Literature DB >> 25319600

Does blood pressure variability contribute to risk stratification? Methodological issues and a review of outcome studies based on home blood pressure.

Kei Asayama1, Fang-Fei Wei2, Yan-Ping Liu3, Azusa Hara3, Yu-Mei Gu3, Rudolph Schutte4, Yan Li5, Lutgarde Thijs3, Jan A Staessen6.   

Abstract

This review addresses methodological issues in the assessment of blood pressure variability and the predictive value of blood pressure variability derived from blood pressure readings obtained in the relaxed home environment. Preference should be given to indexes of blood pressure variability that are independent of the mean because we should evaluate the impact of blood pressure variability by eliminating the effect of blood pressure levels. Beat-to-beat blood pressure recordings outperform home blood pressure measurement in the assessment of blood pressure variability in longitudinal Belgian and Japanese population studies, whereas blood pressure variability did not incrementally predict outcome beyond blood pressure level and other cardiovascular risk factors. In conclusion, clinicians should focus on blood pressure level, given that it is the predominant risk factor and is manageable by lifestyle modifications and adequate antihypertensive drug treatment. Blood pressure variability remains a research tool that requires further prospective studies with hard end points to define its potential application, as it may be potentially useful in daily clinical practice.

Mesh:

Year:  2014        PMID: 25319600     DOI: 10.1038/hr.2014.153

Source DB:  PubMed          Journal:  Hypertens Res        ISSN: 0916-9636            Impact factor:   3.872


  41 in total

1.  Use of 2003 European Society of Hypertension-European Society of Cardiology guidelines for predicting stroke using self-measured blood pressure at home: the Ohasama study.

Authors:  Kei Asayama; Takayoshi Ohkubo; Masahiro Kikuya; Hirohito Metoki; Taku Obara; Haruhisa Hoshi; Junichiro Hashimoto; Kazuhito Totsune; Hiroshi Satoh; Yutaka Imai
Journal:  Eur Heart J       Date:  2005-05-25       Impact factor: 29.983

2.  Day-night dip and early-morning surge in blood pressure in hypertension: prognostic implications.

Authors:  Paolo Verdecchia; Fabio Angeli; Giovanni Mazzotta; Marta Garofoli; Elisa Ramundo; Giorgio Gentile; Giuseppe Ambrosio; Gianpaolo Reboldi
Journal:  Hypertension       Date:  2012-05-14       Impact factor: 10.190

3.  The coefficient variation of home blood pressure is a novel factor associated with macroalbuminuria in type 2 diabetes mellitus.

Authors:  Emi Ushigome; Michiaki Fukui; Masahide Hamaguchi; Takafumi Senmaru; Kazumi Sakabe; Muhei Tanaka; Masahiro Yamazaki; Goji Hasegawa; Naoto Nakamura
Journal:  Hypertens Res       Date:  2011-08-04       Impact factor: 3.872

4.  Home blood pressure variability on one occasion is a novel factor associated with arterial stiffness in patients with type 2 diabetes.

Authors:  Michiaki Fukui; Emi Ushigome; Muhei Tanaka; Masahide Hamaguchi; Toru Tanaka; Haruhiko Atsuta; Masayoshi Ohnishi; Yohei Oda; Goji Hasegawa; Naoto Nakamura
Journal:  Hypertens Res       Date:  2012-10-25       Impact factor: 3.872

5.  Relationship of 24-hour blood pressure mean and variability to severity of target-organ damage in hypertension.

Authors:  G Parati; G Pomidossi; F Albini; D Malaspina; G Mancia
Journal:  J Hypertens       Date:  1987-02       Impact factor: 4.844

6.  Prognostic value of reading-to-reading blood pressure variability over 24 hours in 8938 subjects from 11 populations.

Authors:  Tine W Hansen; Lutgarde Thijs; Yan Li; José Boggia; Masahiro Kikuya; Kristina Björklund-Bodegård; Tom Richart; Takayoshi Ohkubo; Jørgen Jeppesen; Christian Torp-Pedersen; Eamon Dolan; Tatiana Kuznetsova; Katarzyna Stolarz-Skrzypek; Valérie Tikhonoff; Sofia Malyutina; Edoardo Casiglia; Yuri Nikitin; Lars Lind; Edgardo Sandoya; Kalina Kawecka-Jaszcz; Yutaka Imai; Jiguang Wang; Hans Ibsen; Eoin O'Brien; Jan A Staessen
Journal:  Hypertension       Date:  2010-03-08       Impact factor: 10.190

7.  Cardiovascular outcomes in the first trial of antihypertensive therapy guided by self-measured home blood pressure.

Authors:  Kei Asayama; Takayoshi Ohkubo; Hirohito Metoki; Taku Obara; Ryusuke Inoue; Masahiro Kikuya; Lutgarde Thijs; Jan A Staessen; Yutaka Imai
Journal:  Hypertens Res       Date:  2012-08-16       Impact factor: 3.872

8.  Relationships between metrics of visit-to-visit variability of blood pressure.

Authors:  E B Levitan; N Kaciroti; S Oparil; S Julius; P Muntner
Journal:  J Hum Hypertens       Date:  2013-03-28       Impact factor: 3.012

9.  Home blood pressure variability as cardiovascular risk factor in the population of Ohasama.

Authors:  Kei Asayama; Masahiro Kikuya; Rudolph Schutte; Lutgarde Thijs; Miki Hosaka; Michihiro Satoh; Azusa Hara; Taku Obara; Ryusuke Inoue; Hirohito Metoki; Takuo Hirose; Takayoshi Ohkubo; Jan A Staessen; Yutaka Imai
Journal:  Hypertension       Date:  2012-11-19       Impact factor: 10.190

Review 10.  Effects of antihypertensive-drug class on interindividual variation in blood pressure and risk of stroke: a systematic review and meta-analysis.

