Suchergebnisse

OBJECTIVE: Cognitive Processing Therapy (CPT) and Prolonged Exposure Therapy (PE) were widely disseminated to treat posttraumatic stress disorder (PTSD) in the Veterans Health Administration (VHA). However, few Iraq and Afghanistan war veterans (OEF/OIF/OND) diagnosed with PTSD have received CPT/PE and many initiate CPT/PE after substantial delay. Veterans who do not initiate CPT/PE or initiate CPT/PE after delay may have poorer treatment outcomes. This study aimed to identify predictors of CPT/PE initiation and timing. METHODS: Participants included OEF/OIF/OND veterans diagnosed with PTSD who received psychotherapy between 2001–2017 in the VHA (n=265,566). Logistic regression analysis was utilized to predict initiating CPT/PE (vs. no CPT/PE). Multinomial logistic regression analysis was utilized to predict initiating "early CPT/PE" (<1 year after first mental health visit) vs. delayed or not initiating. Analyzed predictors included demographic, military, and clinical complexity variables (e.g., comorbidities, reported military sexual trauma [MST] history). RESULTS: 78% of veterans did not initiate CPT/PE, with 7% initiating early and 15% initiating delayed CPT/PE. Reported MST history (OR=1.45, CI(95):1.39–1.51) and history of suicidal ideation/attempt (OR=1.42, CI(95):1.38–1.46) were strong predictors of CPT/PE initiation vs. no CPT/PE. Comorbid pain (RRR=1.35, CI(95):1.30–1.42) and depressive disorders (RRR=1.37, CI(95):1.32–1.43) were associated with increased likelihood of delayed vs. early CPT/PE. CONCLUSIONS: Most veterans in our study did not initiate CPT/PE. Generally, clinical complexity variables increased likelihood of initiating CPT/PE and initiating CPT/PE more than one year after first mental health visit. Additional research is needed to understand whether CPT/PE delay results from receipt of alternative intervention due to clinical complexity variables.

AIM: Million Veteran Program (MVP) is the largest ongoing mega-cohort biobank program in the US with 570,131 enrollees as of May 2017. The primary aim is to describe demographics, military service, and major diseases and comorbidities of the MVP cohort. Our secondary aim is to examine body mass index (BMI), a proxy for general health, among enrollees. MATERIALS AND METHOD: The study population consists of Veterans who actively use the Veterans Health Administration in the US. Data evaluated in this paper combine health information from multiple sources to provide the most comprehensive demographic profile and information on height and weight of MVP enrollees. A standardized cleaning algorithm was used to curate the demographic variables for each participant in MVP. For height and weight, we derived a final data point for each participant to evaluate BMI. STATISTICAL ANALYSIS USED: Multivariable logistic regression was used to compare the differences in BMI categories across enrollment years adjusting for gender, race, and age. P < 0.05 was considered statistically significant. All analyses were conducted using Statistical Analysis System 9.2. RESULTS: The MVP cohort consists of 90.4% of males with an average age of 61.9 years (standard deviation [SD] = 13.9). MVP is the largest multiethnic biobank cohort within the Veteran population with 73.9% White, 19.0% Black, and 6.5% Hispanic. The most common self-reported disease was hypertension (62.6%) for males and depression (47.5%) for females. Mean BMI was 29.7 kg/m(2) (SD = 5.8) with 38.2% obese and 42.3% overweight. CONCLUSIONS: Our findings suggest that demographic representation in MVP is similar to the Veterans Health Administration population and contrasts with the overall National Health and Nutrition Examination Survey US population. The prevalence of overweight and obese is high among US Veterans, and future studies will examine the role of BMI and disease risk in the Veteran population.

The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of U.S. military veterans. We genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least 1 blood lipid measurement including 57,332 blacks and 24,743 Hispanics, we tested up to ~32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total N > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes), and PDE3B (triglycerides and coronary disease).