Faculty Bibliography

Post-traumatic stress disorder (PTSD) should be one of the most preventable mental disorders, since many people exposed to traumatic experiences (TEs) could be targeted in first response settings in the immediate aftermath of exposure for preventive intervention. However, these interventions are costly and the proportion of TE-exposed people who develop PTSD is small. To be cost-effective, risk prediction rules are needed to target high-risk people in the immediate aftermath of a TE. Although a number of studies have been carried out to examine prospective predictors of PTSD among people recently exposed to TEs, most were either small or focused on a narrow sample, making it unclear how well PTSD can be predicted in the total population of people exposed to TEs. The current report investigates this issue in a large sample based on the World Health Organization (WHO)'s World Mental Health Surveys. Retrospective reports were obtained on the predictors of PTSD associated with 47,466 TE exposures in representative community surveys carried out in 24 countries. Machine learning methods (random forests, penalized regression, super learner) were used to develop a model predicting PTSD from information about TE type, socio-demographics, and prior histories of cumulative TE exposure and DSM-IV disorders. DSM-IV PTSD prevalence was 4.0% across the 47,466 TE exposures. 95.6% of these PTSD cases were associated with the 10.0% of exposures (i.e., 4,747) classified by machine learning algorithm as having highest predicted PTSD risk. The 47,466 exposures were divided into 20 ventiles (20 groups of equal size) ranked by predicted PTSD risk. PTSD occurred after 56.3% of the TEs in the highest-risk ventile, 20.0% of the TEs in the second highest ventile, and 0.0-1.3% of the TEs in the 18 remaining ventiles. These patterns of differential risk were quite stable across demographic-geographic sub-samples. These results demonstrate that a sensitive risk algorithm can be created using data collected in the immediate aftermath of TE exposure to target people at highest risk of PTSD. However, validation of the algorithm is needed in prospective samples, and additional work is warranted to refine the algorithm both in terms of determining a minimum required predictor set and developing a practical administration and scoring protocol that can be used in routine clinical practice.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Many patients with post-traumatic stress disorder (PTSD) achieve but partial remission with current treatments. Patients with unremitted PTSD show high rates of substance abuse. Marijuana is often used as compassion add-on therapy for treatment-resistant PTSD. This open-label study evaluates the tolerance and safety of orally absorbable Δ(9)-tetrahydrocannabinol (THC) for chronic PTSD. METHODS:Ten outpatients with chronic PTSD, on stable medication, received 5 mg of Δ(9)-THC twice a day as add-on treatment. RESULTS:There were mild adverse effects in three patients, none of which led to treatment discontinuation. The intervention caused a statistically significant improvement in global symptom severity, sleep quality, frequency of nightmares, and PTSD hyperarousal symptoms. CONCLUSIONS:Orally absorbable Δ(9)-THC was safe and well tolerated by patients with chronic PTSD.

BACKGROUND: Clinical research suggests that posttraumatic stress disorder (PTSD) patients exposed to multiple traumatic events (TEs) rather than a single TE have increased morbidity and dysfunction. Although epidemiological surveys in the United States and Europe also document high rates of multiple TE exposure, no population-based cross-national data have examined this issue. METHODS: Data were analyzed from 20 population surveys in the World Health Organization World Mental Health Survey Initiative (n = 51,295 aged 18+). The Composite International Diagnostic Interview (3.0) assessed 12-month PTSD and other common DSM-IV disorders. Respondents with 12-month PTSD were assessed for single versus multiple TEs implicated in their symptoms. Associations were examined with age of onset (AOO), functional impairment, comorbidity, and PTSD symptom counts. RESULTS: 19.8% of respondents with 12-month PTSD reported that their symptoms were associated with multiple TEs. Cases who associated their PTSD with four or more TEs had greater functional impairment, an earlier AOO, longer duration, higher comorbidity with mood and anxiety disorders, elevated hyperarousal symptoms, higher proportional exposures to partner physical abuse and other types of physical assault, and lower proportional exposure to unexpected death of a loved one than cases with fewer associated TEs. CONCLUSIONS: A risk threshold was observed in this large-scale cross-national database wherein cases who associated their PTSD with four or more TEs presented a more "complex" clinical picture with substantially greater functional impairment and greater morbidity than other cases of PTSD. PTSD cases associated with four or more TEs may merit specific and targeted intervention strategies.

