiovascular Disease China, Fuwai Hospital, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xingquan Zhao
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yilong Wang
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hao Li
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Haipeng Shen
11 Faculty of Business and Economics, University of Hong Kong, Hong Kong, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yongjun Wang
1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2 China National Clinical Research Center for Neurological Diseases (NCRCND), Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Yongjun Wang
  • Article
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF
Loading

Abstract

Objectives To establish a new ambulatory blood pressure (ABP) parameter (24-hour ABP profile) and evaluated its performance on stroke outcome in ischaemic stroke (IS) or transient ischaemic attack (TIA) patients.

Methods The prospective cohort consisted of 1996 IS/TIA patients enrolled for ABP monitoring and a 3-month follow-up for stroke recurrence as outcome. Profile groups of systolic blood pressure (SBP) were identified via an advanced functional clustering method, and the associations of the profile groups and conventional ABP parameters with stroke recurrence were examined in a Cox proportional hazards model.

Results Three discrete profile groups (n=604, 781 and 611 in profiles 1, 2 and 3, respectively) in 24-hour ambulatory SBP were identified. Profile 1 resembled most to the normal diurnal blood pressure pattern; profile 2 also dropped at night, but climbed earlier and with higher morning surge; while profile 3 had sustained higher nocturnal SBP without significant nocturnal SBP decline. The incidence of stroke recurrence was 2.9%, 3.9% and 5.5% in profiles 1, 2 and 3, respectively. After adjustment for covariates, profile 3 was significantly associated with higher risk of stroke recurrence with profile 1 as reference (HR 1.76, 95% CI: 1.00 to 3.09), while no significant difference was observed between profiles 2 and 1 (HR 1.22, 95% CI: 0.66 to 2.25). None of conventional ABP parameters showed significant associations with the outcome.

Conclusions Ambulatory 24-hour SBP profile is associated with short-term stroke recurrence. Profiles of ABP may help improve identification of stroke recurrence by capturing the additive effects of individual ABP parameters.

Introduction

Hypertension has been identified as the first leading modifiable risk factor for stroke.1 2 It is widely accepted that 24-hour ambulatory blood pressure (ABP) monitoring is superior to clinic and self-measurement of blood pressure (BP) in the diagnosis and prognosis of hypertension and risk assessment of cardiovascular and cerebrovascular disease.3 The conventional ABP parameters includes 24-hour mean BP, daytime and night-time BP, dipping status, morning surge (MS), nocturnal hypertension, BP variability (BPV) et al.4 Extensive studies have shown that above conventional ABP parameters are associated with stroke3 5–16 and its clinical outcome.17–21 However, individual ABP parameter might only represent a specific characteristic of the whole ABP profiles, and different parameter play distinct role on stroke prognosis. For example, disturbed dipping status, especially reverse dippers, the long-lasting high BP level could cause impairment of the arterial wall structure and endothelium leading to acceleration of vascular remodelling and atherosclerosis of the artery, which promote subsequent stroke events.22 An exaggerated morning BP surge could induce plaque instability through increased inflammatory reaction and leading to plaque rupture triggered by increased mechanical pressure and shear stress of an exaggerated fluctuation of blood flow on the vessel wall.23 24

Moreover, despite extensive existing data on individual ABP parameters in relation to the risk of developing stroke, the literature is relatively limited regarding the association between ABP profiles and stroke outcome. Most previous studies that focused on analyses of individual ABP parameters neglected the temporal nature of the 24-hour ABP data and the additive effects of multiple ABP characteristics. Profile analysis of 24-hour ABP, incorporating all the ABP parameters with the minimum information lost, may be better for evaluating its performance on stroke outcome. A piecewise linear random effects model has been recently proposed to identify 24-hour ABP profile clusters25; however, this model has not been used for clinical evaluation of stroke patients. In this study, we aimed to identify clusters of stroke patients with similar ABP profile patterns, characterise the circadian rhythm parameters in the profile groups and examine the association of 24-hour ABP profiles with the clinical outcome measured as stroke recurrence.

Methods

Study cohort

The Blood pressure and clinical Outcome in Stroke Survivors study is a nationwide, hospital-based, longitudinal, prospective cohort study conducted in 61 hospitals in China. Details of the design, rationale and baseline characteristics were described previously.26 In brief, 2608 patients of acute ischaemic stroke (IS) and transient ischaemic attack (TIA) within 7 days of the index event, aged 18 years or older, were enrolled from October 2012 to February 2014 at baseline for ABP monitoring (ABPM) and followed for 3 months for stroke recurrence as outcome. In this study cohort, 199 patients with incomplete baseline data and 376 patients with incomplete ABP data were excluded, and 37 patients were lost to follow-up. A total of 1996 patients formed the current study cohort.

