A major obstacle in understanding and treating posttraumatic stress disorder (PTSD) is its clinical and neurobiological heterogeneity. To address this barrier, the field has become increasingly interested in identifying subtypes of PTSD based on dysfunction in neural networks alongside cognitive impairments that may underlie the development and maintenance of symptoms. The current study aimed to determine if subtypes of PTSD, based on normative-based cognitive dysfunction across multiple domains, have unique neural network signatures.

In a sample of 271 veterans (90% male) that completed both neuropsychological testing and resting-state fMRI, two complementary, whole-brain functional connectivity analyses explored the link between brain functioning, PTSD symptoms, and cognition.

At the network level, PTSD symptom severity was associated with reduced negative coupling between the limbic network (LN) and frontal-parietal control network (FPCN), driven specifically by the dorsolateral prefrontal cortex and amygdala Hubs of Dysfunction. Further, this relationship was uniquely moderated by executive function (EF). Specifically, those with PTSD and impaired EF had the strongest marker of LN-FPCN dysregulation, while those with above-average EF did not exhibit PTSD-related dysregulation of these networks.

These results suggest that poor executive functioning, alongside LN-FPCN dysregulation, may represent a neurocognitive subtype of PTSD.

Although mania is the hallmark symptom of bipolar I disorder (BD-I), most patients initially present for treatment with depressive symptoms. Misdiagnosis of BD-I as major depressive disorder (MDD) is common, potentially resulting in poor outcomes and inappropriate antidepressant monotherapy treatment. Screening patients with depressive symptoms is a practical strategy to help healthcare providers (HCPs) identify when additional assessment for BD-I is warranted. The new 6-item Rapid Mood Screener (RMS) is a pragmatic patient-reported BD-I screening tool that relies on easily understood terminology to screen for manic symptoms and other BD-I features in <2 minutes. The RMS was validated in an observational study in patients with clinically confirmed BD-I (n=67) or MDD (n=72). When 4 or more items were endorsed (“yes”), the sensitivity of the RMS for identifying patients with BP-I was 0.88 and specificity was 0.80; positive and negative predictive values were 0.80 and 0.88, respectively. To more thoroughly understand screening tool use among HCPs, a 10-minute survey was conducted.

A nationwide sample of HCPs (N=200) was selected using multiple HCP panels; HCPs were asked to describe their opinions/current use of screening tools, assess the RMS, and evaluate the RMS versus the widely recognized Mood Disorder Questionnaire (MDQ). Results were reported by grouped specialties (primary care physicians, general nurse practitioners [NPs]/physician assistants [PAs], psychiatrists, and psychiatric NPs/PAs). Included HCPs were in practice <30 years, spent at least 75% of their time in clinical practice, saw at least 10 patients with depression per month, and diagnosed MDD or BD in at least 1 patient per month. Findings were reported using descriptive statistics; statistical significance was reported at the 95% confidence interval.

Among HCPs, 82% used a tool to screen for MDD, while 32% used a tool for BD. Screening tool attributes considered to be of the greatest value included sensitivity (68%), easy to answer questions (66%), specificity (65%), confidence in results (64%), and practicality (62%). Of HCPs familiar with screening tools, 70% thought the RMS was at least somewhat better than other screening tools. Most HCPs were aware of the MDQ (85%), but only 29% reported current use. Most HCPs (81%) preferred the RMS to the MDQ, and the RMS significantly outperformed the MDQ across valued attributes; 76% reported that they were likely to use the RMS to screen new patients with depressive symptoms. A total of 84% said the RMS would have a positive impact on their practice, with 46% saying they would screen more patients for bipolar disorder.

The RMS was viewed positively by HCPs who participated in a brief survey. A large percentage of respondents preferred the RMS over the MDQ and indicated that they would use it in their practice. Collectively, responses indicated that the RMS is likely to have a positive impact on screening behavior.

AbbVie Inc.

Social cognition has not previously been assessed in treatment-naive patients with chronic schizophrenia, in patients over 60 years of age, or in patients with less than 5 years of schooling.

We revised a commonly used measure of social cognition, the Reading the Mind in the Eyes Test (RMET), by expanding the instructions, using both self-completion and interviewer-completion versions (for illiterate respondents), and classifying each test administration as ‘successfully completed’ or ‘incomplete’. The revised instrument (RMET-CV-R) was administered to 233 treatment-naive patients with chronic schizophrenia (UT), 154 treated controls with chronic schizophrenia (TC), and 259 healthy controls (HC) from rural communities in China.

In bivariate and multivariate analyses, successful completion rates and RMET-CV-R scores (percent correct judgments about emotion exhibited in 70 presented slides) were highest in HC, intermediate in TC, and lowest in UT (adjusted completion rates, 97.0, 72.4, and 49.9%, respectively; adjusted RMET-CV-R scores, 45.4, 38.5, and 34.6%, respectively; all p < 0.02). Stratified analyses by the method of administration (self-completed v. interviewer-completed) and by education and age (‘educated-younger’ v. ‘undereducated-older’) show the same relationship between groups (i.e. NC>TC>UT), though not all differences remain statistically significant.

We find poorer social cognition in treatment-naive than in treated patients with chronic schizophrenia. The discriminant validity of RMET-CV-R in undereducated, older patients demonstrates the feasibility of administering revised versions of RMET to patients who may otherwise be considered ineligible due to education or age by changing the method of test administration and carefully assessing respondents' ability to complete the task successfully.

