We evaluated the adequacy of microbiological tests in patients withholding or withdrawing life-sustaining treatment (WLST) at the end stage of life.

The study was conducted at 2 tertiary-care referral hospitals in Daegu, Republic of Korea.

Retrospective cross-sectional study.

Demographic findings, clinical and epidemiological characteristics, statistics of microbiological tests, and microbial species isolated from patients within 2 weeks before death were collected in 2 tertiary-care referral hospitals from January to December 2018. We also reviewed the antimicrobial treatment that was given within 3 days of microbiological testing in patients on WLST.

Of the 1,187 hospitalized patients included, 905 patients (76.2%) had WLST. The number of tests per 1,000 patient days was higher after WLST than before WLST (242.0 vs 202.4). Among the category of microbiological tests, blood cultures were performed most frequently, and their numbers per 1,000 patient days before and after WLST were 95.9 and 99.0, respectively. The positive rates of blood culture before and after WLST were 17.2% and 18.0%, respectively. Candida spp. were the most common microbiological species in sputum (17.4%) and urine (48.2%), and Acinetobacter spp. were the most common in blood culture (17.3%). After WLST determination, 70.5% of microbiological tests did not lead to a change in antibiotic use.

Many unnecessary microbiological tests are being performed in patients with WLST within 2 weeks of death. Microbiological testing should be performed carefully and in accordance with the patient’s treatment goals.

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.

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.

Firefighters are frequently exposed to stressful situations and are at high risk of developing post-traumatic stress disorder (PTSD). Hyperresponsiveness to threatening and emotional stimuli and diminishment of executive control have been suggested as manifestations of PTSD.

To examine brain activation in firefighters with PTSD by conducting an executive control-related behavioural task with trauma-related interferences.

Twelve firefighters with PTSD and 14 healthy firefighters underwent functional magnetic resonance imaging (fMRI) while performing a Stroop match-to-sample task using trauma-related photographic stimuli. Seed-based functional connectivity analysis was conducted using regions identified in fMRI contrast analysis.

Compared with the controls, the participants with PTSD had longer reaction times when the trauma-related interferences were presented. They showed significantly stronger brain activation to interfering trauma-related stimuli in the left insula, and had weaker insular functional connectivity in the supplementary motor area and the anterior cingulate cortex than the controls. They also showed a significant correlation between left insula–supplementary motor area connectivity strength and the hyperarousal subscale of the Clinician-Administered PTSD Scale.

Our findings indicate that trauma-related stimuli elicit excessive brain activation in the left insula among firefighters with PTSD. Firefighters with PTSD also appear to have weak left insular functional connectivity with executive control-related brain regions. This aberrant insular activation and functional connectivity could be related to the development and maintenance of PTSD symptoms in firefighters.

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.

To propose a new anthropometric index that can be employed to better predict percent body fat (PBF) among young adults and to compare with current anthropometric indices.

Cross-sectional.

All measurements were taken in a controlled laboratory setting in Seoul (South Korea), between 1 December 2015 and 30 June 2016.

Eighty-seven young adults (18–35 years) who underwent dual-energy x-ray absorptiometry (DXA) were used for analysis. Multiple regression analyses were conducted to develop a body fat index (BFI) using simple demographic and anthropometric information. Correlations of DXA measured PBF (DXA_PBF) with previously developed anthropometric indices and the BFI were analysed. Receiver operating characteristic curve analyses were conducted to compare the ability of anthropometric indices to identify obese individuals.

BFI showed a strong correlation with DXA_PBF (r = 0·84), which was higher than the correlations of DXA_PBF with the traditional (waist circumference, r = 0·49; waist to height ratio, r = 0·68; BMI, r = 0·36) and alternate anthropometric indices (a body shape index, r = 0·47; body roundness index, r = 0·68; body adiposity index, r = 0·70). Moreover, the BFI showed higher accuracy at identifying obese individuals (area under the curve (AUC) = 0·91), compared with the other anthropometric indices (AUC = 0·71–0·86).

