Patients with schizophrenia experience accelerated aging, accompanied by abnormalities in biomarkers such as shorter telomere length. Brain age prediction using neuroimaging data has gained attention in schizophrenia research, with consistently reported increases in brain-predicted age difference (brain-PAD). However, its associations with clinical symptoms and illness duration remain unclear.

We developed brain age prediction models using structural magnetic resonance imaging (MRI) data from 10,938 healthy individuals. The models were validated on an independent test dataset comprising 79 healthy controls, 57 patients with recent-onset schizophrenia, and 71 patients with chronic schizophrenia. Group comparisons and the clinical associations of brain-PAD were analyzed using multiple linear regression. SHapley Additive exPlanations (SHAP) values estimated feature contributions to the model, and between-group differences in SHAP values and group-by-SHAP value interactions were also examined.

Patients with recent-onset schizophrenia and chronic schizophrenia exhibited increased brain-PAD values of 1.2 and 0.9 years, respectively. Between-group differences in SHAP values were identified in the right lateral prefrontal area (false discovery rate [FDR] p = 0.022), with group-by-SHAP value interactions observed in the left prefrontal area (FDR p = 0.049). A negative association between brain-PAD and Full-scale Intelligence Quotient scores in chronic schizophrenia was noted, which did not remain significant after correction for multiple comparisons.

Brain-PAD increases were pronounced in the early phase of schizophrenia. Regional brain abnormalities contributing to brain-PAD likely vary with illness duration. Future longitudinal studies are required to overcome limitations related to sample size, heterogeneity, and the cross-sectional design of this study.

It has been suggested that schizophrenia involves dysconnectivity between functional brain regions and also the white matter structural disorganisation. Thus, diffusion tensor imaging (DTI) has widely been used for studying schizophrenia. However, most previous studies have used the region of interest (ROI) based approach. We, therefore, performed the probabilistic tractography method in this study to reveal the alterations of white matter tracts in the schizophrenia brain.

A total of four different datasets consisted of 189 patients with schizophrenia and 213 healthy controls were investigated. We performed retrospective harmonisation of raw diffusion MRI data by dMRIharmonisation and used the FMRIB Software Library (FSL) for probabilistic tractography. The connectivities between different ROIs were then compared between patients and controls. Furthermore, we evaluated the relationship between the connection probabilities and the symptoms and cognitive measures in patients with schizophrenia.

After applying Bonferroni correction for multiple comparisons, 11 different tracts showed significant differences between patients with schizophrenia and healthy controls. Many of these tracts were associated with the basal ganglia or cortico-striatal structures, which aligns with the current literature highlighting striatal dysfunction. Moreover, we found that these tracts demonstrated statistically significant relationships with few cognitive measures related to language, executive function, or processing speed.

We performed probabilistic tractography using a large, harmonised dataset of diffusion MRI data, which enhanced the statistical power of our study. It is important to note that most of the tracts identified in this study, particularly callosal and cortico-striatal streamlines, have been previously implicated in schizophrenia within the current literature. Further research with harmonised data focusing specifically on these brain regions could be recommended.

Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects.

We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonising the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fibre clustering on the tractography data. We compared the fractional anisotropy (FA) of white matter tracts between healthy controls and patients with schizophrenia. Spearman’s rho was adopted for the associations with clinical symptoms measured by the Positive and Negative Syndrome Scale (PANSS). The Bonferroni correction was used to adjust multiple testing.

Among the 33 DWM and 8 SWM tracts, patients with schizophrenia had a lower FA in 14 DWM and 4 SWM tracts than healthy controls, with small effect sizes. In the patient group, the FA deviations of the corticospinal and superficial–occipital tracts were negatively correlated with the PANSS negative score; however, this correlation was not evident after adjusting for multiple testing.

We observed the structural impairments of both the DWM and SWM tracts in patients with schizophrenia. The SWM could be a potential target of interest in future research on neural biomarkers for schizophrenia.

Substantial evidence indicates structural abnormalities in the cerebral cortex of patients with schizophrenia (SCZ), although their clinical implications remain unclear. Previous case-control studies have investigated group-level differences in structural abnormalities, although the study design cannot account for interindividual differences. Recent research has focused on the association between the heterogeneity of the cerebral cortex morphometric features and clinical heterogeneity.

We used neuroimaging data from 420 healthy controls and 695 patients with SCZ from seven studies. Four cerebral cortex measures were obtained: surface area, gray matter volume, thickness, and local gyrification index. We calculated the coefficient of variation (CV) and person-based similarity index (PBSI) scores and performed group comparisons. Associations between the PBSI scores and cognitive functions were evaluated using Spearman's rho test and normative modeling.

