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Trauma center resource management could be facilitated by a readily available indicator of resource consumption. This marker should identify patients more likely to require transfusion and intensive care services and to develop complications. Base deficit (BD) has been shown to be a valuable indicator of shock, abdominal injury, fluid requirements, efficacy of resuscitation, and to be predictive of mortality after trauma. This study was performed to determine whether BD could be used to identify which patients were likely to require blood transfusion in the first 24 hours of hospitalization, and to develop shock-related complications and increased intensive care unit (ICU) and hospital stays. A retrospective review of 2,954 patients admitted to the Valley Medical Center Level I trauma service from July 1990 through August 1995 was done using the trauma registry and blood bank data bases. Medical record review was done to supplement missing data. Transfusion requirements increased as the BD category became more severe (p < 0.001). Transfusions were required within 24 hours of admission in 72% of patients with a BD < or = -6 versus 18% of patients with a BD > -6 (p < 0.001, chi2). Both ICU and hospital length of stay increased with worsening BD (p < 0.015 and p < 0.05, respectively). The frequency of adult respiratory distress syndrome (ARDS) (p < 0.01), renal failure (p = 0.015), coagulopathy (p < 0.001), and multiorgan system failure (MOF) (p < 0.002) all increased with increasingly severe BD. Discriminate analysis using Injury Severity Score (ISS) and BD category demonstrated predictive accuracy of 81%, 77%, and 77% for coagulopathy, ARDS, and MOF, respectively. Mortality also increased with worsening BD. When stratified by BD category, there was no difference between observed and predicted survival. Admission BD identifies patients likely to require early transfusion and increased ICU and hospital stays, and be at increased risk for shock-related complications. Patients with BD < or = -6 should undergo type and cross-match rather than type and screen. The use of ISS and BD category probability curves may identify candidates for early invasive monitoring.