Background: This study aimed to generate a Z score calculation model for coronary artery diameter of normal children and adolescents to be adopted as the standard calculation method with consensus in clinical practice. Methods: This study was a retrospective, multicenter study that collected data from multiple institutions across South Korea. Data were analyzed to determine the model that best fit the relationship between the diameter of coronary arteries and independent demographic parameters. Linear, power, logarithmic, exponential, and square root polynomial models were tested for best fit. Results: Data of 2,030 subjects were collected from 16 institutions. Separate calculation models for each sex were developed because the impact of demographic variables on the diameter of coronary arteries differs according to sex. The final model was the polynomial formula with an exponential relationship between the diameter of coronary arteries and body surface area using the DuBois formula. Conclusion A new coronary artery diameter Z score model was developed and is anticipated to be applicable in clinical practice. The new model will help establish a consensus-based Z score model.

Background: Korea recently established 70 emergency medical service areas. However, there are many concerns that medical resources for stroke could not be evenly distributed through the country. We aimed to compare the treatment quality and outcomes of acute stroke among the emergency medical service areas. Methods: This study analyzed the data of 28,800 patients admitted in 248 hospitals which participated in the 8th acute stroke quality assessment by Health Insurance Review and Assessment Service. Individual hospitals were regrouped into emergency service areas according to the address of the location. Assessment indicators and fatality were compared by the service areas. We defined the appropriate hospital by the performance of intravenous thrombolysis. Results: In seven service areas, there were no hospitals which received more than 10 stroke patients for 6 months. In nine service areas, there were no patients who underwent intravenous thrombolysis (IVT). Among 167 designated emergency medical centers, 50 hospitals (29.9%) responded that IVT was impossible 24 hours a day. There are 97 (39.1%) hospitals that meet the definitions of appropriate hospital. In 23 service areas (32.9%) had no appropriate or feasible hospitals. The fatality of service areas with stroke centers were 6.9% within 30 days and 15.6% within 1 year from stroke onset than those without stroke centers (7.7%, 16.9%, respectively). Conclusions There was a wide regional gap in the medical resource and the quality of treatments for acute stroke among emergency medical service areas in Korea. The poststroke fatality rate of the service areas which have stroke centers or appropriate hospitals were significantly low.

Background: There has been no comparison of the determinants of admission route between acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We examined whether factors associated with direct versus transferred-in admission to regional cardiocerebrovascular centers (RCVCs) differed between AIS and AMI. Methods: Using a nationwide RCVC registry, we identified consecutive patients presenting with AMI and AIS between July 2016 and December 2018. We explored factors associated with direct admission to RCVCs in patients with AIS and AMI and examined whether those associations differed between AIS and AMI, including interaction terms between each factor and disease type in multivariable models. To explore the influence of emergency medical service (EMS) paramedics on hospital selection, stratified analyses according to use of EMS were also performed. Results: Among the 17,897 and 8,927 AIS and AMI patients, 66.6% and 48.2% were directly admitted to RCVCs, respectively. Multivariable analysis showed that previous coronary heart disease, prehospital awareness, higher education level, and EMS use increased the odds of direct admission to RCVCs, but the odds ratio (OR) was different between AIS and AMI (for the first 3 factors, AMI > AIS; for EMS use, AMI < AIS). EMS use was the single most important factor for both AIS and AMI (OR, 4.72 vs. 3.90). Hypertension and hyperlipidemia increased, while living alone decreased the odds of direct admission only in AMI;additionally, age (65–74 years), previous stroke, and presentation during non-working hours increased the odds only in AIS. EMS use weakened the associations between direct admission and most factors in both AIS and AMI. Conclusions Various patient factors were differentially associated with direct admission to RCVCs between AIS and AMI. Public education for symptom awareness and use of EMS is essential in optimizing the transportation and hospitalization of patients with AMI and AIS.

