New Tool Can Predict Who is at High Risk for PTSD Following a Traumatic Event
Researchers have steadily been identifying individual risk factors for post-traumatic stress disorder (PTSD) and now a team has brought them all together into a new computational tool capable of identifying up to 800 different factors for PTSD in individuals.
The tool could be very helpful in creating a personalized PTSD prediction guide which would make identifying high-risk individuals following traumatic events for early intervention much easier.
“Our study shows that high-risk individuals who have experienced a traumatic event can be identified less than two weeks after they are first seen in the emergency department,” says Dr. Arieh Y. Shalev in BMC Psychiatry.
“Until now, we have not had a tool – in this case, a computational algorithm – that can weigh the many different ways in which trauma occurs to individuals and provide a personalized risk estimate.”
Until now, clinicians have been limited in their ability to predict risk for PTSD. Clinicians had the means to calculate the average risk of PTSD for large groups, but the computational methods for doing so are considered insufficient and inaccurate for predicting individual risk.
“Together, current findings suggest that PTSD is associated with an array of multimodal risk indicators, many of which are observable shortly after trauma exposure. Despite these findings, research to date has failed to reveal clinically useful, personalized predictors,” explained the authors.
Previous research conducted by the World Health Organization and the US indicates the majority of living adults will experience a traumatic event in their lifetime. Approximately 5-10% of those individuals will go on to develop PTSD related to the event.
For the study, the researchers relied on data from the Jerusalem Trauma Outreach and Prevention Study which included data from 4,743 individuals admitted to emergency rooms for traumatic events. When the team applied their computational tool to data collected from these individuals within 10 days of a traumatic event, the algorithm accurately predicted which individuals were most likely to develop PTSD. The test even accounts for the wide range of ways traumatic events can occur.
“This study extends our ability to predict effectively,” states Dr. Shalev. “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 says the tool is still in early stages and this study is simply a proof of concept and he believes it will be even more effective with more data collected from other patient populations.
“In the future, we hope that we will be better able to tailor treatment approaches based on more personalized risk assessment,” states Dr. Shalev. “PTSD exacts a heavy toll on affected individuals and society.”