Authors:  Alastair J S Webb; Urs Fischer; Ziyah Mehta; Peter M Rothwell
Journal:  Lancet       Date:  2010-03-13       Impact factor: 79.321

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  10 in total

1.  The effects of increasing calcium channel blocker dose vs. adding a diuretic to treatment regimens for patients with uncontrolled hypertension.

Authors:  Shigemasa Tani; Kei Asayama; Koji Oiwa; Shinsuke Harasawa; Katsuaki Okubo; Atsuhiko Takahashi; Ayumi Tanabe; Takayoshi Ohkubo; Atsushi Hirayama; Toshio Kushiro
Journal:  Hypertens Res       Date:  2017-04-27       Impact factor: 3.872

2.  Analysis of beat-to-beat blood pressure variability response to the cold pressor test in the offspring of hypertensive and normotensive parents.

Authors:  Dan Wu; Lin Xu; Derek Abbott; William Kongto Hau; Lijie Ren; Heye Zhang; Kelvin K L Wong
Journal:  Hypertens Res       Date:  2017-02-09       Impact factor: 3.872

3.  Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium.

Authors:  Ang Li; Quan Zhou; Yayuan Mei; Jiaxin Zhao; Meiduo Zhao; Jing Xu; Xiaoyu Ge; Qun Xu
Journal:  Front Nutr       Date:  2022-05-30

4.  Excessive variability in systolic blood pressure that is self-measured at home exacerbates the progression of brain white matter lesions and cognitive impairment in the oldest old.

Authors:  Zhendong Liu; Yingxin Zhao; Hua Zhang; Qiang Chai; Yi Cui; Yutao Diao; Jianchao Xiu; Xiaolin Sun; Guosheng Jiang
Journal:  Hypertens Res       Date:  2015-12-03       Impact factor: 3.872

Review 5.  Hypertension, Blood Pressure Variability, and Target Organ Lesion.

Authors:  Maria-Cláudia Irigoyen; Kátia De Angelis; Fernando Dos Santos; Daniela R Dartora; Bruno Rodrigues; Fernanda Marciano Consolim-Colombo
Journal:  Curr Hypertens Rep       Date:  2016-04       Impact factor: 5.369

Review 6.  The dawning of the digital era in the management of hypertension.

Authors:  Ryo Matsuoka; Hiroshi Akazawa; Satoshi Kodera; Issei Komuro
Journal:  Hypertens Res       Date:  2020-07-13       Impact factor: 3.872

7.  High Short-Term Blood Pressure Variability Predicts Long-Term Cardiovascular Mortality in Untreated Hypertensives But Not in Normotensives.

Authors:  Pai-Feng Hsu; Hao-Min Cheng; Cheng-Hsueh Wu; Shih-Hsien Sung; Shao-Yuan Chuang; Edward G Lakatta; Frank C P Yin; Pesus Chou; Chen-Huan Chen
Journal:  Am J Hypertens       Date:  2016-02-01       Impact factor: 2.689

8.  Home blood pressure and cardiovascular risk in treated hypertensive patients: the prognostic value of the first and second measurements and the difference between them in the HONEST study.

Authors:  Ikuo Saito; Kazuomi Kario; Toshio Kushiro; Satoshi Teramukai; Mai Yaginuma; Yoshihiro Mori; Yasuyuki Okuda; Kazuyuki Shimada
Journal:  Hypertens Res       Date:  2016-08-04       Impact factor: 3.872

9.  Blood pressure variability is related to faster cognitive decline in ischemic stroke patients: PICASSO subanalysis.

Authors:  Ju-Hun Lee; Sun U Kwon; Yerim Kim; Jae-Sung Lim; Mi Sun Oh; Kyung-Ho Yu; Ji Sung Lee; Jong-Ho Park; Yong-Jae Kim; Joung-Ho Rha; Yang-Ha Hwang; Sung Hyuk Heo; Seong Hwan Ahn
Journal:  Sci Rep       Date:  2021-03-03       Impact factor: 4.379

10.  Visit-to-visit office blood pressure variability combined with Framingham risk score to predict all-cause mortality: A post hoc analysis of the systolic blood pressure intervention trial.

Authors:  Yi Cheng; Jian Li; Xinping Ren; Dan Wang; Yulin Yang; Ya Miao; Chang-Sheng Sheng; Jingyan Tian
Journal:  J Clin Hypertens (Greenwich)       Date:  2021-07-03       Impact factor: 3.738

  10 in total

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