During the Randomized Assessment of Rapid Endovascular Treatment (EVT) of Ischemic Stroke (ESCAPE) trial, patient-level micro-costing data were collected. We report a cost-effectiveness analysis of EVT, using ESCAPE trial data and Markov simulation, from a universal, single-payer system using a societal perspective over a patient’s lifetime.

Primary data collection alongside the ESCAPE trial provided a 3-month trial-specific, non-model, based cost per quality-adjusted life year (QALY). A Markov model utilizing ongoing lifetime costs and life expectancy from the literature was built to simulate the cost per QALY adopting a lifetime horizon. Health states were defined using the modified Rankin Scale (mRS) scores. Uncertainty was explored using scenario analysis and probabilistic sensitivity analysis.

The 3-month trial-based analysis resulted in a cost per QALY of $201,243 of EVT compared to the best standard of care. In the model-based analysis, using a societal perspective and a lifetime horizon, EVT dominated the standard of care; EVT was both more effective and less costly than the standard of care (−$91). When the time horizon was shortened to 1 year, EVT remains cost savings compared to standard of care (∼$15,376 per QALY gained with EVT). However, if the estimate of clinical effectiveness is 4% less than that demonstrated in ESCAPE, EVT is no longer cost savings compared to standard of care.

Results support the adoption of EVT as a treatment option for acute ischemic stroke, as the increase in costs associated with caring for EVT patients was recouped within the first year of stroke, and continued to provide cost savings over a patient’s lifetime.

Clinical Trial Registration: NCT01778335

Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.

The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].

Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).

A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.

Recent studies suggest that close-range blast exposure (CBE), regardless of acute concussive symptoms, may have negative long-term effects on brain health and cognition; however, these effects are highly variable across individuals. One potential genetic risk factor that may impact recovery and explain the heterogeneity of blast injury’s long-term cognitive outcomes is the inheritance of an apolipoprotein (APOE) ε4 allele, a well-known genetic risk factor for Alzheimer’s disease. We hypothesized that APOE ε4 carrier status would moderate the impact of CBE on long-term cognitive outcomes.

To test this hypothesis, we examined 488 post-9/11 veterans who completed assessments of neuropsychological functioning, psychiatric diagnoses, history of blast exposure, military and non-military mild traumatic brain injuries (mTBIs), and available APOE genotypes. We separately examined the effects of CBE on attention, memory, and executive functioning in individuals with and without the APOE ε4 allele.

As predicted, we observed a differential impact of CBE status on cognition as a function of APOE ε4 status, in which CBE ε4 carriers displayed significantly worse neuropsychological performance, specifically in the domain of memory. These results persisted after adjusting for clinical, demographic, and genetic factors and were not observed when examining other neurotrauma variables (i.e., lifetime or military mTBI, distant blast exposure), though these variables displayed similar trends.

These results suggest APOE ε4 carriers are more vulnerable to the impact of CBE on cognition and highlight the importance of considering genetic risk when studying cognitive effects of neurotrauma.

Prehospital use of lung ultrasound (LUS) by paramedics to guide the diagnoses and treatment of patients has expanded over the past several years. However, almost all of this education has occurred in a classroom or hospital setting. No published prehospital use of LUS simulation software within an ambulance currently exists.

The objective of this study was to determine if various ambulance driving conditions (stationary, constant acceleration, serpentine, and start-stop) would impact paramedics’ abilities to perform LUS on a standardized patient (SP) using breath-holding to simulate lung pathology, or to perform LUS using ultrasound (US) simulation software. Primary endpoints included the participating paramedics’: (1) time to acquiring a satisfactory simulated LUS image; and (2) accuracy of image recognition and interpretation. Secondary endpoints for the breath-holding portion included: (1) the agreement between image interpretation by paramedic versus blinded expert reviewers; and (2) the quality of captured LUS image as determined by two blinded expert reviewers. Finally, a paramedic LUS training session was evaluated by comparing pre-test to post-test scores on a 25-item assessment requiring the recognition of a clinical interpretation of prerecorded LUS images.

Seventeen paramedics received a 45-minute LUS lecture. They then performed 25 LUS exams on both SPs and using simulation software, in each case looking for lung sliding, A and B lines, and seashore or barcode signs. Pre- and post-training, they completed a 25-question test consisting of still images and videos requiring pathology recognition and formulation of a clinical diagnosis. Sixteen paramedics performed the same exams in an ambulance during different driving conditions (stationary, constant acceleration, serpentines, and abrupt start-stops). Lung pathology was block randomized based on driving condition.

Paramedics demonstrated improved post-test scores compared to pre-test scores (P <.001). No significant difference existed across driving conditions for: time needed to obtain a simulated image; clinical interpretation of simulated LUS images; quality of saved images; or agreement of image interpretation between paramedics and blinded emergency physicians (EPs). Image acquisition time while parked was significantly greater than while the ambulance was driving in serpentines (Z = -2.898; P = .008). Technical challenges for both simulation techniques were noted.

Paramedics can correctly acquire and interpret simulated LUS images during different ambulance driving conditions. However, simulation techniques better adapted to this unique work environment are needed.