Power spectral analysis of short term blood pressure predicts daily variation of blood pressure

DOI
  • KINOSHITA HIROYUKI
    Graduate School of Information Science, Nara Institute of Science and Technology Technology development HQ, OMRON Healthcare Co., Ltd.
  • Mannoji Hiroshi
    Department of Cardiovascular Medicine, Graduate School of Medical Sciences, Kyushu University
  • Saku Keita
    Department of Advanced Risk Stratification for Cardiovascular Diseases, Center for Disruptive Cardiovascular Medicine, Kyushu University
  • Kishi Takuya
    Department of Advanced Risk Stratification for Cardiovascular Diseases, Center for Disruptive Cardiovascular Medicine, Kyushu University
  • Kanaya Shigehiko
    Graduate School of Information Science, Nara Institute of Science and Technology
  • Sunagawa Kenji
    Department of Therapeutic Regulation of Cardiovascular Homeostasis, Center for Disruptive Cardiovascular Medicine, Kyushu University

Bibliographic Information

Other Title
  • 短時間連続血圧波形のパワースペクトル解析を用いた長時間血圧変動性の予測

Abstract

<p>OBJECTIVE: Although the daily variation of blood pressure (BP) predicts cardiovascular event risk, the fact that its assessment requires ambulatory BP monitoring makes its clinical application impractical. Since the baroreflex is a major determinant of BP variation especially in the frequency range of 0.01-0.1Hz (baro-F), we hypothesized the power spectral density (PSD) of short-term BP in baro-F predicts the daily variation of BP.</p><p>METHODS: In rats (N=15) with various severities of baroreflex dysfunction, we recorded continuous BP for 12 hours and estimated the standard deviation (SD12H). We estimated PSD using Fourier transform from 30-min continuous BP at 0.01 and 0.1 Hz, and compared their ratio (dPSD) against SD12H.</p><p>RESULTS: dPSD predicted SD12H reasonably well (R2=0.79).</p><p>CONCLUSION: dPSD derived from short-term BP recordings is capable of predicting the daily BP variation. dPSD may serve as a simple, noninvasive and practical predictor of cardiovascular event risk. </p>

Journal

Details 詳細情報について

  • CRID
    1390564238023491200
  • NII Article ID
    130007483960
  • DOI
    10.11239/jsmbe.annual56.s342
  • ISSN
    18814379
    1347443X
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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