Despite the accuracy of nucleic acid amplification tests (NAATs), rapid antigen tests (RATs) for severe acute respiratory syndrome coronavirus-2 are widely used as point-of-care tests. A total of 282 pairs of reverse transcription-polymerase chain reaction and Standard Q COVID-19 Ag tests were serially conducted for 68 patients every 3–4 days until their discharge. Through a field evaluation of RATs using direct nasopharyngeal swabs, the sensitivities were 84.6% and 87.3% for E and RNA-dependent RNA polymerase (RdRp) genes, respectively, for specimens with cycle thresholds (Cts) < 25. The Ct values of E and RdRp genes for 95% detection rates by RATs were 16.9 and 18.1, respectively. The sensitivity of RAT was 48.4% after the onset of symptoms, which was not sufficient. RAT positivity gradually decreased with increased time after symptom onset and had continuously lower sensitivity than NAATs.

Background: Alcohol consumption has been considered as a modifiable risk factor for dementia development and alcohol-related brain damage may further impair cognitive abilities in dementia patients. This study aimed to find out the differences in cognitive function according to current alcohol drinking in patients with self-perceived memory decline, including subjective cognitive decline (SCD), mild cognitive impairment (MCI) and early Alzheimer-type dementia (ATD). Methods: From May 2018 to December 2019, retrospective chart review was performed in patients who visited CHA Bundang Medical Center for cognitive decline. A two-way analysis of variance with interaction test were used to analyze the impact of alcohol consumption on cognitive function between groups. Results: A total of 147 patients was classified into three groups of SCD (n=30), MCI (n=53), and ATD (n=64), and each group was divided into two subgroups of alcohol users and alcohol non-users, according to the current status of alcohol consumption. Between SCD, MCI and ATD groups, scores of clock drawing test and Go/No-go test were significantly lower in current alcohol users of ATD groups compared to the SCD and MCI groups (p<0.05). Conclusions These results suggest that current alcohol consumption has detrimental effects especially on the frontal/executive function in early ATD patients. Considering the association between frontal/executive function and ADL, our finding suggests that cessation of alcohol intake may be a therapeutic strategy to prevent ADL deterioration in patients with ATD.

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: Multidrug-resistant Acinetobacter baumannii (MDRAB) is widespread among intensive care units worldwide, posing a threat to patients and the health system. We describe the successful management of a MDRAB outbreak by implementing an infection-control strategy in a pediatric intensive care unit (PICU). Methods: This retrospective study investigated the patients admitted to the PICU in periods 1 (8 months) and 2 (7 months), from the index MDRAB case to intervention implementation, and from intervention implementation to cessation of MDRAB spread. An infection-control strategy was designed following six concepts: 1) cohort isolation of colonized patients, 2) enforcement of hand hygiene, 3) universal contact precautions, 4) environmental management, 5) periodic surveillance culture study, and 6) monitoring and feedback. Results: Of the 427 patients, 29 were confirmed to have MDRAB colonization, of which 18 had MDRAB infections. Overall incidence per 1,000 patient days decreased from 7.8 (period 1) to 5.8 (period 2). The MDRAB outbreak was declared terminated after the 6-month followup following period 2. MDRAB was detected on the computer keyboard and in condensed water inside the ventilator circuits. The rate of hand hygiene performance was the lowest in the three months before and after index case admission and increased from 84% (period 1) to 95% (period 2). Patients with higher severity, indicated by a higher Pediatric Risk of Mortality III score, were more likely to develop colonization (P = 0.030), because they had invasive devices and required more contact with healthcare workers. MDRAB colonization contributed to an increase in the duration of mechanical ventilation and PICU stay (P < 0.001), but did not affect mortality (P = 0.273). Conclusion The MDRAB outbreak was successfully terminated by the implementation of a comprehensive infection-control strategy focused on the promotion of hand hygiene, universal contact precautions, and environmental management through multidisciplinary teamwork.

Optimized management of atrial fibrillation requires patient-oriented decision making with a multidisciplinary approach. This report incorporates recent authoritative studies to provide detailed recommendations for managing atrial fibrillation in specific clinical settings. The principles of the Atrial fibrillation Better Care (ABC) pathway apply in these clinical settings. In addition, specific considerations are discussed for each of these conditions and populations.

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: and Purpose: Blood pressure (BP) control is strongly recommended, but BP control rate has not been well studied in patients with stroke. We evaluated the BP control rate with fimasartan-based antihypertensive therapy initiated in patients with recent cerebral ischemia. Methods: This multicenter, prospective, single-arm trial involved 27 centers in South Korea. Key inclusion criteria were recent cerebral ischemia within 90 days and high BP [systolic blood pressure (SBP) >140 mm Hg or diastolic blood pressure (DBP) >90 mm Hg]. BP lowering was initiated with fimasartan. BP management during the follow-up was at the discretion of the responsible investigators. The primary endpoint was the target BP goal achievement rate (<140/90 mm Hg) at 24 weeks. Key secondary endpoints included achieved BP and BP changes at each visit, and clinical events (ClinicalTrials.gov Identifier: NCT03231293). Results: Of 1,035 patients enrolled, 1,026 were included in the safety analysis, and 951 in the efficacy analysis. Their mean age was 64.1 years, 33% were female, the median time interval from onset to enrollment was 10 days, and the baseline SBP and DBP were 162.3±16.0 and 92.2±12.4 mm Hg (mean±SD). During the study period, 55.5% of patients were maintained on fimasartan monotherapy, and 44.5% received antihypertensive therapies other than fimasartan monotherapy at at least one visit. The target BP goal achievement rate at 24-week was 67.3% (48.6% at 4-week and 61.4% at 12-week). The mean BP was 139.0/81.8±18.3/11.7, 133.8/79.2±16.4/11.0, and 132.8/78.5±15.6/10.9 mm Hg at 4-, 12-, and 24-week. The treatment-emergent adverse event rate was 5.4%, including one serious adverse event. Conclusions Fimasartan-based BP lowering achieved the target BP in two-thirds of patients at 24 weeks, and was generally well tolerated.

Purpose: This study was conducted to investigate the nursing needs and workload of nurses according to nursing dependency for effective placement of nursing staff in the emergency department (ED). Methods: In June 2020, 256 adult patients who visited the ED were classified as two groups, suspected COVID-19 patients and general patients. The participants’electronic medical records were analyzed using descriptive statistics, t-test, x 2 -test, and Fisher's exact test using the SPSS. Results: The patient dependence score showed a significant difference between the two groups, with an average of 13.99±1.85 for the suspected COVID-19 patient group and 10.58±2.10 for the general patient group (t=12.42, p<.001). There were statistically significant differences in communication (t=3.28, p=.001), mobility (t=3.29, p=.001), nutrition, elimination, and personal care (t=7.34, p<.001) among the six domains of nursing dependency. In the domains of environment, safety, health, and social needs, the dependency score was 3 for all suspected COVID-19 patients and 1 for all general patients. Conclusion The results of this study confirmed that infection control activities of emergency patients who need isolation affect the patients’ nursing dependency on nursing care.

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.