Mild traumatic brain injury has been associated with higher prevalence of posttraumatic stress disorder (PTSD). The extent to which head injury or loss of consciousness predicts PTSD is unknown. To evaluate the contribution of head injury and loss of consciousness to the occurrence of PTSD, we made a longitudinal evaluation of 1,260 road accident survivors admitted to the emergency department with head injury (n = 287), head injury and loss of consciousness (n = 115), or neither (n = 858). A telephone-administered posttraumatic symptoms scale inferred PTSD and quantified PTSD symptoms at 10 days and 8 months after admission. The study groups had similar heart rate, blood pressure, and pain levels in the emergency department. Survivors with loss of consciousness and head injury had higher prevalence of PTSD and higher levels of PTSD symptoms, suggesting that patients with head injury and loss of consciousness reported in the emergency department are at higher risk for PTSD.

Background: Predicting pathways to chronic PTSD has significant clinical and public health implications but current risk indicators are inconsistent and limited. Previously identified in a large cohort of recent trauma survivors (n=957) using Latent Growth Mixture Modeling, trajectories of PTSD symptoms from one-week to fifteenmonths, include Rapid Remission (56%), Slow Remission (27%), and Non-Remission (17%), the non-remission class comprising the majority PTSD cases at fifteen months, and not responding to cognitive behavioral therapy (CBT). Innovative approaches to forecasting membership in a nonremitting, treatment resistant class may improve our ability to identify, shortly after trauma exposure, survivors at high risk of developing PTSD. We tested the robustness of seven machine learning forecasting methods to predicting the non-remitting class from predictor variables collected during the days that followed trauma exposure. Methods: Consecutive trauma survivors admitted to a general hospital emergency department were screened and followed longitudinally and n=125 with Acute PTSD received efficient cognitive behavioral therapy within a month of the traumatic event. CBT was equally distributed among trajectory classes. Survivors were followed regardless and blindly of their participation in treatment. Markov boundary feature selection was used to identify a parsimonious set of trajectory predictors from 68 candidate variables. That set was than used to compare seven classification algorithms [two variants of linear Support Vector Machines (SVMs), polynomial SVMs, AdaBoost, Random Forests, Bayesian Logistic Regression (BBR) and Kernal Ridge Regression (KRR)] for their ability to build accurate multivariate classification models separating nonremission from other trajectories: Support Vector Machines (SVMs), two Optimized SVMs, AdaBoost, Random Forests, Bayesian Logistic Regression (BBR) and Kernel Ridge Regression (KRR). Results: Variables selected by Markov boundary method robustly predic!

Posttraumatic stress disorder (PTSD) is a prevalent psychiatric disorder, especially in combat veterans. Existing functional neuroimaging studies have provided important insights into the neural mechanisms of PTSD using various experimental paradigms involving trauma recollection or other forms of emotion provocation. However it is not clear whether the abnormal brain activity is specific to the mental processes related to the experimental tasks or reflects general patterns across different brain states. Thus, studying intrinsic spontaneous brain activity without the influence of external tasks may provide valuable alternative perspectives to further understand the neural characteristics of PTSD. The present study evaluated the magnitudes of spontaneous brain activity of male US veterans with or without PTSD, with the two groups matched on age, gender, and ethnicity. Amplitudes of low frequency fluctuation (ALFF), a data driven analysis method, were calculated on each voxel of the resting state fMRI data to measure the magnitudes of spontaneous brain activity. Results revealed that PTSD subjects showed increased spontaneous activity in the amygdala, ventral anterior cingulate cortex, insula, and orbital frontal cortex, as well as decreased spontaneous activity in the precuneus, dorsal lateral prefrontal cortex and thalamus. Within the PTSD group, larger magnitudes of spontaneous activity in the thalamus, precuneus and dorsal lateral prefrontal cortex were associated with lower re-experiencing symptoms. Comparing our results with previous functional neuroimaging findings, increased activity of the amygdala and anterior insula and decreased activity of the thalamus are consistent patterns across emotion provocation states and the resting state.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a debilitating anxiety disorder induced by traumatic experiences. To date, psychotherapy and drug treatment achieve only partial success, indicating need for further development of treatment strategies. Recent research has found that impaired acquired fear extinction capability serves as an important factor at the pathogenesis of the disorder. Medial prefrontal cortex (mPFC) hypo-activity has been implicated in this extinction impairment, providing insight as to why some trauma exposed individuals will develop PTSD. OBJECTIVE: To test whether fear extinction can be facilitated and therapeutic effect achieved by repeated mPFC deep transcranial magnetic stimulation (DTMS) of PTSD patients resistant to standard treatment. METHODS: In a double-blind study, 30 PTSD patients were enrolled and randomly assigned into 3 treatment groups: A) DTMS after brief exposure to the traumatic event with the script-driven imagery procedure; B) DTMS after brief exposure to a non-traumatic event; C) sham stimulation after brief exposure to the traumatic event. RESULTS: Significant improvement was demonstrated in the intrusive component of the CAPS scale in patients administered DTMS after exposure to the traumatic event script, while patients in the control groups showed no significant improvement. Similar trend was demonstrated in the Total-CAPS score as in the other rating scales. A significant reduction in the HR response to the traumatic script was evident in group A, further supporting the above results. CONCLUSIONS: Combining brief script-driven exposure with DTMS can induce therapeutic effects in PTSD patients. A wide multi-center study is suggested to substantiate these findings. Trial registration:ClinicalTrials.gov identifier: NCT00517400.

