Michael R. Pinsky, MD, CM, Dr hc, FCCP, MCCM

  • Vice Chair Emeritus
  • Director, Cardiopulmonary Research Laboratory
  • Professor of Critical Care Medicine, Bioengineering, Anesthesiology, Cardiovascular Diseases, and Clinical & Translational Science
  • Senior Advisor, Center for Military Medicine Research

    Education & Training

  • BS, Molecular Genetics and Physiologic Psychology, McGill University, 1971
  • MD, CM, Medicine, McGill University, 1974
  • Residency, Internal Medicine, Stanford University, 1976
  • Fellowship, Internal/Pulmonary Medicine, Stanford University, 1978
  • Fellowship, Pulmonary Medicine/Environmental Physics, John Hopkins University, 1981
  • MBA, Health Care Economics, University of Pittsburgh, 2001
Fellow of the American Physiological Society
Docteur honoris causa, University of Paris V (Le Sorbonne), 2002
Master of the College of Critical Care Medicine, 2011
SMART Award for Distinguished Achievement in Critical Care, 2014
Representative Publications

Buda AJ, Pinsky MR, Ingels Jr NB, Daughters GT, Stinson EB, Alderman EL. Effect of intrathoracic pressure on left ventricular performance. New England Journal of Medicine. 1979 Aug 30;301(9):453-9. 

Michard F, Boussat S, Chemla D, Anguel N, Mercat A, Lecarpentier Y, Richard C, Pinsky MR, Teboul JL. Relation between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. American journal of respiratory and critical care medicine. 2000 Jul 1;162(1):134-8. 

Guarracino F, Bertini P, Pinsky MR. Cardiovascular determinants of resuscitation from sepsis and septic shock. Critical Care. 2019 Dec;23(1):118.

Pinsky MR, Dubrawski A. Gleaning knowledge from data in the intensive care unit. American journal of respiratory and critical care medicine. 2014 Sep 15;190(6):606-10.

Research Interests
  • Effects of ventilation on cardiovascular function
  • Functional hemodynamic monitoring as a precision diagnostic tool for cardiorespiratory insufficiency
  • Left ventricular pump function and dysfunction in the setting of regional wall motion abnormalities
  • Machine learning to glean knowledge from data in defining health and disease