A 48 Subject Study Using Non-invasive Multi-Technology Measurements for Early Detection of Ongoing Hemorrhage

Early detection of ongoing hemorrhage (OH) before onset of hemorrhagic shock is a universally acknowledged great unmet need, and particularly important after traumatic injury. Delays in the detection of OH are associated with a "failure to rescue" and a dramatic deterioration in prognosis once the onset of clinically frank shock has occurred. An early alert to the presence of OH would save countless lives. This is a single site study, enrolling 48 patients undergoing liver resection in a "no significant risk" prospective clinical trial to: 1) further identify a minimal subset of noninvasive measurement technologies necessary for the desired diagnostic performance, 2) validate the performance of our Phase I algorithm, and 3) re-train the algorithm to a Phase II human iteration. The main outcome variables are non-invasive measurements that will be used for machine learning, not real-time patient management. The data generated will be used later for discovery and validation in traditional and innovative machine learning.