Injuries result in more deaths in children than all other causes combined. Because injured children have better outcomes at centers with specialized trauma care, appropriate transport to these centers may reduce morbidity and mortality. Prehospital information must be used to determine the need for transport to a trauma center and for planning care after arrival. Several triage schemes have been evaluated for stratifying minimally and severely injured children based on prehospital information. These have used a diverse range of inputs, including physiological parameters, anatomic site of injury and mechanism of injury, and have used both linear techniques of analysis and logistic regression. Despite these efforts, no pediatric trauma triage method has yet met the goal of being sufficiently accurate (avoiding under- or over-triage) and reproducible. One potential explanation for the limited success of triage criteria developed using standard regression and classification techniques is the complexity of prehospital data and the uncertain relationship of this data to outcome. Neural networks are a family of models that have an advantage over conventional methods when classification requires using different types of input data or the relationships between these variables and the final classification are vaguely understood. While their use for triage has not been described, neural networks have been better than logistic regression methods in predicting morbidity and mortality in adult trauma patients. Neural networks may be well suited for analysis of pediatric trauma triage because of the diversity and age-specificity of prehospital variables and the uncertain relationship between these variables and the outcome of injured children. These observations have led to the hypothesis that a neural network can more accurately classify pediatric trauma patients by severity of injury and need for hospital resources than current triage methods. Neural networks will be trained to classify injured children based on severity of injury and need for hospital resources using information available to prehospital providers. The classification accuracy of trained networks will be compared with that based on current triage strategies. The long-term goal of this project is to develop and implement a tool for triaging injured children based on neural networks. ? ?
| Burd, Randall S; Jang, Tai S; Nair, Satish S (2007) Evaluation of the relationship between mechanism of injury and outcome in pediatric trauma. J Trauma 62:1004-14 |
| Burd, Randall S; Jang, Tai S; Nair, Satish S (2006) Predicting hospital mortality among injured children using a national trauma database. J Trauma 60:792-801 |
| Heckman, Seth R; Trooskin, Stanley Z; Burd, Randall S (2005) Risk factors for blunt thoracic aortic injury in children. J Pediatr Surg 40:98-102 |