Background: Tuberculous meningitis (TBM) is the most severe form of tuberculosis, but differentiating between the diagnosis of TBM and viral meningitis (VM) is difficult. Thus, we have developed machine-learning modules for differentiating TBM from VM.Material and Methods: For the training data, confirmed or probable TBM and confirmed VM cases were retrospectively collected from five teaching hospitals in Korea between January 2000 - July 2018. Various machine-learning algorithms were used for training. The machinelearning algorithms were tested by the leave-one-out cross-validation. Four residents and two infectious disease specialists were tested using the summarized medical information. Results: The training study comprised data from 60 patients with confirmed or probable TBM and 143 patients with confirmed VM. Older age, longer symptom duration before the visit, lower serum sodium, lower cerebrospinal fluid (CSF) glucose, higher CSF protein, and CSF adenosine deaminase were found in the TBM patients. Among the various machinelearning algorithms, the area under the curve (AUC) of the receiver operating characteristics of artificial neural network (ANN) with ImperativeImputer for matrix completion (0.85; 95% confidence interval 0.79 - 0.89) was found to be the highest. The AUC of the ANN model was statistically higher than those of all the residents (range 0.67 - 0.72, P <0.001) and an infectious disease specialist (AUC 0.76; P = 0.03). Conclusion The machine-learning techniques may play a role in differentiating between TBM and VM. Specifically, the ANN model seems to have better diagnostic performance than the non-expert clinician.

Purpose: Our previous work demonstrated that miRNA-495 targets SOX9 to inhibit chondrogenesis of mesenchymal stem cells.In this study, we aimed to investigate whether miRNA-495-mediated SOX9 regulation could be a novel therapeutic target for osteoarthritis (OA) using an in vitro cell culture model. Materials and Methods: An in vitro model mimicking the OA environment was established using TC28a2 normal human chondrocyte cells. Interleukin-1β (IL-1β, 10 ng/mL) was utilized to induce inflammation-related changes in TC28a2 cells. Safranin O staining and glycosaminoglycan assay were used to detect changes in proteoglycans among TC28a2 cells. Expression levels of COX-2, ADAMTS5, MMP13, SOX9, CCL4, and COL2A1 were examined by qRT-PCR and/or Western blotting. Immunohistochemistry was performed to detect SOX9 and CCL4 proteins in human cartilage tissues obtained from patients with OA. Results: miRNA-495 was upregulated in IL-1β-treated TC28a2 cells and chondrocytes from damaged cartilage tissues of patients with OA. Anti-miR-495 abolished the effect of IL-1β in TC28a2 cells and rescued the protein levels of SOX9 and COL2A1, which were reduced by IL-1β. SOX9 was downregulated in the damaged cartilage tissues of patients with OA, and knockdown of SOX9 abolished the effect of anti-miR-495 on IL-1β-treated TC28a2 cells. Conclusion We demonstrated that inhibition of miRNA-495 alleviates IL-1β-induced inflammatory responses in chondrocytes by rescuing SOX9 expression. Accordingly, miRNA-495 could be a potential novel target for OA therapy, and the application of anti-miR-495 to chondrocytes could be a therapeutic strategy for treating OA.

Purpose: Our previous work demonstrated that miRNA-495 targets SOX9 to inhibit chondrogenesis of mesenchymal stem cells.In this study, we aimed to investigate whether miRNA-495-mediated SOX9 regulation could be a novel therapeutic target for osteoarthritis (OA) using an in vitro cell culture model. Materials and Methods: An in vitro model mimicking the OA environment was established using TC28a2 normal human chondrocyte cells. Interleukin-1β (IL-1β, 10 ng/mL) was utilized to induce inflammation-related changes in TC28a2 cells. Safranin O staining and glycosaminoglycan assay were used to detect changes in proteoglycans among TC28a2 cells. Expression levels of COX-2, ADAMTS5, MMP13, SOX9, CCL4, and COL2A1 were examined by qRT-PCR and/or Western blotting. Immunohistochemistry was performed to detect SOX9 and CCL4 proteins in human cartilage tissues obtained from patients with OA. Results: miRNA-495 was upregulated in IL-1β-treated TC28a2 cells and chondrocytes from damaged cartilage tissues of patients with OA. Anti-miR-495 abolished the effect of IL-1β in TC28a2 cells and rescued the protein levels of SOX9 and COL2A1, which were reduced by IL-1β. SOX9 was downregulated in the damaged cartilage tissues of patients with OA, and knockdown of SOX9 abolished the effect of anti-miR-495 on IL-1β-treated TC28a2 cells. Conclusion We demonstrated that inhibition of miRNA-495 alleviates IL-1β-induced inflammatory responses in chondrocytes by rescuing SOX9 expression. Accordingly, miRNA-495 could be a potential novel target for OA therapy, and the application of anti-miR-495 to chondrocytes could be a therapeutic strategy for treating OA.

