Objective: Incontrovertible disease markers are absent in delirium. This study investigated the usefulness of quantitative electroencephalography (qEEG) in diagnosing delirium. Methods: This retrospective case-control study reviewed medical records and qEEG data of 69 age/sex-matched patients (delirium group, n=30; control group, n=39). The first minute of artifact-free EEG data with eyes closed was selected. Nineteen electrodes’ sensitivity, specificity, and correlation with delirium rating scale-revised-98 were analyzed. Results: On comparing the means of absolute power by frontal, central, and posterior regions, the delta and theta powers showed significant differences (p<0.001) in all regions, and the magnitude of the absolute power was higher in the delirium group than in the control group; only the posterior region showed a significant (p<0.001) difference in beta power. The spectral power of theta at the frontal region (area under the curve [AUC]=0.84) and theta at the central and posterior regions (AUC=0.83) showed 90% sensitivity and 79% specificity, respectively, in differentiating delirious patients and controls. The beta power of the central region showed a significant negative correlation with delirium severity (R=-0.457, p=0.011). Conclusion Power spectrum analysis of qEEG showed high accuracy in screening delirium among patients. The study suggests qEEG as a potential aid in diagnosing delirium.

Objectives: ：This study assessed the psychological impact of quarantine during the coronavirus disease 2019 (COVID-19) outbreak. Methods: ：A total of 2080 participants filled the self-report questionnaire from March 17 to April 20, 2020 in Daegu, Republic of Korea. An online link was sent to currently or previously quarantined participants. The self-report questionnaire included patient health questionnaire-9 (PHQ-9), generalized anxiety disorder-7 (GAD-7), primary care post-traumatic stress disorder screen for diagnostic and statistical manual-5 (PTSD-PC), state-trait anger expression inventory (STAXI), and P4 suicidality screener scale (P4). PHQ-9 score of 5 or more and 9 or less indicates mild to moderate depressive symptoms, and 10 or more indicates severe depressive symptoms; A GAD-7 score of 5 or more and 14 or less indicates mild to moderate anxiety symptoms, and a score of 15 or more indicates severe anxiety symptoms; A PTSD-PC-5 score of 2 indicates mild to moderate PTSD; a score of 3 or higher indicates severe PTSD; A STAXI score of 14 or higher indicates severe anger symptoms; In P4, the cut-off points for each self-report questionnaire were set as mild suicidal thoughts at 1 point or more and 2 points or less, and severe suicide thoughts at 3 or more points. Logistic regression analyses were used to explore COVID-19-related risk factors. Results: ：The prevalence of mental health symptoms among the survey respondents was at 52.5% for depression, 44.5% for anxiety, 39.4% for post-traumatic stress, 31.6% for anger, and 10.9% for suicidal ideation. Participants with confirmed or suspected COVID-19 family members showed a high risk for symptoms of anxiety, posttraumatic stress, and anger. Participants with financial loss had increased symptoms of depression, anxiety, posttraumatic stress, anger, and suicidal ideation. Participants with a history of medical/psychiatric illnesses reported more symptoms of depression, anxiety, post-traumatic stress, anger, and suicidal ideation. Having inadequate basic supplies during quarantine was associated with negative mental health outcomes. Conclusions ：Quarantine had a negative psychological impact on all five mental health factors. The risk of depression, anxiety, post-traumatic stress disorder, anger, and suicidality increased among those who suffered from financial losses due to COVID-19. The associated risk factors will help identify populations at risk for mental health problems and implement mental health intervention policies.