Medical Student Research Forum Posters

Continuous BP monitoring is essential to intraoperative care, as hypotensive events can significantly increase the risk of AKI, MI, and mortality post-op1,2 . The Hypotension Prediction Index (HPI) is a novel algorithm derived from machine learning that gives anesthesiologists the ability to predictive hypotensive events. The HPI derived from intra-arterial catheter monitoring has been shown to predict hypotensive events with sensitivity and specificity >80%3 . However, the utility and accuracy of the HPI when derived from non-invasive monitoring techniques, such the ClearSight finger cuff, have yet to be examined. This study seeks to compare the intraarterial catheter-derived HPI vs the ClearSight finger cuff-derived HPI, to see if it is viable tool for anesthesiologists to use when non-invasive monitoring is not indicated.