The BFI can accurately predict DXA_PBF in young adults, using simple demographic and anthropometric information that are commonly available in research and clinical settings. However, larger representative studies are required to build on our findings.

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.

The aim of this study is to develop predictive models to predict organ at risk (OAR) complication level, classification of OAR dose-volume and combination of this function with our in-house developed treatment decision support system.

We analysed the support vector machine and decision tree algorithm for predicting OAR complication level and toxicity in order to integrate this function into our in-house radiation treatment planning decision support system. A total of 12 TomoTherapyTM treatment plans for prostate cancer were established, and a hundred modelled plans were generated to analyse the toxicity prediction for bladder and rectum.

The toxicity prediction algorithm analysis showed 91·0% accuracy in the training process. A scatter plot for bladder and rectum was obtained by 100 modelled plans and classification result derived. OAR complication level was analysed and risk factor for 25% bladder and 50% rectum was detected by decision tree. Therefore, it was shown that complication prediction of patients using big data-based clinical information is possible.

We verified the accuracy of the tested algorithm using prostate cancer cases. Side effects can be minimised by applying this predictive modelling algorithm with the planning decision support system for patient-specific radiotherapy planning.

The National Institute of Neurological Disease and Stroke-Canadian Stroke Network (NINDS-CSN) 5-minute neuropsychology protocol consists of only verbal tasks, and is proposed as a brief screening method for vascular cognitive impairment. We evaluated its feasibility within two weeks after stroke and ability to predict the development of post-stroke dementia (PSD) at 3 months after stroke.

We prospectively enrolled subjects with ischemic stroke within seven days of symptom onset who were consecutively admitted to 12 university hospitals. Neuropsychological assessments using the NINDS-CSN 5-minute and 60-minute neuropsychology protocols were administered within two weeks and at 3 months after stroke onset, respectively. PSD was diagnosed with reference to the American Heart Association/American Stroke Association statement, requiring deficits in at least two cognitive domains.

Of 620 patients, 512 (82.6%) were feasible for the NINDS-CSN 5-minute protocol within two weeks after stroke. The incidence of PSD was 16.2% in 308 subjects who had completed follow-up at 3 months after stroke onset. The total score of the NINDS-CSN 5-minute protocol differed significantly between those with and without PSD (4.0 ± 2.7, 7.4 ± 2.7, respectively; p < 0.01). A cut-off value of 6/7 showed reasonable discriminative power (sensitivity 0.82, specificity 0.67, AUC 0.74). The NINDS-CSN 5-minute protocol score was a significant predictor for PSD (adjusted odds ratio 6.32, 95% CI 2.65–15.05).

The NINDS-CSN 5-minute protocol is feasible to evaluate cognitive functions in patients with acute ischemic stroke. It might be a useful screening method for early identification of high-risk groups for PSD.

Devastating disasters around the world directly contribute to significant increases in human mortality and economic costs. The objective of this study was to examine the current state of the Korea Disaster Relief Team that participated in an international training module.

The whole training period was videotaped in order to observe and evaluate the respondents. The survey was carried out after completion of the 3-day training, and the scores were reported by use of a 5-point Likert scale.

A total of 43 respondents were interviewed for the survey, and the results showed that the overall preparedness score for international disasters was 3.4±1.6 (mean±SD). The awareness of the Incident Command System for international disasters was shown to be low (3.5±1.1). Higher scores were given to personnel who took on leadership roles in the team and who answered “I knew my duty” (4.4±0.6) in the survey, as well as to the training participants who answered “I clearly knew my duty” (4.5±0.5).

The preparedness level of the Korea Disaster Relief Team was shown to be insufficient, whereas understanding of the roles of leaders and training participants in the rescue team was found to be high. It is assumed that the preparedness level for disaster relief must be improved through continued training. (Disaster Med Public Health Preparedness. 2016;1–5)