From January 2015 to December 2015, a total of 746 patients with IS were enrolled for ABPM in Neurology Department of Beijing Tiantan Hospital, Capital Medical University. These patients who did not have information on the clinical outcome were used as a validation cohort for the ABP profile cluster analysis. In this validation cohort (mean age=56.1±12.7 years, 28.3% female), 41.9% had a history of hypertension and a median of National Institute of Health Stroke Scale of 3 with an IQR of 1–8.

The study was approved by the central Institutional Review Board at Beijing Tiantan Hospital. All patients or the designated relatives gave written consent when enrolled.

BP measurements

For stroke patients, to avoid BP elevation during the stress period after stroke onset, 24-hour ABPM was completed within 3–14 days after the index event; however, for TIA patients, because TIA does not generally cause stress hypertension, ABPM could be evaluated from onset to 14 days. The frequency of measurements was set every 15 min during daytime and every 30 min during night-time. Daytime was defined from 06:00 to 21:59 and night-time from 22:00 to 05:59. If the recorded BP readings were less than 80% of expected measurements, the ABPM should be repeated. Participants were instructed to keep a diary of their daily activities during the measurements.

Definition of the conventional ABP parameters

In this study, all ABP parameters were calculated based on systolic blood pressure (SBP).6 The percentage of nocturnal decline in SBP was calculated as ((daytime SBP−night-time SBP)/daytime SBP)×100%. Daytime and night-time SBP was defined as the mean SBP during daytime and night-time episodes. Night-time dipping was classified as follows: extreme dipper (nocturnal decline ≥20%), dipper (10%≤nocturnal decline <20%), non-dipper (0%≤nocturnal decline <10%) and reverse dipper (nocturnal decline <0%). Morning SBP was defined as the average of SBP readings during the first 2 hours of the daytime (06:00 to 08:00). The sleep-trough (ST) SBP was defined as the lowest SBP during night-time. MS was defined as ST-MS calculated by the morning SBP minus the ST SBP. SBP variability was evaluated by coefficient of variation defined as 100×SD/mean SBP.

Clinical outcomes

Patients were followed up for clinical outcomes at 3 months through face-to-face interview and at 12 months by telephone. Follow-up through telephone or face to face was conducted by trained site coordinators. In this study, the clinical outcome was stroke recurrence during the 3 months. Stroke recurrence was defined as a new stroke event (ischaemic or haemorrhagic stroke). If stroke event occurred before ABPM, it would not be included in the statistical analysis.

Statistical analysis

The functional clustering method was implemented to group the cluster of BP profiles. To facilitate the computation, we preprocessed the ABP readings so that the measurement times are equally spaced on the 15-min grids. The detailed preprocessing steps were described in Section S.2.1 in the online supplemental material. We treated each resulting BP curve as a function of time and assumed that the profiles in the same cluster share the same mean value. Then we used the Fourier expansion in combination with the iterative k-centres clustering method.27 Essentially, the algorithm was developed to minimise the errors between observed curves and their cluster sample means. Since wrong clustering would lead to larger errors than the true one did, the minimisation algorithm forced the estimated clusters approaching the underlying truth when the sample size increased. The technical details are presented in Section S.2.2 in the online supplemental material.

Supplementary data

[svn-2020-000526supp001.pdf]

The associations of ambulatory SBP parameters and profiles with the clinical outcome were then examined using a Cox proportional hazards model with adjustment for confounding variables. All statistical analyses were performed with SAS V.9.4 (SAS Institute Inc). A two-sided p<0.05 was considered statistically significant.

Results

Three discrete profile groups in 24-hour ambulatory SBP were identified using functional clustering method (figure 1). Profile 1 (n=781) resembled most to the normal diurnal BP pattern; profile 2 (n=611) also dropped at night, but climbed earlier (the trough SBP was seen around 04:00 in profile 1 and around 24:00 in profile 2) and with higher MS; while profile 3 (n=604) had sustained higher nocturnal SBP without significant nocturnal SBP decline. Moreover, differences in daytime SBP were not as big as those in night-time SBP between the three groups. The validation cohort produced considerably similar profile patterns of SBP, especially at night-time (figure 2).

Figure 1
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1

Ambulatory systolic blood pressure (SBP) profiles in the three cluster groups.

Figure 2
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2

Ambulatory systolic blood pressure (SBP) profiles in the three cluster groups of the validation cohort.

