Mild to Moderate to Severe: What Drives the Severity of ARDS in Trauma Patients?

Acute respiratory distress syndrome (ARDS) is a complex inflammatory process with multifactorial etiologies. Risk factors for its development have been extensively studied, but factors associated with worsening severity of disease, as defined by the Berlin criteria, are poorly understood. A retrospective chart and trauma registry review identified trauma patients in our surgical intensive care unit who developed ARDS, defined according to the Berlin definition, between 2010 and 2015. The primary outcome was development of mild, moderate, or severe ARDS. A logistic regression model identified risk factors associated with developing ARDS and with worsening severity of disease. Of 2704 total patients, 432 (16%) developed ARDS. Of those, 100 (23%) were categorized as mild, 176 (41%) as moderate, and 156 (36%) as severe. Two thousand two hundred and seventy-two patients who did not develop ARDS served as controls. Male gender, blunt trauma, severe head and chest injuries, and red blood cell as well as total blood product transfusions are independent risk factors associated with ARDS. Worsening severity of disease is associated with severe chest trauma and volume of plasma transfusion. Novel findings in our study include the association between plasma transfusions and specifically severe chest trauma with worsening severity of ARDS in trauma patients.

Automated closed-loop resuscitation of multiple hemorrhages: a comparison between fuzzy logic and decision table controllers in a sheep model.

BACKGROUND: Hemorrhagic shock is the leading cause of trauma-related death in the military setting. Definitive surgical treatment of a combat casualty can be delayed and life-saving fluid resuscitation might be necessary in the field. Therefore, improved resuscitation strategies are critically needed for prolonged field and en route care. We developed an automated closed-loop control system capable of titrating fluid infusion to a target endpoint. We used the system to compare the performance of a decision table algorithm (DT) and a fuzzy logic controller (FL) to rescue and maintain the mean arterial pressure (MAP) at a target level during hemorrhages. Fuzzy logic empowered the control algorithm to emulate human expertise. We hypothesized that the FL controller would be more effective and more efficient than the DT algorithm by responding in a more rigid, structured way. METHODS: Ten conscious sheep were submitted to a hemorrhagic protocol of 25 ml/kg over three separate bleeds. Automated resuscitation with lactated Ringer's was initiated 30 min after the first hemorrhage started. The endpoint target was MAP. Group differences were assessed by two-tailed t test and alpha of 0.05. RESULTS: Both groups maintained MAP at similar levels throughout the study. However, the DT group required significantly more fluid than the FL group, 1745 ± 552 ml (42 ± 11 ml/kg) versus 978 ± 397 ml (26 ± 11 ml/kg), respectively (p = 0.03). CONCLUSION: The FL controller was more efficient than the DT algorithm and may provide a means to reduce fluid loading. Effectiveness was not different between the two strategies. Automated closed-loop resuscitation can restore and maintain blood pressure in a multi-hemorrhage model of shock.