Augmented Reality Forward Damage Control Procedures for Nonsurgeons: A Feasibility Demonstration.

INTRODUCTION: This article presents an emerging capability to project damage control procedures far forward for situations where evacuation to a formal surgical team is delayed. Specifically, we demonstrate the plausibility of using a wearable augmented reality (AR) telestration device to guide a nonsurgeon through a damage control procedure. METHODS: A stand-alone, low-profile, commercial-off-the-shelf wearable AR display was utilized by a remotely located surgeon to synchronously guide a nonsurgeon through proximal control of the distal external iliac artery on a surgical manikin. The manikin wound pattern was selected to simulate a rapidly exsanguinating junctional hemorrhage not controllable by nonsurgical means. RESULTS: This capability demonstration displayed successful use of AR technology, telecommunication, and procedural training and guidance in a single test pilot. The assisted physician assistant was able to rapidly control the simulated external iliac artery injury on this model. The telestration system used was commercially available for use with available civilian cell phone, wireless and satellite networks, without the need for dedicated high-speed networks. CONCLUSIONS: A nonsurgeon, using a wearable commercial on-visual-axis telestration system, successfully performed a damage control procedure, demonstrating the plausibility of this approach.

A new resource-constrained triage method applied to victims of penetrating injury.

BACKGROUND: Resource-constrained triage occurs when the number of trauma patients exceeds the capacity for simultaneous transport and treatment. The objective of this article is to apply a new resource-constrained triage method (denoted Sacco triage method [STM]) to victims of penetrating trauma and compare it with existing methods. METHODS: STM is a mathematical model of resource-constrained triage. Its objective is to maximize expected survivors given constraints on the timing and availability of resources. The model incorporates estimates of time-dependent victim survival probabilities based on initial assessments and expected deteriorations. For application to penetrating trauma, an "RPM" score based on respiratory rate, pulse rate, and best motor response was used to predict survivability. Logistic function-generated survival probability estimates for scene values of RPM were determined from 7,274 penetrating injury patients from the Pennsylvania Trauma Outcome Study. The Delphi Method provided expert consensus on victim deterioration rates, and the model was solved using linear programming. The accuracy of predicting survivability was assessed using calibration and discrimination statistics. STM was compared with START (Simple Triage and Rapid Treatment)-like triage methods with respect to process and outcomes (assessed by expected number of survivors in simulated resource-constrained casualty incidents). RESULTS: RPM was shown to be an accurate predictor of survival probability for penetrating trauma, equivalent to the Revised Trauma Score and exceeding that of the Injury Severity Score, as measured by calibration and discrimination statistics. In the simulations, STM had substantially more expected survivors than did current triage methods. CONCLUSIONS: Resource-constrained triage is modeled as an evidence-based, outcome-driven method (STM) that maximizes expected survivors in consideration of resources. STM offers lifesaving and operational advantages over current methods.

Precise formulation and evidence-based application of resource-constrained triage.

OBJECTIVES: To develop a precise mathematical formulation of resource-constrained triage, denoted the Sacco triage method (STM), to develop an evidence-based application to blunt trauma, and to compare the STM with the simple triage and rapid treatment (START) method. METHODS: Resource-constrained triage is modeled mathematically as a classic resource allocation problem. The objective is to maximize expected survivors given constraints on the timing and availability of resources. The model incorporates estimates of time-dependent victim survival probabilities based on an initial assessment and expected deterioration. For application to blunt trauma, an "RPM" score, based on respiratory rate, pulse rate, and motor response, was used to predict survivability. Logistic function-generated survival probability estimates for scene values of RPM were determined from 76,459 blunt-injured patients from the Pennsylvania Trauma Outcome Study (PTOS). The Delphi method provided expert consensus on victim deterioration rates, and the model was solved using linear programming. STM was compared with START across various criteria of process and outcome. Outcome was measured by expected number of survivors in simulated resource-constrained casualty incidents. RESULTS: In this mathematical simulation, RPM was a more accurate predictor of survivability from blunt trauma than the Injury Severity Score and the Revised Trauma Score, as measured by calibration and discrimination statistics. STM resulted in greater expected survivorship than START in all simulations. CONCLUSIONS: Resource-constrained triage is modeled precisely as an evidence-based, outcome-driven method that maximizes expected survivors in consideration of resources. The lifesaving potential and operational advantages over current methods warrant scrutiny and further research.

A new "TRISS-like" probability of survival model for intubated trauma patients.

BACKGROUND: Prehospital trauma patient field intubations and paralyzations, using neuromuscular blocking agents before emergency department respiratory and neurologic assessments are made, bias assessments and outcome evaluations using probability-of-survival models, such as TRISS and A Severity Characterization of Trauma (ASCOT). We present a newly developed "TRISS-like" probability-of-survival model for intubated blunt- and penetrating-injured patient assessment. METHODS: From a population of 51397 consecutively admitted trauma patients, this study used all 5740 (11.2% of the total injured population) intubated patients with complete data from a statewide trauma registry from October 1, 1993, to September 30, 1996. Model performance was evaluated using standard calibration and discrimination measures and z and W statistics of significance. RESULTS: The new model accurately predicted survival for blunt- and penetrating-injured intubated patients and is applicable to 11 etiologic patient populations. CONCLUSION: Study findings suggest that the new TRISS-like model should be used to assess both blunt- and penetrating-injured intubated patients. Use of this new model provides an analytical method for addressing a significant limitation of both the standard TRISS and ASCOT models, which are not applicable to intubated injured patient assessment. In addition, use of this model will complement TRISS/ASCOT assessments of nonintubated trauma patients and thus permit appropriate assessments for both intubated and nonintubated injured patient study populations.