The characteristics in the total cohort of 1996 patients and by three profile groups were shown in table 1. The mean age was 62.7±10.9 years; 32.9% were females; 88.2% was IS patients in the total cohort. Patients in profile groups 2 and 3 were older and had more coronary heart disease than those in group 1. Group 2 had less alcohol drinkers than group 1. Group 3 had less dyslipidaemia than group 1. More patients in group 3 (71.4%) took antihypertensive therapy at discharge than those in group 1 (65.4%). Other characteristics did not differ significantly between the three profile groups. Comparison of characteristics between the included and excluded patients is given in online supplemental table S1.

View this table:
  • View inline
  • View popup
Table 1

Characteristics of the participants by profile groups

Table 2 presents ambulatory SBP parameters of all participants and by profile groups. Daytime, night-time, morning and trough SBP, and ST-MS showed significant differences between groups in different directions. 24-hour SBP variability did not differ significantly between groups. Compared with group 1, groups 2 and 3 had significantly less dippers and more non-dippers and reverse dippers. Group 3 had the highest incidence of stroke recurrence (5.5%).

View this table:
  • View inline
  • View popup
Table 2

Ambulatory SBP parameters of the participants by profile groups

In table 3, profile patterns, mean 24-hour SBP, night-time SBP, morning SBP and trough SBP were found to be significantly associated with 3-month stroke recurrence without adjustment for covariates. However, after adjustment for age, sex, risk factors and secondary prevention medication in model 2 and with additional adjustment for mean 24-hours SBP in model 3, profile group 3 was still significantly associated with stroke recurrence with group 1 as reference; but other associations became non-significant.

View this table:
  • View inline
  • View popup
Table 3

HR of SBP parameters for 3-month stroke recurrence

Finally, table 4 shows ambulatory SBP parameters by profile groups in the validation cohort. Differences in mean 24-hour SBP, daytime SBP, night-time SBP, morning SBP, trough SBP, ST-MS, 24-hour SBP variability and night-time dipping patterns were very similar to those as shown in table 2.

View this table:
  • View inline
  • View popup
Table 4

Ambulatory blood pressure parameters by profile groups in the validation cohort

Discussion

In the present study, we characterised the 24-hour ABP profiles in 1996 IS and TIA patients using a novel functional clustering method, in relation to stroke recurrence as the outcome. Three different profile groups in ABP were identified. The most characteristic cluster was the patients in group 3 who had significantly higher nocturnal SBP than those in group 1. The validation cohort produced a substantially similar profile pattern. The incidence of stroke recurrence was significantly higher in group 3 (5.5%) than in group 1 (2.9%). The ABP profile cluster of group 3 was significantly associated with a higher risk of stroke recurrence; but individual ABP parameters did not show significant associations with the outcome after adjustment for covariates. These findings support the notion that the profile cluster is a more strongly associated with the clinical outcome of stroke patients by capturing the additive effects of individual ABP parameters.

ABPM that continuously monitors changes in BP during daytime and night-time can generate a large number of readings with multiple characteristics of BP.28 Extensive studies have demonstrated that higher MS, non-dipping and reverse dipping and increased diurnal levels and variability of BP are associated with the risk of developing stroke.3 5–11 However, the literature relating these ABP parameters to clinical outcomes of stroke patients remained relatively limited, and the results were inconsistent.17–19 29 30 In the current study, we did not find conventional ABP parameters to be significantly associated with the 3-month stroke recurrence after adjustment for covariates. The observations from this and previous studies suggest that individual ABP parameters might have a limited statistical power to predict stroke recurrence of stroke patients. Previous studies of ABP focused analysis of single readings ignored the temporal nature of the data. Advanced statistical techniques that incorporate the information of multiple ABP characteristics may help improve comprehensive BP assessment for stroke patients.

BP as an important cardiovascular function parameter displays a circadian rhythm, with clear day–night variability in a 24-hour cycle controlled by the central circadian clock.31 The profile of diurnal changes in BP is constituted by 24-hour BP levels, variability and circadian rhythms. The trajectory patterns of short-term and long-term visit-to-visit BP have been established and have shown to be associated with cardiovascular events.32 Recently, a piecewise linear random effects model has been proposed to identify 24-hour ABP trajectory groups25; however, this model has not been applied for prediction of stroke outcomes. In the present study, we developed a novel profile clustering method, and three distinct ABP profile groups were identified. Stroke patients in group 3 who had sustained higher nocturnal SBP compared with those in group 1 showed an increased risk of stroke recurrence. However, when individual ABP parameters were analysed separately with adjustment for covariates, none of them was significantly associated with stroke recurrence. These findings suggest that our novel profile clustering approach is superior to the traditional analysis of individual ABP parameters in relation to stroke outcome.