CONTEXT: Uncovering heterogeneities in the progression of early PTSD symptoms can improve our understanding of the disorder's pathogenesis and prophylaxis. OBJECTIVES: To describe discrete symptom trajectories and examine their relevance for preventive interventions. DESIGN: Latent Growth Mixture Modeling (LGMM) of data from a randomized controlled study of early treatment. LGMM identifies latent longitudinal trajectories by exploring discrete mixture distributions underlying observable data. SETTING: Hadassah Hospital unselectively receives trauma survivors from Jerusalem and vicinity. PARTICIPANTS: Adult survivors of potentially traumatic events consecutively admitted to the hospital's emergency department (ED) were assessed ten days and one-, five-, nine- and fifteen months after ED admission. Participants with data at ten days and at least two additional assessments (n = 957) were included; 125 received cognitive behavioral therapy (CBT) between one and nine months. APPROACH: We used LGMM to identify latent parameters of symptom progression and tested the effect of CBT on these parameters. CBT consisted of 12 weekly sessions of either cognitive therapy (n = 41) or prolonged exposure (PE, n = 49), starting 29.8+/-5.7 days after ED admission, or delayed PE (n = 35) starting at 151.8+/-42.4 days. CBT effectively reduced PTSD symptoms in the entire sample. MAIN OUTCOME MEASURE: Latent trajectories of PTSD symptoms; effects of CBT on these trajectories. RESULTS: THREE TRAJECTORIES WERE IDENTIFIED: Rapid Remitting (rapid decrease in symptoms from 1- to 5-months; 56% of the sample), Slow Remitting (progressive decrease in symptoms over 15 months; 27%) and Non-Remitting (persistently elevated symptoms; 17%). CBT accelerated the recovery of the Slow Remitting class but did not affect the other classes. CONCLUSIONS: The early course of PTSD symptoms is characterized by distinct and diverging response patterns that are centrally relevant to understanding the disorder and preventing its occurrence. Studies of the pathogenesis of PTSD may benefit from using clustered symptom trajectories as their dependent variables.

Patients with posttraumatic stress disorder (PTSD) experience psychological and physiological distress. However, imaging research has mostly focused on the psychological aspects of the disorder. Considered an expression of distress, heart rate (HR) in PTSD is often elevated. In the current study, we sought to identify brain regions associated with increased HR in PTSD. Nine patients with PTSD and six healthy trauma survivors were scanned while resting, clenching teeth, and listening to neutral and traumatic scripts. Brain function was evaluated using H2O15 positron emission tomography (PET). HR was monitored by electrocardiogram. Data were analyzed using statistical parametric mapping (SPM). Subjects with PTSD exhibited a significant increase in HR upon exposure to traumatic scripts, while trauma survivors did not. Correlations between regional cerebral blood flow and HR were found only in patients with PTSD, in orbitofrontal, precentral and occipital regions. Neither group showed correlation between rCBF and HR in the amygdala or hippocampus. These preliminary results indicate that "top down" central nervous system regulation of autonomic stress response in PTSD may involve associative, sensory and motor areas in addition to regions commonly implicated in fear conditioning.