Patients with SCZ had a greater CV of surface area and cortical thickness than those of healthy controls. All PBSI scores across cortical measures were lower in patients with SCZ than in HCs. In the patient group, the PBSI scores for gray matter volume and all cortical measures taken together positively correlated with the full-scale IQ scores. Patients with deviant PBSI scores for gray matter volume and all cortical measures taken together had lower full-scale IQ scores than those of other patients.

The cerebral cortex in patients with SCZ showed greater regional and global structural variability than that in healthy controls. Patients with deviant similarity of cortical structural profiles exhibited a lower general intelligence than those exhibited by the other patients.

Clozapine is generally considered as the treatment of choice for patients with treatment-resistant schizophrenia (TRS). However, its superiority has recently been questioned because olanzapine has been suggested as non-inferior to clozapine in its effectiveness.

We aimed to investigate the current status of clozapine prescriptions to identify any disparity between clinical guidelines and real-world practices.

In this study, we utilised the Health Insurance Review Agency database in the Republic of Korea to investigate the real-world effectiveness of clozapine for patients with TRS. We compared differences in patient variables before and after clozapine administration, and we also performed survival analyses for both psychiatric admissions and emergency room visits among patients who used clozapine or olanzapine.

This study investigated an incident cohort of 64 442 patients, and 2338 patients have been prescribed clozapine. Of these, 998 patients had TRS. In survival analysis, clozapine showed a worse survival rate for psychiatric admissions than olanzapine (hazard ratio 0.615). We also identified that clinicians tended to try a number of antipsychotics, as recommended, before starting patients on clozapine.

In conclusion, we found that olanzapine led to higher survival rates for psychiatric admissions than clozapine. Thus, considering the risk of serious adverse effects, clozapine may be used conservatively. Considering several studies advocating superior efficacy of clozapine, further studies with extensive data are recommended.

Current evidence on antipsychotic treatment and risk of psychiatric hospitalization in first-episode schizophrenia (FES) is largely based on the findings from randomized clinical trials (RCTs). However, the generalization of the findings to real-world patients is limited due to inherent caveats of the RCT. We aimed to investigate the treatment discontinuation and risk of psychiatric hospitalization using a nationwide population database.

The Health Insurance Review Agency database in South Korea was obtained, and the observation period started from 1 January 2009 to 31 December 2016. We defined the maintenance period as the period from 6-month after the diagnosis of schizophrenia, which is utilized for the main results. For a total of 44 396 patients with FES, a within-individual Cox regression model was used to compare the risk of the treatment discontinuation and psychiatric hospitalization.

In group comparison, a long-acting injectable (LAI) antipsychotic group was associated with the lowest risk of the treatment discontinuation (0.64, 0.55–0.75) and psychiatric hospitalization (0.29, 0.22–0.38) in comparison with a typical antipsychotic group and no use, respectively. Among individual antipsychotics, the lowest risk of the treatment discontinuation was observed in LAI paliperidone (0.46, 0.37–0.66) compared to olanzapine. Clozapine was found to be the most effective antipsychotic in lowering the risk of psychiatric hospitalization as monotherapy compared to no use (0.23, 0.18–0.31).

In real-world patients with FES, LAI paliperidone and clozapine were associated with low treatment discontinuation and better effectiveness in lowering the risk of psychiatric hospitalization.

Network approach has been applied to a wide variety of psychiatric disorders. The aim of the present study was to identify network structures of remitters and non-remitters in patients with first-episode psychosis (FEP) at baseline and the 6-month follow-up.

Participants (n = 252) from the Korean Early Psychosis Study (KEPS) were enrolled. They were classified as remitters or non-remitters using Andreasen's criteria. We estimated network structure with 10 symptoms (three symptoms from the Positive and Negative Syndrome Scale, one depressive symptom, and six symptoms related to schema and rumination) as nodes using a Gaussian graphical model. Global and local network metrics were compared within and between the networks over time.

Global network metrics did not differ between the remitters and non-remitters at baseline or 6 months. However, the network structure and nodal strengths associated with positive-self and positive-others scores changed significantly in the remitters over time. Unique central symptoms for remitters and non-remitters were cognitive brooding and negative-self, respectively. The correlation stability coefficients for nodal strength were within the acceptable range.

Our findings indicate that network structure and some nodal strengths were more flexible in remitters. Negative-self could be an important target for therapeutic intervention.

Traumatic brain injury (TBI) is an important public health concern because of the high mortality rate of young people and a high proportion among the trauma. According to studies, patients visiting the emergency department (ED) with TBI comprise 1.4% of all ED patients.

The authors think that the characteristics of patients with TBI will vary according to the age group. Therefore, the purpose of this study is to investigate the clinical and social characteristics of patients with TBI visiting the ED by age group.