Elevated nocturnal BP or non-dippers at night have long been recognised as a strong predictor of cardiovascular and cerebrovascular disease in numerous clinical and epidemiologic studies.8 33–36 The current study aimed to assess the predictive value of the ABP profile patterns as well as individual BP parameters for stroke recurrence. The most characteristic feature of the profile pattern of group 3 classified in this study was significantly lower daytime SBP and increased nocturnal SBP with 68.1% reverse dippers. It is obvious that the association between the profile pattern of group 3 and stroke recurrence was mainly driven by the consistently higher night-time SBP levels. However, it is worthy to be noted that night-time SBP, ST SBP, non-dippers and reverse dippers at night did not significantly predict the risk of stroke recurrence after adjusting for confounding variables. Our results suggest an idea that the significant association between circadian BP profile patterns and stroke recurrence depends on not only the elevated nocturnal BP but also other ABP parameters with weak additive effects.

Another important finding was that MS may not have enough predictive power for stroke recurrence. Our result showed that profile 2 with higher MS did not have significant higher risk of stroke recurrence compared with profile 1. Moreover, the amplitude of MS of profile 3, which had the highest risk of stroke recurrence was lowest among three profiles. In fact, previous studies concerning the predictive value of MS for stroke also showed conflicting results.37–39 And some study revealed that the reverse dippers were associated with blunted MS, so it is reverse dippers but not the accompanying blunted MS accounting for stroke risk.40 This, in other hand, emphasise the importance of the elevated night-time BP (NBP) on stroke prognosis rather than MS. While, previous study also reported that the prognostic predictive value of MS could only be found in the dippers rather than non-dippers.8 Considering the high prevalence of non-dippers in the three profiles, MS might have little effect on stroke risk prediction. Higher NBP might partly explained the higher stroke risk of profile 2 in contrast to profile 1, although the difference was insignificant. It could be due to the relatively small difference between the NBPs of the two profiles, and larger samples might be needed.

Our study had some limitations. First, there may be enrolment bias in our study population, which have more mild stroke patients, and low proportion of atrial fibrillation enrolled. Therefore, our findings may not be generalisable to all stroke patients. Second, the number of patients included in this study seemed to be low to justify the lack of prognostic value of conventional individual ABP parameters (dipping pattern, MS, etc). Third, follow-up data were unavailable in the validation group, we could not examin the prognostic significance of the new obtained profile.

Conclusions

Of note, night-time SBP, ST SBP, non-dippers and reverse dippers at night did not significantly predict the risk of stroke recurrence after adjusting for covariates. These results suggest that ambulatory 24-hour SBP profile pattern is more strongly associated with short-term stroke recurrence in stroke patients compared with individual ABP parameters. Profile patterns of ABP may help improve identification of stroke patients at a high risk of adverse clinical outcomes by capturing the additive effects of individual ABP parameters.

Data availability statement

Data are available upon reasonable request. All data are available to researchers on request for purposes of reproducing the results or replicating the procedure by directly contacting the corresponding author.

Ethics statements

Patient consent for publication

Not required.

Footnotes

  • Contributors All authors were involved in the interpretation of study results and approval of the final version of the manuscript. YW had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. JX, HS and YW contributed to the study concept and design. JX, JM and ZC contributed to the drafting of the manuscript. FJ, HZ, YG and JT contributed to the acquisition of data. AW, HS, TZ and WC contributed to statistical analysis. AX, BL, BH, YZ, XZ, YW and HL contributed to critical revision of the manuscript for important intellectual content.

  • Funding This study was funded by National Natural Science Foundation of China, Beijing Municipal Science & Technology Commission, China Postdoctoral Science Foundation, National Science and Technology Major Project, Young Scientist Program of Beijing Tiantan hospital and National Key R&D Program of China.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

