We sought to evaluate the efficacy, efficiency, and physiologic consequences of automated, endpoint-directed resuscitation systems and compare them to formula-based bolus resuscitation.Design:
Experimental human hemorrhage and resuscitation.Setting:
Clinical research laboratory.Subjects:
Subjects (n = 7) were subjected to hemorrhage and underwent a randomized fluid resuscitation scheme on separate visits 1) formula-based bolus resuscitation; 2) semiautonomous (decision assist) fluid administration; and 3) fully autonomous (closed loop) resuscitation. Hemodynamic variables, volume shifts, fluid balance, and cardiac function were monitored during hemorrhage and resuscitation. Treatment modalities were compared based on resuscitation efficacy and efficiency.Measurements and Main Results:
All approaches achieved target blood pressure by 60 minutes. Following hemorrhage, the total amount of infused fluid (bolus resuscitation: 30 mL/kg, decision assist: 5.6 ± 3 mL/kg, closed loop: 4.2 ± 2 mL/kg; p < 0.001), plasma volume, extravascular volume (bolus resuscitation: 17 ± 4 mL/kg, decision assist: 3 ± 1 mL/kg, closed loop: –0.3 ± 0.3 mL/kg; p < 0.001), body weight, and urinary output remained stable under decision assist and closed loop and were significantly increased under bolus resuscitation. Mean arterial pressure initially decreased further under bolus resuscitation (–10 mm Hg; p < 0.001) and was lower under bolus resuscitation than closed loop at 20 minutes (bolus resuscitation: 57 ± 2 mm Hg, closed loop: 69 ± 4 mm Hg; p = 0.036). Colloid osmotic pressure (bolus resuscitation: 19.3 ± 2 mm Hg, decision assist, closed loop: 24 ± 0.4 mm Hg; p < 0.05) and hemoglobin concentration were significantly decreased after bolus fluid administration.Conclusions:
We define efficacy of decision-assist and closed-loop resuscitation in human hemorrhage. In comparison with formula-based bolus resuscitation, both semiautonomous and autonomous approaches were more efficient in goal-directed resuscitation of hemorrhage. They provide favorable conditions for the avoidance of over-resuscitation and its adverse clinical sequelae. Decision-assist and closed-loop resuscitation algorithms are promising technological solutions for constrained environments and areas of limited resources.