Objective Comprehensive review of the use of computerized treatment as a rehabilitation tool for attention and executive function in adults (aged 18 years or older) who suffered an acquired brain injury. Design Systematic review of empirical research. Main Measures Two reviewers independently assessed articles using the methodological quality criteria of Cicerone et al. Data extracted included sample size, diagnosis, intervention information, treatment schedule, assessment methods, and outcome measures. Results A literature review (PubMed, EMBASE, Ovid, Cochrane, PsychINFO, CINAHL) generated a total of 4931 publications. Twenty-eight studies using computerized cognitive interventions targeting attention and executive functions were included in this review. In 23 studies, significant improvements in attention and executive function subsequent to training were reported; in the remaining 5, promising trends were observed. Conclusions Preliminary evidence suggests improvements in cognitive function following computerized rehabilitation for acquired brain injury populations including traumatic brain injury and stroke. Further studies are needed to address methodological issues (eg, small sample size, inadequate control groups) and to inform development of guidelines and standardized protocols.

Prevalence of nine chronic medical conditions in the population-based Ft. Devens Cohort (FDC) of GW veterans were compared with the population-based 2013–2014 National Health and Nutrition Examination Survey (NHANES) cohort. Excess prevalence was calculated as the difference in prevalence estimates from the Ft. Devens and NHANES cohorts; and confidence intervals and p-values are based on the standard errors for the two prevalence estimates. FDC males were at increased risk for reporting seven chronic medical conditions compared with NHANES males. FDC females were at decreased risk for high blood pressure and increased risk for diabetes when compared with NHANES females. FDC veterans reporting war-related chemical weapons exposure showed higher risk of high blood pressure; diabetes; arthritis and chronic bronchitis while those reporting taking anti-nerve gas pills had increased risk of heart attack and diabetes. GW veterans are at higher risk of chronic conditions than the general population and these risks are associated with self-reported toxicant exposures.

Supplemental Digital Content is available in the text.

Supplemental Digital Content is available in the text.

ObjectivesAcross diverse groups of Gulf War (GW) veterans, reports of musculoskeletal pain, cognitive dysfunction, unexplained fatigue, chronic diarrhoea, rashes and respiratory problems are common. GW illness is a condition resulting from GW service in veterans who report a combination of these symptoms. This study integrated the GW literature using meta-analytical methods to characterise the most frequently reported symptoms occurring among veterans who deployed to the 1990–1991 GW and to better understand the magnitude of ill health among GW-deployed veterans compared with non-deployed GW-era veterans.DesignMeta-analysis.MethodsLiterature databases were searched for peer-reviewed studies published from January 1990 to May 2017 reporting health symptom frequencies in GW-deployed veterans and GW-era control veterans. Self-reported health symptom data were extracted from 21 published studies. A binomial-normal meta-analytical model was used to determine pooled prevalence of individual symptoms in GW-deployed veterans and GW-era control veterans and to calculate combined ORs of health symptoms comparing GW-deployed veterans and GW-era control veterans.ResultsGW-deployed veterans had higher odds of reporting all 56 analysed symptoms compared with GW-era controls. Odds of reporting irritability (OR 3.21, 95% CI 2.28 to 4.52), feeling detached (OR 3.59, 95% CI 1.83 to 7.03), muscle weakness (OR 3.19, 95% CI 2.73 to 3.74), diarrhoea (OR 3.24, 95% CI 2.51 to 4.17) and rash (OR 3.18, 95% CI 2.47 to 4.09) were more than three times higher among GW-deployed veterans compared with GW-era controls.ConclusionsThe higher odds of reporting mood-cognition, fatigue, musculoskeletal, gastrointestinal and dermatological symptoms among GW-deployed veterans compared with GW-era controls indicates these symptoms are important when assessing GW veteran health status.

Aim Asymptomatic deep vein thrombosis (DVT) diagnosed with compression ultrasound (CUS) is a common endpoint in trials assessing the efficacy of anticoagulants to prevent venous thromboembolism (VTE), but the relationship of asymptomatic thrombus to mortality remains uncertain. Methods In the APEX trial (ClinicalTrials.gov: NCT01583218), 7,513 acutely ill hospitalized medical patients were randomly assigned to extended-duration betrixaban (35–42 days) or enoxaparin (10 ± 4 days). Asymptomatic DVT was assessed once with CUS between day 32 and 47, and mortality was assessed through 77 days. Results A total of 309 asymptomatic DVTs were detected through CUS. Of these, 133 (4.27%) subjects were in the betrixaban group, and 176 (5.55%) subjects were in the enoxaparin group (relative risk = 0.77, 95% confidence interval [CI] = 0.62–0.97, p = 0.025, number needed to treat = 79). With respect to all-cause mortality due to cardiovascular diseases, non-cardiovascular diseases and unknown causes, the number of the deaths was 5 (1.67%), 4 (1.34%) and 1 (0.33%) in the asymptomatic DVT group and 25 (0.42%), 33 (0.56%) and 11 (0.19%) in the no DVT group, respectively. Subjects with an asymptomatic DVT had an almost threefold increase in the risk of all-cause mortality compared with subjects without DVT (hazard ratio = 2.87, 95% CI = 1.48–5.57, p = 0.001). A positive linear trend was observed between greater thrombus burden and mortality during the follow-up (p = 0.019). Conclusion Asymptomatic DVT was associated with approximately threefold increased risk of short-term all-cause mortality in patients hospitalized with an acute medical illness within the prior 77 days. A positive linear trend was observed between greater thrombus burden and mortality during the follow-up.

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Background The identification of acutely ill patients at high risk for venous thromboembolism (VTE) may be determined clinically or by use of integer‐based scoring systems. These scores demonstrated modest performance in external data sets. Objectives To evaluate the performance of machine learning models compared to the IMPROVE score. Methods The APEX trial randomized 7513 acutely medically ill patients to extended duration betrixaban vs. enoxaparin. Including 68 variables, a super learner model (ML) was built to predict VTE by combining estimates from 5 families of candidate models. A “reduced” model (rML) was also developed using 16 variables that were thought, a priori, to be associated with VTE. The IMPROVE score was calculated for each patient. Model performance was assessed by discrimination and calibration to predict a composite VTE end point. The frequency of predicted risks of VTE were plotted and divided into tertiles. VTE risks were compared across tertiles. Results The ML and rML algorithms outperformed the IMPROVE score in predicting VTE (c‐statistic: 0.69, 0.68 and 0.59, respectively). The Hosmer‐Lemeshow goodness‐of‐fit P‐value was 0.06 for ML, 0.44 for rML, and <0.001 for the IMPROVE score. The observed event rate in the lowest tertile was 2.5%, 4.8% in tertile 2, and 11.4% in the highest tertile. Patients in the highest tertile of VTE risk had a 5‐fold increase in odds of VTE compared to the lowest tertile. Conclusion The super learner algorithms improved discrimination and calibration compared to the IMPROVE score for predicting VTE in acute medically ill patients.