References

  1. ↵
    1. O'Donnell MJ ,
    2. Xavier D ,
    3. Liu L , et al
    . Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet 2010;376:112–23.doi:10.1016/S0140-6736(10)60834-3 pmid:http://www.ncbi.nlm.nih.gov/pubmed/20561675
    OpenUrlCrossRefPubMedWeb of Science
  2. ↵
    1. Webb AJS ,
    2. Fischer U ,
    3. Mehta Z , et al
    . Effects of antihypertensive-drug class on interindividual variation in blood pressure and risk of stroke: a systematic review and meta-analysis. Lancet 2010;375:906–15.doi:10.1016/S0140-6736(10)60235-8 pmid:http://www.ncbi.nlm.nih.gov/pubmed/20226989
    OpenUrlCrossRefPubMedWeb of Science
  3. ↵
    1. Mancia G ,
    2. Verdecchia P
    . Clinical value of ambulatory blood pressure: evidence and limits. Circ Res 2015;116:1034–45.doi:10.1161/CIRCRESAHA.116.303755 pmid:http://www.ncbi.nlm.nih.gov/pubmed/25767288
    OpenUrlAbstract/FREE Full Text
  4. ↵
    1. Staessen JA ,
    2. Beilin L ,
    3. Parati G , et al
    . Task force IV: clinical use of ambulatory blood pressure monitoring. participants of the 1999 consensus conference on ambulatory blood pressure monitoring. Blood Press Monit 1999;4:319–31.doi:10.1097/00126097-199912000-00005 pmid:http://www.ncbi.nlm.nih.gov/pubmed/10602536
    OpenUrlPubMed
  5. ↵
    1. Bilo G ,
    2. Grillo A ,
    3. Guida V , et al
    . Morning blood pressure surge: pathophysiology, clinical relevance and therapeutic aspects. Integr Blood Press Control 2018;11:47–56.doi:10.2147/IBPC.S130277 pmid:http://www.ncbi.nlm.nih.gov/pubmed/29872338
    OpenUrlPubMed
  6. ↵
    1. Kario K ,
    2. Pickering TG ,
    3. Umeda Y , et al
    . Morning surge in blood pressure as a predictor of silent and clinical cerebrovascular disease in elderly hypertensives: a prospective study. Circulation 2003;107:1401–6.doi:10.1161/01.CIR.0000056521.67546.AA pmid:http://www.ncbi.nlm.nih.gov/pubmed/12642361
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Kario K ,
    2. Pickering TG ,
    3. Matsuo T , et al
    . Stroke prognosis and abnormal nocturnal blood pressure falls in older hypertensives. Hypertension 2001;38:852–7.doi:10.1161/hy1001.092640 pmid:http://www.ncbi.nlm.nih.gov/pubmed/11641298
    OpenUrlCrossRefPubMed
  8. ↵
    1. Pierdomenico SD ,
    2. Pierdomenico AM ,
    3. Cuccurullo F
    . Morning blood pressure surge, dipping, and risk of ischemic stroke in elderly patients treated for hypertension. Am J Hypertens 2014;27:564–70.doi:10.1093/ajh/hpt170 pmid:http://www.ncbi.nlm.nih.gov/pubmed/24048146
    OpenUrlCrossRefPubMed
  9. ↵
    1. Verdecchia P ,
    2. Schillaci G ,
    3. Reboldi G , et al
    . Different prognostic impact of 24-hour mean blood pressure and pulse pressure on stroke and coronary artery disease in essential hypertension. Circulation 2001;103:2579–84.doi:10.1161/01.CIR.103.21.2579 pmid:http://www.ncbi.nlm.nih.gov/pubmed/11382727
    OpenUrlAbstract/FREE Full Text
  10. ↵
    1. Metoki H ,
    2. Ohkubo T ,
    3. Kikuya M , et al
    . Prognostic significance for stroke of a morning pressor surge and a nocturnal blood pressure decline. Hypertension 2006;47:149–54.doi:10.1161/01.HYP.0000198541.12640.0f
    OpenUrlCrossRefPubMed
  11. ↵
    1. Neutel JM
    . The importance of 24-h blood pressure control. Blood Press Monit 2001;6:9–16.doi:10.1097/00126097-200102000-00002 pmid:http://www.ncbi.nlm.nih.gov/pubmed/11248755
    OpenUrlCrossRefPubMedWeb of Science
  12. ↵
    1. Kikuya M ,
    2. Ohkubo T ,
    3. Asayama K , et al
    . Ambulatory blood pressure and 10-year risk of cardiovascular and noncardiovascular mortality: the Ohasama study. Hypertension 2005;45:240–5.doi:10.1161/01.HYP.0000152079.04553.2c pmid:http://www.ncbi.nlm.nih.gov/pubmed/15596571
    OpenUrlCrossRefPubMed
  13. ↵
    1. Boggia J ,
    2. Li Y ,
    3. Thijs L , et al
    . Prognostic accuracy of day versus night ambulatory blood pressure: a cohort study. Lancet 2007;370:1219–29.doi:10.1016/S0140-6736(07)61538-4 pmid:http://www.ncbi.nlm.nih.gov/pubmed/17920917
    OpenUrlCrossRefPubMedWeb of Science
  14. ↵
    1. Hansen TW ,
    2. Jeppesen J ,
    3. Rasmussen S , et al
    . Ambulatory blood pressure and mortality: a population-based study. Hypertension 2005;45:499–504.doi:10.1161/01.HYP.0000160402.39597.3b pmid:http://www.ncbi.nlm.nih.gov/pubmed/15753229