Background: Tuberculous meningitis (TBM) is the most severe form of tuberculosis, but differentiating between the diagnosis of TBM and viral meningitis (VM) is difficult. Thus, we have developed machine-learning modules for differentiating TBM from VM.Material and Methods: For the training data, confirmed or probable TBM and confirmed VM cases were retrospectively collected from five teaching hospitals in Korea between January 2000 - July 2018. Various machine-learning algorithms were used for training. The machinelearning algorithms were tested by the leave-one-out cross-validation. Four residents and two infectious disease specialists were tested using the summarized medical information. Results: The training study comprised data from 60 patients with confirmed or probable TBM and 143 patients with confirmed VM. Older age, longer symptom duration before the visit, lower serum sodium, lower cerebrospinal fluid (CSF) glucose, higher CSF protein, and CSF adenosine deaminase were found in the TBM patients. Among the various machinelearning algorithms, the area under the curve (AUC) of the receiver operating characteristics of artificial neural network (ANN) with ImperativeImputer for matrix completion (0.85; 95% confidence interval 0.79 - 0.89) was found to be the highest. The AUC of the ANN model was statistically higher than those of all the residents (range 0.67 - 0.72, P <0.001) and an infectious disease specialist (AUC 0.76; P = 0.03). Conclusion The machine-learning techniques may play a role in differentiating between TBM and VM. Specifically, the ANN model seems to have better diagnostic performance than the non-expert clinician.

Background: This study aimed to explore the time interval distribution pattern between the Physicians Order for Life-Sustaining Treatment (POLST) form completion and death at a tertiary hospital in South Korea. It also examined the association between various independent parameters and POLST form completion timing. Methods: A total of 150 critically ill patients admitted to Korea University Guro Hospital between June 1, 2018 and December 31, 2018 who completed the POLST form were retrospectively analyzed and included in this study. Data were analyzed with descriptive statistics, and group comparisons were performed using the chi-square test for categorical variables. Fisher’s exact test was also used to compare cancer versus non-cancer groups. Results: More than half the decedents (54.7%) completed their POLST within 15 days of death and 73.4% within 30 days. The non-cancer group had the highest percentage of patients (77.8%) who died within 15 days of POLST form completion while the colorectal (39.1%) and other cancer (37.5%) groups had the lowest (P=0.336). Conclusion Our findings demonstrated a current need for more explicit guidance to assist physicians with initiating more timely, proactive end-of-life discussions.

Objective: Overcrowding in the emergency department (ED) has been a long-standing global problem, but has yet to be resolved. This study was undertaken to investigate whether expansion of the ED can affect overcrowding. Methods: This was a retrospective study comparing two 10-month periods: before (September 2015 to June 2016) and after (September 2017 to June 2018) the ED expansion in an urban tertiary hospital. The ED expansion included expansion of the ambulatory area and establishment of a 25-bedded emergency ward dedicated to patients admitted through the ED. Results: Comparing the two study periods, we noted an increase in the number of patients visiting the ED, from 77,078 to 87,027. Moreover, the proportion of patients who returned home untreated significantly decreased from 11.5% to 0.9% (P<0.001). The number of adult patients increased from 40,814 to 60,720; in particular, the number of ambulatory patients increased from 18,648 to 42,944. Conversely, waiting time for X-ray and computed tomography increased (10.0 to 17.0 minutes, and 35.0 to 48.0 minutes, respectively). Other areas with increased time duration include median ED length of stay of total patients (193.0 minutes to 205.8 minutes), and time from consultation to admission decision (122.3 to 161.4 minutes). However, the boarding time decreased from 239.2 to 190.9 minutes. Conclusion The ED expansion allowed more patients to be treated, and the boarding time of admitted patients was reduced through operation of the emergency ward. However, due to increase in the number of visiting patients, the time required for medical treatment increased concurrently.