A clinical, proteomics, and artificial intelligence-driven model to predict acute kidney injury in patients undergoing coronary angiography.

Journal: Clinical cardiology
Published Date: Feb 1, 2019

Abstract

BACKGROUND: Standard measures of kidney function are only modestly useful for accurate prediction of risk for acute kidney injury (AKI).

Authors

  • Nasrien E Ibrahim
    Cardiology Division, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA.
  • Cian P McCarthy
    Cardiology Division, Massachusetts General Hospital, Boston, MA.
  • Shreya Shrestha
    Cardiology Division, Massachusetts General Hospital, Boston, MA.
  • Hanna K Gaggin
    Cardiology Division, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA.
  • Renata Mukai
    Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts.
  • Craig A Magaret
    Prevencio, Inc., Kirkland, Washington.
  • Rhonda F Rhyne
    Prevencio, Inc., Kirkland, Washington.
  • James L Januzzi
    Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

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