    OpenUrlCrossRefPubMed
  15. ↵
    1. Clement DL ,
    2. De Buyzere ML ,
    3. De Bacquer DA , et al
    . Prognostic value of ambulatory blood-pressure recordings in patients with treated hypertension. N Engl J Med 2003;348:2407–15.doi:10.1056/NEJMoa022273 pmid:http://www.ncbi.nlm.nih.gov/pubmed/12802026
    OpenUrlCrossRefPubMedWeb of Science
  16. ↵
    1. Banegas JR ,
    2. Ruilope LM ,
    3. de la Sierra A , et al
    . Relationship between clinic and ambulatory blood-pressure measurements and mortality. N Engl J Med 2018;378:1509–20.doi:10.1056/NEJMoa1712231 pmid:http://www.ncbi.nlm.nih.gov/pubmed/29669232
    OpenUrlCrossRefPubMed
  17. ↵
    1. Manning LS ,
    2. Rothwell PM ,
    3. Potter JF , et al
    . Prognostic significance of short-term blood pressure variability in acute stroke: systematic review. Stroke 2015;46:2482–90.doi:10.1161/STROKEAHA.115.010075 pmid:http://www.ncbi.nlm.nih.gov/pubmed/26243226
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Kakaletsis N ,
    2. Ntaios G ,
    3. Milionis H , et al
    . Prognostic value of 24-h ABPM in acute ischemic stroke for short-, medium-, and long-term outcome: a systematic review and meta-analysis. Int J Stroke 2015;10:1000–7.doi:10.1111/ijs.12609 pmid:http://www.ncbi.nlm.nih.gov/pubmed/26283262
    OpenUrlCrossRefPubMed
  19. ↵
    1. Tsivgoulis G ,
    2. Spengos K ,
    3. Zakopoulos N , et al
    . Twenty four hour pulse pressure predicts long term recurrence in acute stroke patients. J Neurol Neurosurg Psychiatry 2005;76:1360–5.doi:10.1136/jnnp.2004.057265 pmid:http://www.ncbi.nlm.nih.gov/pubmed/16170077
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Dolan E ,
    2. Stanton A ,
    3. Thijs L , et al
    . Superiority of ambulatory over clinic blood pressure measurement in predicting mortality: the Dublin outcome study. Hypertension 2005;46:156–61.doi:10.1161/01.HYP.0000170138.56903.7a pmid:http://www.ncbi.nlm.nih.gov/pubmed/15939805
    OpenUrlCrossRefPubMed
  21. ↵
    1. Mancia G ,
    2. Facchetti R ,
    3. Bombelli M , et al
    . Long-Term risk of mortality associated with selective and combined elevation in office, home, and ambulatory blood pressure. Hypertension 2006;47:846–53.doi:10.1161/01.HYP.0000215363.69793.bb pmid:http://www.ncbi.nlm.nih.gov/pubmed/16567588
    OpenUrlCrossRefPubMed
  22. ↵
    1. Izzedine H ,
    2. Launay-Vacher V ,
    3. Deray G
    . Abnormal blood pressure circadian rhythm: a target organ damage? Int J Cardiol 2006;107:343–9.doi:10.1016/j.ijcard.2005.03.046 pmid:http://www.ncbi.nlm.nih.gov/pubmed/16503256
    OpenUrlCrossRefPubMedWeb of Science
  23. ↵
    1. Maeda K ,
    2. Yasunari K ,
    3. Watanabe T , et al
    . Oxidative stress by peripheral blood mononuclear cells is increased in hypertensives with an extreme-dipper pattern and/or morning surge in blood pressure. Hypertens Res 2005;28:755–61.doi:10.1291/hypres.28.755 pmid:http://www.ncbi.nlm.nih.gov/pubmed/16419649
    OpenUrlCrossRefPubMed
  24. ↵
    1. Kario K
    . Vascular damage in exaggerated morning surge in blood pressure. Hypertension 2007;49:771–2.doi:10.1161/01.HYP.0000259736.67231.18 pmid:http://www.ncbi.nlm.nih.gov/pubmed/17325233
    OpenUrlCrossRefPubMed
  25. ↵
    1. Madden JM ,
    2. Li X ,
    3. Kearney PM , et al
    . Exploring diurnal variation using piecewise linear splines: an example using blood pressure. Emerg Themes Epidemiol 2017;14:1. doi:10.1186/s12982-017-0055-5 pmid:http://www.ncbi.nlm.nih.gov/pubmed/28184234
    OpenUrlCrossRefPubMed
  26. ↵
    1. Xu J ,
    2. Liu Y ,
    3. Tao Y , et al
    . The design, rationale, and baseline characteristics of a nationwide cohort registry in China: blood pressure and clinical outcome in TIA or ischemic stroke. Patient Prefer Adherence 2016;10:2419–27.doi:10.2147/PPA.S119825 pmid:http://www.ncbi.nlm.nih.gov/pubmed/27942205
    OpenUrlPubMed
  27. ↵
    1. Chiou J-M ,
    2. Li P-L
    . Functional clustering and identifying substructures of longitudinal data. J Royal Statistical Soc B 2007;69:679–99.doi:10.1111/j.1467-9868.2007.00605.x
    OpenUrl
  28. ↵
    1. Pickering TG ,
    2. Shimbo D ,
