A newly developed analytic model can predict with significant accuracy which trauma victims are most likely to develop chronic post-traumatic stress disorder (PTSD).
The findings are published in the journal World Psychiatry.
Since chronic PTSD is so difficult to treat, knowing soon after trauma exposure how likely a survivor is to develop the disorder can help clinicians know whether to initiate early therapies — even as early as the emergency room, where most trauma victims are first seen.
An international research team led by psychiatrists at New York University’s (NYU) School of Medicine analyzed the medical records of nearly 2,500 patients in 10 longitudinal studies of civilian trauma survivors treated in emergency departments in the United States, Australia, Japan, the Netherlands, Switzerland and Israel.
The study participants, all of whom had experienced trauma ranging from traffic and workplace accidents to assaults and terrorist attacks, were initially evaluated using the Clinician-Administered PTSD Scale for DSM-IV (CAPS), considered the “gold standard” for assessing PTSD.
All subjects had a CAPS interview within 60 days of their traumatic event and a follow-up interview four to 15 months later.
The researchers took these CAPS scores and further analyzed them using the Brier Score, a measurement developed in the 1950s, as well as other validation methods to estimate of each individual’s risk of developing PTSD nine to 15 months later.
The researchers discovered that this approach could, indeed, predict chronic PTSD with high confidence and calculate, with similar accuracy, additional risk tied to other factors such as sex, lower education or a lifetime experience of interpersonal trauma.
In particular, the research team found that PTSD prevalence after follow-up was on average 11.8 percent in those exposed to a traumatic event: 9.2 percent in men and 16.4 percent in women.
They also found that women with less than a secondary education and previous exposure to interpersonal trauma, such as child abuse or sexual assault, had a much higher risk of chronic PTSD.
Other previously known risk factors such as age, marital status and type of trauma did not increase a person’s risk of developing PTSD.
The researchers say that patients with higher initial CAPS scores could require earlier intervention, while lower scores might justify a “watchful waiting” approach with additional follow-up assessments.
“We are moving from the near impossible task of trying to predict who will develop PTSD to more accurately identifying a risk score for each individual who was exposed to a traumatic event,” said Arieh Y. Shalev, M.D., the Barbara Wilson Professor of Psychiatry at NYU School of Medicine and lead author of the report. ”
Knowing that a person has an increased risk for PTSD will help mitigate it more rapidly, and with fewer residual consequences.”
“Early symptoms, previously known to globally predict the risk of PTSD among trauma survivors (e.g., 11 percent in road traffic accidents or 38 percent following terror in our previous work) were unable to tell us who, within a group, was at particularly high risk. We now can precisely predict each individual’s risk, thus moving PTSD evaluation to a more personalized and individualized risk estimate.”
For example, the new analysis model can help determine that a specific patient will likely remain with chronic PTSD unless treated, whereas another from the same study group may only have 2 percent risk. “It is a more immediate call for action that the previous group estimates could not provide,” Shalev says.
The researchers say that the new PTSD evaluation model joins a large family of online tools used in other clinical areas, such as heart disease and cancer, to assign a likelihood of developing a disease or a recurrence based on current information (e.g., cholesterol, weight and smoking history in heart attacks).
In the United States, 70 percent of adults have experienced some type of trauma, and over 10 percent will go on to develop PTSD.
The published study includes an online tool allowing clinicians immediate access to the risk estimate model.