Depression is a complex mental health disorder with highly heterogeneous symptoms that vary significantly across individuals, influenced by various factors, including sex and regional contexts. Network analysis is an analytical method that provides a robust framework for evaluating the heterogeneity of depressive symptoms and identifying their potential clinical implications.

To investigate sex-specific differences in the network structures of depressive symptoms in Asian patients diagnosed with depressive disorders, using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3, which was conducted in 2023.

A network analysis of 10 depressive symptoms defined according to the National Institute for Health and Care Excellence guidelines was performed. The sex-specific differences in the network structures of the depressive symptoms were examined using the Network Comparison Test. Subgroup analysis of the sex-specific differences in the network structures was performed according to geographical region classifications, including East Asia, Southeast Asia, and South or West Asia.

A total of 998 men and 1,915 women with depression were analysed in this study. The analyses showed that all 10 depressive symptoms were grouped into a single cluster. Low self-confidence and loss of interest emerged as the most central nodes for men and women, respectively. In addition, a significant difference in global strength invariance was observed between the networks. In the regional subgroup analysis, only East Asian men showed two distinct clustering patterns. In addition, significant differences in global strength and network structure were observed only between East Asian men and women.

The study highlights the sex-specific differences in depressive symptom networks across Asian countries. The results revealed that low self-confidence and loss of interest are the main symptoms of depression in Asian men and women, respectively. The network connections were more localised in men, whereas women showed a more diverse network. Among the Asian subgroups analysed, only East Asians exhibited significant differences in network structure. The considerable effects of neurovegetative symptoms in men may indicate potential neurobiological underpinnings of depression in the East Asian population.

Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones.

The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy.

Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively.

We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.

There are growing concerns about the impact of the COVID-19 pandemic on the mental health of older adults. We examined the effect of the pandemic on the risk of depression in older adults.

We analyzed data from the prospective cohort study of Korean older adults, which has been followed every 2 years. Among the 2308 participants who completed both the third and the fourth follow-up assessments, 58.4% completed their fourth follow-up before the outbreak of COVID-19 and the rest completed it during the pandemic. We conducted face-to-face diagnostic interviews using Mini International Neuropsychiatric Interview and used Geriatric Depression Scale. We performed generalized estimating equations and logistic regression analyses.

The COVID-19 pandemic was associated with increased depressive symptoms in older adults [b (standard error) = 0.42 (0.20), p = 0.040] and a doubling of the risk for incident depressive disorder even in euthymic older adults without a history of depression (odds ratio = 2.44, 95% confidence interval 1.18–5.02, p = 0.016). Less social activities, which was associated with the risk of depressive disorder before the pandemic, was not associated with the risk of depressive disorder during the pandemic. However, less family gatherings, which was not associated with the risk of depressive disorder before the pandemic, was associated with the doubled risk of depressive disorder during the pandemic.

The COVID-19 pandemic significantly influences the risk of late-life depression in the community. Older adults with a lack of family gatherings may be particularly vulnerable.

This study aimed to determine the effect of donor-transmitted atherosclerosis on the late aggravation of cardiac allograft vasculopathy in paediatric heart recipients aged ≥7 years.

In total, 48 patients were included and 23 had donor-transmitted atherosclerosis (baseline maximal intimal thickness of >0.5 mm on intravascular ultrasonography). Logistic regression analyses were performed to identify risk factors for donor-transmitted atherosclerosis. Rates of survival free from the late aggravation of cardiac allograft vasculopathy (new or worsening cardiac allograft vasculopathy on following angiograms, starting 1 year after transplantation) in each patient group were estimated using the Kaplan–Meier method and compared using the log-rank test. The effect of the results of intravascular ultrasonography at 1 year after transplantation on the late aggravation of cardiac allograft vasculopathy, correcting for possible covariates including donor-transmitted atherosclerosis, was examined using the Cox proportional hazards model.

The mean follow-up duration after transplantation was 5.97 ± 3.58 years. The log-rank test showed that patients with donor-transmitted atherosclerosis had worse survival outcomes than those without (p = 0.008). Per the multivariate model considering the difference of maximal intimal thickness between baseline and 1 year following transplantation (hazard ratio, 22.985; 95% confidence interval, 1.948–271.250; p = 0.013), donor-transmitted atherosclerosis was a significant covariate (hazard ratio, 4.013; 95% confidence interval, 1.047–15.376; p = 0.043).