    3. Haas D
    . Ambulatory blood-pressure monitoring. N Engl J Med 2006;354:2368–74.doi:10.1056/NEJMra060433 pmid:http://www.ncbi.nlm.nih.gov/pubmed/16738273
    OpenUrlCrossRefPubMedWeb of Science
  29. ↵
    1. Zis P ,
    2. Vemmos K ,
    3. Spengos K , et al
    . Ambulatory blood pressure monitoring in acute stroke: pathophysiology of the time rate of blood pressure variation and association with the 1-year outcome. Blood Press Monit 2013;18:94–100.doi:10.1097/MBP.0b013e32835ebc3f pmid:http://www.ncbi.nlm.nih.gov/pubmed/23388403
    OpenUrlPubMed
  30. ↵
    1. Tomii Y ,
    2. Toyoda K ,
    3. Suzuki R , et al
    . Effects of 24-hour blood pressure and heart rate recorded with ambulatory blood pressure monitoring on recovery from acute ischemic stroke. Stroke 2011;42:3511–7.doi:10.1161/STROKEAHA.111.628586 pmid:http://www.ncbi.nlm.nih.gov/pubmed/21960578
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Goncharuk VD ,
    2. van Heerikhuize J ,
    3. Dai JP , et al
    . Neuropeptide changes in the suprachiasmatic nucleus in primary hypertension indicate functional impairment of the biological clock. J Comp Neurol 2001;431:320–30.doi:10.1002/1096-9861(20010312)431:3&lt;320::AID-CNE1073&gt;3.0.CO;2-2 pmid:http://www.ncbi.nlm.nih.gov/pubmed/11170008
    OpenUrlCrossRefPubMedWeb of Science
  32. ↵
    1. Allen NB ,
    2. Siddique J ,
    3. Wilkins JT , et al
    . Blood pressure trajectories in early adulthood and subclinical atherosclerosis in middle age. JAMA 2014;311:490–7.doi:10.1001/jama.2013.285122 pmid:http://www.ncbi.nlm.nih.gov/pubmed/24496536
    OpenUrlCrossRefPubMedWeb of Science
  33. ↵
    1. Fagard RH ,
    2. Celis H ,
    3. Thijs L , et al
    . Daytime and nighttime blood pressure as predictors of death and cause-specific cardiovascular events in hypertension. Hypertension 2008;51:55–61.doi:10.1161/HYPERTENSIONAHA.107.100727 pmid:http://www.ncbi.nlm.nih.gov/pubmed/18039980
    OpenUrlCrossRefPubMed
  34. ↵
    1. Routledge FS ,
    2. McFetridge-Durdle JA ,
    3. Dean CR , et al
    . Night-Time blood pressure patterns and target organ damage: a review. Can J Cardiol 2007;23:132–8.doi:10.1016/S0828-282X(07)70733-X pmid:http://www.ncbi.nlm.nih.gov/pubmed/17311119
    OpenUrlCrossRefPubMed
  35. ↵
    1. Hansen TW ,
    2. Li Y ,
    3. Boggia J , et al
    . Predictive role of the nighttime blood pressure. Hypertension 2011;57:3–10.doi:10.1161/HYPERTENSIONAHA.109.133900 pmid:http://www.ncbi.nlm.nih.gov/pubmed/21079049
    OpenUrlCrossRefPubMed
  36. ↵
    1. Hermida RC ,
    2. Crespo JJ ,
    3. Otero A , et al
    . Asleep blood pressure: significant prognostic marker of vascular risk and therapeutic target for prevention. Eur Heart J 2018;39:4159–71.doi:10.1093/eurheartj/ehy475 pmid:http://www.ncbi.nlm.nih.gov/pubmed/30107515
    OpenUrlPubMed
  37. ↵
    1. Metoki H ,
    2. Ohkubo T ,
    3. Kikuya M , et al
    . Prognostic significance for stroke of a morning pressor surge and a nocturnal blood pressure decline: the Ohasama study. Hypertension 2006;47:149–54.doi:10.1161/01.HYP.0000198541.12640.0f pmid:http://www.ncbi.nlm.nih.gov/pubmed/16380533
    OpenUrlCrossRefPubMed
  38. ↵
    1. Kario K
    . Morning surge in blood pressure and cardiovascular risk: evidence and perspectives. Hypertension 2010;56:765–73.doi:10.1161/HYPERTENSIONAHA.110.157149 pmid:http://www.ncbi.nlm.nih.gov/pubmed/20937968
    OpenUrlCrossRefPubMed
  39. ↵
    1. Cheng H-M ,
    2. Wu C-L ,
    3. Sung S-H , et al
    . Prognostic utility of morning blood pressure surge for 20-year all-cause and cardiovascular mortalities: results of a community-based study. J Am Heart Assoc 2017;6:e007667. doi:10.1161/JAHA.117.007667 pmid:http://www.ncbi.nlm.nih.gov/pubmed/29223957
    OpenUrlAbstract/FREE Full Text
  40. ↵
    1. Fujiwara T ,
    2. Tomitani N ,
    3. Sato K , et al
    . The relationship between a blunted morning surge and a reversed nocturnal blood pressure dipping or “riser” pattern. J Clin Hypertens 2017;19:1108–14.doi:10.1111/jch.13087
    OpenUrl
PreviousNext
Back to top
Vol 6 Issue 3 Table of Contents
Stroke and Vascular Neurology: 6 (3)
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Front Matter (PDF)
Email

