Professor Demetri Yannopolous, MD, PhD has been awarded an R01 from the NHLBI for his research involving machine learning algorithms incorporated into a mechanical CPR device to predict and optimize hemodynamics during CPR. Current recommendations for CPR follow a “one-size-fits-all” paradigm that isn’t always adequate for every individual suffering out-of-hospital cardiac arrest (OHCA). The goal of this project is to improve vital organ perfusion during prolonged CPR by “personalizing” compression/decompression therapy. A dynamic CPR method that changes compression characteristics over the course of CPR after taking into account the temporal changes of chest wall compliance and hemodynamics is predicted to increase the rate of neurologically intact survival after OHCA. Grant details>