Paediatric heart transplantation recipients with donor-transmitted atherosclerosis aged ≥7 years had worse late cardiac allograft vasculopathy aggravation-free survival outcomes.

Prognostic heterogeneity in early psychosis patients yields significant difficulties in determining the degree and duration of early intervention; this heterogeneity highlights the need for prognostic biomarkers. Although mismatch negativity (MMN) has been widely studied across early phases of psychotic disorders, its potential as a common prognostic biomarker in early periods, such as clinical high risk (CHR) for psychosis and first-episode psychosis (FEP), has not been fully studied.

A total of 104 FEP patients, 102 CHR individuals, and 107 healthy controls (HCs) participated in baseline MMN recording. Clinical outcomes were assessed; 17 FEP patients were treatment resistant, 73 FEP patients were nonresistant, 56 CHR individuals were nonremitters (15 transitioned to a psychotic disorder), and 22 CHR subjects were remitters. Baseline MMN amplitudes were compared across clinical outcome groups and tested for utility prognostic biomarkers using binary logistic regression.

MMN amplitudes were greatest in HCs, intermediate in CHR subjects, and smallest in FEP patients. In the clinical outcome groups, MMN amplitudes were reduced from the baseline in both FEP and CHR patients with poor prognostic trajectories. Reduced baseline MMN amplitudes were a significant predictor of later treatment resistance in FEP patients [Exp(β) = 2.100, 95% confidence interval (CI) 1.104–3.993, p = 0.024] and nonremission in CHR individuals [Exp(β) = 1.898, 95% CI 1.065–3.374, p = 0.030].

These findings suggest that MMN could be used as a common prognostic biomarker across early psychosis periods, which will aid clinical decisions for early intervention.

Over the past two decades, early detection and early intervention in psychosis have become essential goals of psychiatry. However, clinical impressions are insufficient for predicting psychosis outcomes in clinical high-risk (CHR) individuals; a more rigorous and objective model is needed. This study aims to develop and internally validate a model for predicting the transition to psychosis within 10 years.

Two hundred and eight help-seeking individuals who fulfilled the CHR criteria were enrolled from the prospective, naturalistic cohort program for CHR at the Seoul Youth Clinic (SYC). The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was used to develop a predictive model for a psychotic transition. We performed k-means clustering and survival analysis to stratify the risk of psychosis.

The predictive model, which includes clinical and cognitive variables, identified the following six baseline variables as important predictors: 1-year percentage decrease in the Global Assessment of Functioning score, IQ, California Verbal Learning Test score, Strange Stories test score, and scores in two domains of the Social Functioning Scale. The predictive model showed a cross-validated Harrell's C-index of 0.78 and identified three subclusters with significantly different risk levels.

Overall, our predictive model showed a predictive ability and could facilitate a personalized therapeutic approach to different risks in high-risk individuals.

We report our experience with an emergency room (ER) shutdown related to an accidental exposure to a patient with coronavirus disease 2019 (COVID-19) who had not been isolated.

A 635-bed, tertiary-care hospital in Daegu, South Korea.

To prevent nosocomial transmission of the disease, we subsequently isolated patients with suspected symptoms, relevant radiographic findings, or epidemiology. Severe acute respiratory coronavirus 2 (SARS-CoV-2) reverse-transcriptase polymerase chain reaction assays (RT-PCR) were performed for most patients requiring hospitalization. A universal mask policy and comprehensive use of personal protective equipment (PPE) were implemented. We analyzed effects of these interventions.

From the pre-shutdown period (February 10–25, 2020) to the post-shutdown period (February 28 to March 16, 2020), the mean hourly turnaround time decreased from 23:31 ±6:43 hours to 9:27 ±3:41 hours (P < .001). As a result, the proportion of the patients tested increased from 5.8% (N=1,037) to 64.6% (N=690) (P < .001) and the average number of tests per day increased from 3.8±4.3 to 24.7±5.0 (P < .001). All 23 patients with COVID-19 in the post-shutdown period were isolated in the ER without any problematic accidental exposure or nosocomial transmission. After the shutdown, several metrics increased. The median duration of stay in the ER among hospitalized patients increased from 4:30 hours (interquartile range [IQR], 2:17–9:48) to 14:33 hours (IQR, 6:55–24:50) (P < .001). Rates of intensive care unit admissions increased from 1.4% to 2.9% (P = .023), and mortality increased from 0.9% to 3.0% (P = .001).