Thank you for your interest in spreading the word on Stroke and Vascular Neurology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Ambulatory blood pressure profile and stroke recurrence
(Your Name) has sent you a message from Stroke and Vascular Neurology
(Your Name) thought you would like to see the Stroke and Vascular Neurology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
Alerts
Sign In to Email Alerts with your Email Address
Citation Tools
Ambulatory blood pressure profile and stroke recurrence
Jie Xu, Fei Jiang, Anxin Wang, Hui Zhi, Yuan Gao, Junping Tian, Jinglin Mo, Zimo Chen, An-Ding Xu, Benyan Luo, Bo Hu, Yuqing Zhang, Xingquan Zhao, Yilong Wang, Hao Li, Haipeng Shen, Yongjun Wang
Stroke and Vascular Neurology Sep 2021, 6 (3) 352-358; DOI: 10.1136/svn-2020-000526

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Cite This
  • APA
  • Chicago
  • Endnote
  • MLA
Loading
Ambulatory blood pressure profile and stroke recurrence
Jie Xu, Fei Jiang, Anxin Wang, Hui Zhi, Yuan Gao, Junping Tian, Jinglin Mo, Zimo Chen, An-Ding Xu, Benyan Luo, Bo Hu, Yuqing Zhang, Xingquan Zhao, Yilong Wang, Hao Li, Haipeng Shen, Yongjun Wang
Stroke and Vascular Neurology Sep 2021, 6 (3) 352-358; DOI: 10.1136/svn-2020-000526
Download PDF

Share
Ambulatory blood pressure profile and stroke recurrence
Jie Xu, Fei Jiang, Anxin Wang, Hui Zhi, Yuan Gao, Junping Tian, Jinglin Mo, Zimo Chen, An-Ding Xu, Benyan Luo, Bo Hu, Yuqing Zhang, Xingquan Zhao, Yilong Wang, Hao Li, Haipeng Shen, Yongjun Wang
Stroke and Vascular Neurology Sep 2021, 6 (3) 352-358; DOI: 10.1136/svn-2020-000526
Reddit logo Twitter logo Facebook logo Mendeley logo
Respond to this article
  • Tweet Widget
  • Facebook Like
  • Google Plus One
  • Article
    • Abstract
    • Introduction
    • Methods
    • Results
    • Discussion
    • Conclusions
    • Data availability statement
    • Ethics statements
    • Footnotes
    • References
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • Stepwise improvement in intracerebral haematoma expansion prediction with advanced imaging: a comprehensive comparison of existing scores
  • Learning curve and embolisation strategy in single-stage surgery combined embolisation and microsurgery for brain arteriovenous malformations: results from a nationwide multicentre prospective registry study
  • Thrombus iodine-based perviousness is associated with recanalisation and functional outcomes in endovascular thrombectomy
Show more Original research

Similar Articles

 
 

CONTENT

  • Latest content
  • Current issue
  • Archive
  • eLetters
  • Sign up for email alerts
  • RSS

JOURNAL

  • About the journal
  • Editorial board
  • Recommend to librarian
  • Chinese Stroke Association

AUTHORS

  • Instructions for authors
  • Submit a paper
  • Track your article
  • Open Access at BMJ

HELP

  • Contact us
  • Reprints
  • Permissions
  • Advertising
  • Feedback form

© 2025 Chinese Stroke Association