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Can We Identify Futility in Kids? An Evaluation of Admission Parameters Predicting 100% Mortality in 1,292 Severely Injured Children

Journal title
Journal of the American College of Surgeons
Publication year
Kalkwarf, K. J.; Jensen, S. D.; Allukian, M., 3rd; Harting, M. T.; Cox, C. S.; Fox, E. E.; Wade, C. E.; Cotton, B. A.

BACKGROUND: Objective parameters predicting futility of care in severely injured pediatric patients are lacking. Although futility of care has been investigated in a limited number of studies in trauma patients, none of these studies achieves a 100% success rate in a large cohort of pediatric patients. The purpose of the current study was to identify extreme laboratory values that could be used to predict 100% mortality in severely injured children. STUDY DESIGN: We evaluated a registry-based, historical cohort of all severely injured children (Level I trauma, younger than 16 years old) who were not dead on arrival between January 2010 and December 2016 from a single Level I trauma center. Extreme arrival laboratory data were evaluated both alone and in conjunction with traumatic brain injury. RESULTS: There were 1,292 patients who met inclusion criteria, of which 1,169 (90.5%) survived and 123 (9.5%) died. Those who died were significantly younger, with higher head Abbreviated Injury Scale scores and overall Injury Severity Scores. Single extreme laboratory values were identified that predicted mortality perfectly (100% positive predictive value): international normalized ratio >/=3.0, pH /=50%. When 2 laboratory values or the presence of traumatic brain injury were added, lower thresholds for futility were noted. CONCLUSIONS: Extreme admission laboratory values are capable of predicting 100% mortality and futility of additional care in severely injured children with a high level of accuracy. Validation of these single-center findings is warranted and, if supported, should initiate a discussion within the pediatric trauma community about application and cessation of resuscitation efforts to optimize resource use.

Research abstracts