BACKGROUNDVolume expansion and vasopressors for the treatment of shock is an intensive process that requires frequent assessments and adjustments. Strict blood pressure goals in multiple physiologic states of shock (TBI, sepsis, and hemorrhagic) have been associated with improved outcomes. The availability of continuous physiologic data is amenable to closed loop automated critical care to improve goal directed resuscitation.METHODS5 adult swine were anesthetized and subjected to a controlled 30% estimated total blood volume hemorrhage followed by 30 minutes of complete supra-celiac aortic occlusion and then auto-transfusion back to euvolemia with removal of aortic balloon. The animals underwent closed loop critical care for 255 minutes after removal of the endovascular aortic balloon. The closed-loop critical care algorithm using proximal aortic pressure and central venous pressure combined with a fully autonomous algorithm providing programmatically control of pumps for titration of vasopressors and weight-based crystalloid boluses (5ml/kg) to maintain a mean arterial pressure between 60 - 70 mmHg.RESULTSDuring the 255 minutes of critical care the animals experienced hypotension (<60 mmHg) 15.29% (8.63% - 16.47% interquartile range), hypertension (>70 mmHg) 7.84% (6.67% - 9.02% interquartile range), and normotension (60 - 70 mmHg) 76.86% (76.86% - 81.18% interquartile range) of the time. Excluding the first 60 minutes of the critical care phase the animals experienced hypotension 1.03% (0.51% - 7.69% interquartile range) of the time. Median intervention rate was 8.47 interventions per hour (interquartile range: 7.76 - 9.18). The proportion of interventions was 61.54% (interquartile range: 61.11%-66.667%) weight-based crystalloid boluses and 38.46% (interquartile range: 33.33%-38.89%) titration of vasopressors.CONCLUSIONThis autonomous critical care platform, utilizing volume expansion and vasopressor titration in a model of ischemia-reperfusion injury, is effective at minimizing hypotension using goal-directed closed loop algorithms and device actuation. This descriptive study highlights the potential for this approach to deliver nuanced critical care in the ICU environment, thereby optimizing resuscitative efforts and expanding capabilities through cognitive offloading. Future efforts will focus on optimizing this platform through comparative studies, specifically evaluating the performance compared to manual critical care.