In the current study, delirium occurred in 44% of elderly patients after a major operation. Pre-existing cognitive dysfunction was the strongest predictor of the development of postoperative delirium. Outcomes, including an increased rate of 6 month mortality, were worse in patients who developed postoperative delirium.

This large-scale cohort comparison study found that SPI+ was associated with a reduction in suicidal behavior and increased treatment engagement among suicidal patients following ED discharge and may be a valuable clinical tool in health care settings.

Following deployment to Iraq, a clinician-confirmed TBI history was identified in 22.8% of soldiers from a BCT. Those with TBI were significantly more likely to report postinjury and postdeployment somatic and/or neuropsychiatric symptoms than those without this injury history. Overall, symptom endorsement decreased over time.

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The importance of early screening for both conditions is highlighted. In addition, the authors suggest that current best practices include treating symptoms regardless of etiology to decrease military personnel and veteran burden of adversity.

A history of mild traumatic brain injury (mTBI) is common among military members who served in Operations Enduring Freedom, Iraqi Freedom, and New Dawn (OEF/OIF/OND). We completed a systematic review to describe the cognitive, mental health, physical health, functional, social, and cost consequences of mTBI in Veteran and military personnel. Of 2668 reviewed abstracts, the 31 included studies provided very low strength evidence for the questions of interest. Cognitive, physical, and mental health symptoms were commonly reported by Veterans/military members with a history of mTBI. On average, these symptoms were not significantly more common in those with a history of mTBI than in those without, although a lack of significant mean differences does not preclude the possibility that some individuals could experience substantial effects related to mTBI history. Evidence of potential risk or protective factors moderating mTBI outcomes was unclear. Although the overall strength of evidence is very low due to methodological limitations of included studies, our findings are consistent with civilian studies. Appropriate re-integration services are needed to address common comorbid conditions, such as treatment for post-traumatic stress disorder, substance use disorders, headaches, and other difficulties that Veterans and members of the military may experience after deployment regardless of mTBI history. (JINS, 2014, 20, 1-13).

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity, and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1,056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared to observed scores assessed 10–12 years after baseline. ML model prediction accuracy was also compared to that of conventional logistic regression models. Area under the receiver operating characteristic curve (AUC) based on ML (.63 for high chronicity and .71–.76 for the other prospective outcomes) was consistently higher than for the logistic models (.62–.70) despite the latter models including more predictors. 34.6–38.1% of respondents with subsequent high persistence-chronicity and 40.8–55.8% with the severity indicators were in the top 20% of the baseline ML predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML predicted risk distribution. These results confirm that clinically useful MDD risk stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

In soldiers with histories of physical injury, mTBI and PTSD were independently associated with PC symptom reporting. Those with both conditions were at greater risk for PC symptoms than those with either PTSD, mTBI, or neither. Findings support the importance of continued screening for both conditions with the aim of early identification and intervention.