Post Traumatic Stress Disorder (PTSD) is a mental condition triggered by a traumatic event that causes victims to experience recurrent flashbacks of the event followed by acute stress, anxiety, fear and panic. Latest research from NYU Langone Medical Center establishes an algorithm that permits early risk identification of PTSD within 10 days of traumatic event.
Currently, clinicians have had to work with are computation methods capable of calculating the average risk for entire groups of survivors, and those have proven to be insufficient as an individual risk prediction tool. However, this new computational tool identifies 800 different ways people are at increased risk for PTSD, permitting for the first time a personalized prediction guide.
Dr. Arieh Y. Shalev, the Barbara Wilson Professor in the Department of Psychiatry at NYU Langone and a co-director of NYU's Steven and Alexandra Cohen Veterans Center, said, "Until recently, we mainly used early symptoms to predict PTSD, and it had its drawbacks. This study extends our ability to predict effectively. For example, it shows that features like the occurrence of head trauma, duration of stay in the emergency department, or survivors' expressing a need for help, can be integrated into a predictive tool and improve the prediction."
Dr. Shalev added, "This latest publication is a 'proof of concept' paper. For robust prediction across conditions, the identified algorithm needs to be used to gather knowledge gained in traumatic events experienced by other patient populations and traumatic events - beyond those analyzed from the earlier study."
The study appears online in the journal 'BMC Psychiatry'.