• DocumentCode
    2038619
  • Title

    Forecasting acute hypotensive episodes in intensive care patients based on a peripheral arterial blood pressure waveform

  • Author

    Chen, Xiaoxiao ; Xu, D. ; Zhang, G. ; Mukkamala, R.

  • Author_Institution
    Michigan State Univ., East Lansing, MI, USA
  • fYear
    2009
  • fDate
    13-16 Sept. 2009
  • Firstpage
    545
  • Lastpage
    548
  • Abstract
    We entered the 10th Annual PhysioNet/Computers in Cardiology Challenge to predict which intensive care patients would experience an acute hypotensive episode (AHE) using physiologic data prior to the occurrence of the AHE. An AHE was defined through mean arterial blood pressure (ABP). We took a pragmatic approach to the Challenge. We explored six basic indices derived from ABP data near the forecast window including mean ABP and diastolic ABP. We evaluated the predictive ability of each index on the provided training dataset and employed basic classification on the testing dataset. All indices performed well on the training dataset and achieved a perfect score for Event 1 of the Challenge and scores from 32/40 to 37/40 for Event 2. However, our best official score was 36/40 for Event 2. These results stress the importance of continuous ABP monitoring in intensive care patients and indicate that sophisticated data analysis was not necessary to win the Challenge.
  • Keywords
    blood pressure measurement; medical administrative data processing; medical computing; patient care; ABP data; Cardiology Challenge; PhysioNet-Computers; acute hypotensive episodes; diastolic ABP; intensive care patients; peripheral arterial blood pressure waveform; physiologic data; pragmatic approach; Arterial blood pressure; Biomedical monitoring; Cardiology; Data analysis; Electrocardiography; Heart rate; Hydrogen; Patient monitoring; Stress; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology, 2009
  • Conference_Location
    Park City, UT
  • ISSN
    0276-6547
  • Print_ISBN
    978-1-4244-7281-9
  • Electronic_ISBN
    0276-6547
  • Type

    conf

  • Filename
    5445348