This study aimed to utilise graph theory to explore the functional brain networks in individuals with tic disorders and to investigate resting-state functional connectivity changes in critical brain regions associated with tic disorders.

Participants comprised individuals with tic disorders and age-matched healthy controls, ranging from 6 to 18 years old, all recruited from Korea University Guro Hospital. We ensured a medication-naïve cohort by excluding participants exposed to psychotropic medications for at least three weeks prior to the study. Data included structural and resting-state functional MRI scans, analysed with the CONN-fMRI Functional Connectivity toolbox v20b. The analysis included 22 patients (18 males, 4 females) and 26 controls (14 males, 12 females).

Significantly increased global efficiency was observed in the left inferior frontal gyrus pars opercularis among tic disorder patients compared to controls. Furthermore, this region displayed enhanced resting-state functional connectivity with its right counterpart in patients versus controls.

The inferior frontal gyrus pars opercularis, known for its inhibitory role, may reflect adaptive functional adjustments in response to tic symptoms. Increased hubness of the inferior frontal gyrus pars opercularis possibly represents functional adjustments in response to tic symptoms. The identified brain region with increased efficiency and connectivity presents a promising avenue for further research into tic expression and control mechanisms.

Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses.

Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed.

Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028).

This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry.

Comorbid depression substantially affects the management of glycemia and diabetes-related complications among patients with type 2 diabetes mellitus. In this study, we sought to determine the association between weight change over 4 years and depression risk among patients with type 2 diabetes mellitus.

This population-based retrospective cohort study from the National Health Insurance Services of Korea included 1 111 345 patients with type 2 diabetes who were divided into groups according to body weight change over 4 years. Body weight changes were compared with the preceding 4-year period (2005–2008). Depression was defined according to the International Classification of Diseases 10th revision code for depression (F32 and F33) on one or more inpatient or outpatient claims.

During a median follow-up of 7.4 years, 244 081 cases of depression were identified. We observed a U-shaped association between body weight change and depression risk with a higher risk among both groups of weight loss (hazard ratio (HR) 1.17, 95% CI 1.15–1.19 for ⩾ −10%; HR 1.07, 95% CI 1.06–1.08 for −10 to −5%) and weight gain (HR 1.06, 95% CI 1.04–1.08 for ⩾10%; HR 1.02, 95% CI 1.01–1.04 for 5–10%) compared with the stable weight group (−5 to 5%).

A U-shaped association between body weight change and depression risk was observed in this large nationwide cohort study. Our study suggests that patients with type 2 diabetes and weight change, either gain or loss, could be considered a high-risk group for depression.

Cancer is a life-changing experience, and side effects from treatment can make it difficult for survivors to return to their pre-cancer “normal life.” We explored the “new normal” and barriers to achieving it among lung cancer survivors who underwent surgery.

Semi-structured interviews were conducted with 32 recurrence-free non–small cell lung cancer survivors. We asked survivors how life had changed; how they defined the “new normal”; barriers that prevent them from achieving a “normal” life; and unmet needs or support for normalcy. Thematic analysis was performed.

Defining “new normal” subjectively depends on an individual’s expectation of recovery: (1) being able to do what they want without pain or discomfort; (2) being able to do activities they could accomplish before their surgery; and (3) being able to work, earn money, and support their family. We found that (1) persistent symptoms, (2) fear of cancer recurrence, (3) high expectations in recovery, and (4) psychosocial stress and guilty feelings were barriers to achieving a “new normal.” The needs and support for normalcy were information on expected trajectories, postoperative management, and support from family and society.

Survivors defined the “new normal” differently, depending on their expectations for recovery. Informing survivors about the “new normal” so they could expect possible changes and set realistic goals for their life after cancer. Health professionals need to communicate with survivors about expectations for “normality” from the beginning of treatment, and it should be included in comprehensive survivorship care.

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.

To investigate the impacts of depression screening, diagnosis and treatment on major adverse cardiac events (MACEs) in acute coronary syndrome (ACS).

Prospective cohort study including a nested 24-week randomised clinical trial for treating depression was performed with 5–12 years after the index ACS. A total of 1152 patients recently hospitalised with ACS were recruited from 2006 to 2012, and were divided by depression screening and diagnosis at baseline and 24-week treatment allocation into five groups: 651 screening negative (N), 55 screening positive but no depressive disorder (S), 149 depressive disorder randomised to escitalopram (E), 151 depressive disorder randomised to placebo (P) and 146 depressive disorder receiving medical treatment only (M).

Cumulative MACE incidences over a median 8.4-year follow-up period were 29.6% in N, 43.6% in S, 40.9% in E, 53.6% in P and 59.6% in M. Compared to N, screening positive was associated with higher incidence of MACE [adjusted hazards ratio 2.15 (95% confidence interval 1.63–2.83)]. No differences were found between screening positive with and without a formal depressive disorder diagnosis. Of those screening positive, E was associated with a lower incidence of MACE than P and M. M had the worst outcomes even compared to P, despite significantly milder depressive symptoms at baseline.

Routine depression screening in patients with recent ACS and subsequent appropriate treatment of depression could improve long-term cardiac outcomes.