Trauma patients who conducted brain CT at the ED of Korean University Hospital (three hospitals) for 3 years from March 2013 to February 2016 were enrolled. Medical records were investigated retrospectively. The GCS scores were estimated at initial ED arrival. The primary outcome was to determine the characteristics of each age groups with gender, severity (by GSC score), trauma mechanism, and admission rate.

A total of 15,567 TBI patients received brain CT evaluation during the investigation period. Based on age, patients in their 50s were the most common (16.5%). Regarding the severity, the ratio of mild was higher in under patients under 9 (99.3%); the ratio of severe was higher for patients in their 20s (4.6%). In almost every age group, the male ratio of TBI was higher, except for females aged 70 or older. Under 19 years of age, the ambulance utilization rate was lower than any other age group. The most common injury mechanism was a collision, the next was a traffic accident, and in under 9, a fall was the most common. 70.1% of patients returned home after treatments.

Identifying the characteristics of patients with TBI visiting ED is fundamental. Therefore, it is necessary to continuously collect basic data on TBI among patients visiting the ED.

Social media data are a highly contextual health information source. The objective of this study was to identify Korean keywords for detecting influenza epidemics from social media data.

We included data from Twitter and online blog posts to obtain a sufficient number of candidate indicators and to represent a larger proportion of the Korean population. We performed the following steps: initial keyword selection; generation of a keyword time series using a preprocessing approach; optimal feature selection; model building and validation using least absolute shrinkage and selection operator, support vector machine (SVM), and random forest regression (RFR).

A total of 15 keywords optimally detected the influenza epidemic, evenly distributed across Twitter and blog data sources. Model estimates generated using our SVM model were highly correlated with recent influenza incidence data.

The basic principles underpinning our approach could be applied to other countries, languages, infectious diseases, and social media sources. Social media monitoring using our approach may support and extend the capacity of traditional surveillance systems for detecting emerging influenza. (Disaster Med Public Health Preparedness. 2018; 12: 352–359)

This study investigates the relationship between insomnia and cognitive dysfunctions including, subjective memory impairment (SMI), mild cognitive impairment (MCI), and dementia, by considering depression in a community sample of elderly individuals.

Data for 1,740 elderly individuals aged 65 years and over were obtained from a nationwide dementia epidemiological study conducted in South Korea. Cognitive functional status was assessed by the Mini-Mental State Examination and the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet Clinical Assessment Battery. Insomnia was defined as the presence of at least one of the four sleep complaints (difficulty in initiating sleep, difficulty in maintaining sleep, early morning awakening, and non-restorative sleep), accompanied by moderate to severe daytime consequences. Depression was evaluated using the Geriatric Depression Scale.

The prevalence of insomnia in the patients with SMI, MCI, and dementia was found to be 23.2%, 19.6%, and 31.0%, respectively. The patients with SMI, MCI, and dementia were significantly more likely to have insomnia and the four sleep complaints than the normal comparison patients. After adjusting for sociodemographic factors, the significant relationships between cognitive dysfunctional status and insomnia remained. However, after adjusting for sociodemographic factors and depression, no significant relationships with any of the sleep complaints or insomnia remained.

Insomnia is a very common complaint in the elderly with SMI, MCI, and dementia. Depression might play an important factor in the relationship between insomnia and cognitive dysfunctional status in the elderly.

To determine the influence of early pain relief for patients with suspected appendicitis on the diagnostic performance of surgical residents.

A prospective randomized, double-blind, placebo-controlled trial was conducted for patients with suspected appendicitis. The patients were randomized to receive placebo (normal saline intravenous [IV]) infusions over 5 minutes or the study drug (morphine 5 mg IV). All of the clinical evaluations by surgical residents were performed 30 minutes after administration of the study drug or placebo. After obtaining the clinical probability of appendicitis, as determined by the surgical residents, abdominal computed tomography was performed. The primary objective was to compare the influence of IV morphine on the ability of surgical residents to diagnose appendicitis.

A total of 213 patients with suspected appendicitis were enrolled. Of these patients, 107 patients received morphine, and 106 patients received placebo saline. The negative appendectomy percentages in each group were similar (3.8% in the placebo group and 3.2% in the pain control group, p=0.62). The perforation rates in each group were also similar (18.9% in the placebo group and 14.3% in the pain control group, p=0.75). Receiver operating characteristic analysis revealed that the overall diagnostic accuracy in each group was similar (the area under the curve of the placebo group and the pain control group was 0.63 v. 0.61, respectively, p=0.81).

Early pain control in patients with suspected appendicitis does not affect the diagnostic performance of surgical residents.