Deep Learning and Multivariable Models Select EVAR Patients for Short-Stay Discharge.

Journal: Vascular and endovascular surgery
Published Date: Jan 1, 2021

Abstract

OBJECTIVES: We sought to develop a prediction score with data from the Vascular Quality Initiative (VQI) EVAR in efforts to assist endovascular specialists in deciding whether or not a patient is appropriate for short-stay discharge.

Authors

  • Devin S Zarkowsky
    Division of Vascular and Endovascular Surgery, 1878University of Colorado, Aurora, CO, USA.
  • Besma Nejim
    Division of Vascular Surgery and Endovascular Therapy, 1466The Johns Hopkins Medical Institutions, Baltimore, MD, USA.
  • Itay Hubara
    Department of Mechanical Engineering and Computer Science, Technion, Haifa, Israel.
  • Caitlin W Hicks
    Division of Vascular Surgery and Endovascular Therapy, 1466The Johns Hopkins Medical Institutions, Baltimore, MD, USA.
  • Philip P Goodney
    VA Outcomes Group, White River Junction VA Medical Center, White River Junction, VT; The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth College, Hanover, NH.
  • Mahmoud B Malas
    Department of Surgery, Division of Vascular & Endovascular Surgery, University of California San Diego, San Diego, California, The United States of America. Electronic address: mmalas@health.ucsd.edu.

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