Problematic accidental exposure and nosocomial transmission of COVID-19 can be successfully prevented through active isolation and surveillance policies and comprehensive PPE use despite longer ER stays and the presence of more severely ill patients during a severe COVID-19 outbreak.

Suicide rates are high among elderly individuals experiencing socioeconomic insecurity. Socioeconomic security is of critical importance for elderly individuals and directly affects mental health, including suicidal behavior. Thus, we investigated the relationship between socioeconomic status and suicidal ideation in elderly individuals.

We conducted a cross-sectional study using data on 58,590 individuals 65 years of age or older from the Korean Community Health Survey 2013. Logistic regression analysis was used to identify relationships between socioeconomic factors (food insecurity, household income, and living arrangement) and suicidal ideation in the elderly population.

The study included 58,590 participants (24,246 males and 34,344 females). Of those, 2,847 males and 6,418 females experienced suicidal ideation. Participants with food insecure were more likely to experience suicidal ideation than were those who were food secure (males: OR = 1.60; 95% CI, 1.34–1.90; females: OR = 1.54; 95% CI, 1.38–1.72). We found a similar pattern among participants with a low household income and those living alone. Additionally, male and female subjects who were food insecure and living alone or food insecure and had a low household income showed a marked increase in suicidal ideation.

Our findings suggest that low socioeconomic status is associated with an increased risk of suicidal ideation among the elderly. Furthermore, intervention programs that address the prevalence of elderly suicide, particularly among those who are socioeconomically disadvantaged, are needed.

Whether an association exists between cerebral microbleeds (CMBs) and functional recovery after ischemic stroke is unclear. We aimed to evaluate the association between CMBs and functional outcome after acute ischemic stroke.

Consecutive patients with acute stroke were enrolled, and all patients were stratified into good and poor functional outcome groups at discharge and 6 months after ischemic stroke by using a modified Rankin Scale score. Cardiovascular risk factors, CMBs, and white matter hyperintensities were compared between these two outcome groups. Logistic regression analysis was used to estimate the risk of poor functional outcomes.

A total of 225 patients were enrolled, 121 of whom were classified as having a good functional outcome at discharge and 142 as having a good 6-month functional outcome. The presence of CMBs was associated with a poor functional outcome at discharge [CMBs (+) patients in poor vs. good functional group; 48.1% vs. 30.6%; p=0.007] and 6 months [53.0% vs. 30.3%; p=0.001]. After adjustment for confounding factors, only the presence of infratentorial CMBs was associated with a poor functional outcome at discharge and 6 months. The poor functional outcome group had more CMBs than the good outcome group at 6 months.

Infratentorial cerebral microbleeds were significantly associated with worse functional outcomes not only in the early phase of ischemic stroke but also in the chronic phase. These findings suggest that the presence of infratentorial CMBs can predict poor functional outcome after acute ischemic stroke.

Social support programs for dementia caregivers were widely used in order to reduce care burden. We investigated which types of social supports can reduce psychological and non-psychological burdens of dementia caregivers, and explored the mechanism of those social supports.

We evaluated 731 community-dwelling dementia patients and their caregivers from the National Survey of Dementia Care in South Korea. We investigated the five types of social supports (emotional support, informational support, tangible support, positive social interaction, affectionate support) using the Medical Outcomes Study Social Support Survey in each caregiver. The mechanisms of specific types of social support on psychological/non-psychological burden were examined using path analysis.

Positive social interaction and affectionate support reduced psychological burden via direct and indirect paths. Tangible support reduced the non-psychological burden via direct and indirect paths. Informational support and emotional support were not helpful for reducing psychological or non-psychological burden. A maximum of 20% of psychological burden could be relieved by positive social interaction and 10.3% of that could be reduced by affectionate support. Tangible support was associated with a 15.1% maximal improvement in non-psychological burden.

In order to reduce caregiver burden in dementia effectively, psychosocial interventions should be tailored to target type of caregiver burden.