Researcher

    Michaël Sauthier , M.D. , Ph.D.

    michael.sauthier@umontreal.ca
    Michaël Sauthier
    Research Axis
    Infectious Diseases and Acute Care Axis
    Research Theme
    Critical care, trauma and transfusions

    Phone
    (514) 345-4931 ext.7012

    Title

    • Clinical Assistant Professor, Université de Montréal

    Education

    • PhD, Université de Montréal, 2021
    • MBI, Harvard Medical School, 2020
    • Pediatric Critical Care, Université de Montréal, 2018
    • Pediatrics, Université de Montréal, 2015
    • MD, Université de Montréal (Mauricie) 2012

    Research Interests

    I am specifically interested in the automatic diagnosis and management of oxygen deprivation (hypoxemia) for patients admitted to pediatric intensive care. Automatically diagnosing this entity will potentially allow for earlier recognition and treatment of this condition, which could lead to improved respiratory outcomes.

    Research Topics

    • Pediatric Intensive Care
    • Hypoxemia
    • Acute respiratory distress syndrome
    • Clinical Bioinformatics
    • Artificial intelligence
    • Large databases
    • Continuous/big data

    Career Summary

    I specialize in being on the edge between clinical informatics and pediatric critical care medicine. My overall goal is to best utilize informatics to improve healthcare at the bedside of the most critical patients, specifically in the area of respiratory failure.

    Publications

    • Proulx, F. et al. Oxygenation Defects, Ventilatory Ratio, and Mechanical Power During Severe Pediatric Acute Respiratory Distress Syndrome: Longitudinal Time Sequence Analyses in a Single-Center Retrospective Cohort*. Pediatr Crit Care Me 23, 22–33 (2022).
    • Sauthier, M., Tuli, G., Jouvet, P. A., Brownstein, J. S. & Randolph, A. G. Estimated Pao2: A Continuous and Noninvasive Method to Estimate Pao2 and Oxygenation Index. Critical Care Explor 3, e0546 (2021).
    • Sauthier, M. et al. Long-Term Mechanical Ventilation in Neonates: A 10-Year Overview and Predictive Model. Frontiers Pediatrics 9, 689190 (2021).
    • Sauthier, M. et al. Comparison of the Automated Pediatric Logistic Organ Dysfunction-2 Versus Manual Pediatric Logistic Organ Dysfunction-2 Score for Critically Ill Children*. Pediatr Crit Care Me 21, e160–e169 (2020).
    • Sauthier, M. S. et al. Machine Learning Predicts Prolonged Acute Hypoxemic Respiratory Failure in Pediatric Severe Influenza. Critical Care Explor 2, e0175 (2020).
 

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