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Nightmares are a unique feature of posttraumatic stress disorder (PTSD). Although nightmares are a symptom of PTSD, they have been shown to independently contribute to psychiatric distress and poor outcomes, including heightened suicidality and suicide. Nightmares are often resistant to recommended pharmacological or psychological PTSD treatments. Fortunately, nightmare-specific treatments are available, and improvements in nightmares are associated with clinically significant improvements in sleep quality and severity of daytime PTSD symptoms. The recent literature on the characteristics, neurophysiology, and treatment of nightmares in the context of PTSD is reviewed. Recent findings on the neurophysiological correlates of nightmares and more generally, dreaming, are also discussed here as they suggest novel directions for understanding the mechanisms underlying nightmares comorbid with PTSD and potential novel treatment approaches.

BACKGROUND AND PURPOSEEfficacy of restorative cognitive rehabilitation can be predicted from baseline patient factors. In addition, patient profiles of functional connectivity are associated with cognitive reserve and moderate the structure‐cognition relationship in people with multiple sclerosis (PwMS). Such interactions may help predict which PwMS will benefit most from cognitive rehabilitation. Our objective was to determine whether patient response to restorative cognitive rehabilitation is predictable from baseline structural network disruption and whether this relationship is moderated by functional connectivity.METHODSFor this single‐arm repeated measures study, we recruited 25 PwMS for a 12‐week program. Following magnetic resonance imaging, participants were tested using the Symbol Digit Modalities Test (SDMT) pre‐ and postrehabilitation. Baseline patterns of structural and functional connectivity were characterized relative to healthy controls.RESULTSLower white matter tract disruption in a network of region‐pairs centered on the precuneus and posterior cingulate (default‐mode network regions) predicted greater postrehabilitation SDMT improvement (P = .048). This relationship was moderated by profiles of functional connectivity within the network (R2 = .385, P = .017, Interaction β = –.415).CONCLUSIONPatient response to restorative cognitive rehabilitation is predictable from the interaction between structural network disruption and functional connectivity in the default‐mode network. This effect may be related to cognitive reserve.

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.