Deployed Tools


Invasive fungal infections are devastating and threaten both life and limb. Typically, rare in immunocompetent individuals, IFI have developed with remarkable frequency in severely combat-injured patients, particularly those sustaining multi-system blast trauma with associated abdomino-pelvic injuries, multiple amputations, and/or requiring massive early life saving transfusions.  Despite the high survival rate of our wounded warriors from the current conflicts, some such patients have succumbed to these aggressive infections after reaching military medical centers. Surviving patients have complex, morbid clinical courses frequently requiring multiple additional procedures and proximal migration of amputations, with high associated complication rates. Using a large database of combat-injured personnel, we have developed Clinical Decision Support Tools to allow early IFI risk stratification at either the in-theater or medical center echelons of care; these tools were subsequently externally validated utilizing a separate, similar database. These tools can facilitate the early diagnosis and aggressive prophylactic local and systemic treatment of patients at high risk for IFI, which we believe is critical to mitigate IFI-associated morbidity and mortality.


The decision to activate a massive transfusion protocol is both complex and time sensitive. It requires not only an urgent assessment of a critically injured patient's physiology but also must take into account issues of resource availability and utilization. Oftentimes, little empiric data is available rapidly enough to assist the bedside clinician and therefore this key decision is often left to the instincts of the treating team. Several published tools use manual calculations that are either too complex, making them of little use in real-time, or too simple, making them not accurate enough to be truly useful. Fortunately, technology allows us to bring sophisticated computers in the form of smart phones to the bedside to assist in these complex decisions. A mobile application designed to take simple physiologic data available to the clinician within minutes of patient arrival and create an extremely accurate prediction of the need for urgent massive transfusion has been designed using data from over 10 years of patient care in a busy urban trauma center. This application is currently being studied prospectively to understand if it will be a useful Clinical Decision Support tool.


*Live in civilian sector and in process for the military health system