Background: The coronavirus disease 2019 (COVID-19) pandemic has caused the death of thousands of patients worldwide. Although age is known to be a risk factor for morbidity and mortality in COVID-19 patients, critical illness or death is occurring even in the younger age group as the epidemic spreads. In early 2022, omicron became the dominant variant of the COVID-19 virus in South Korea, and the epidemic proceeded on a large scale. Accordingly, this study aimed to determine whether young adults (aged ≤ 50 years) with critical COVID-19 infection during the omicron period had different characteristics from older patients and to determine the risk factors for mortality in this specific age group. Methods: We evaluated 213 critical adult patients (high flow nasal cannula or higher respiratory support) hospitalized for polymerase chain reaction-confirmed COVID-19 in nine hospitals in South Korea between February 1, 2022 and April 30, 2022. Demographic characteristics, including body mass index (BMI) and vaccination status; underlying diseases; clinical features and laboratory findings; clinical course; treatment received; and outcomes were collected from electronic medical records (EMRs) and analyzed according to age and mortality. Results: Overall, 71 critically ill patients aged ≤ 50 years were enrolled, and 142 critically ill patients aged over 50 years were selected through 1:2 matching based on the date of diagnosis. The most frequent underlying diseases among those aged ≤ 50 years were diabetes and hypertension, and all 14 patients who died had either a BMI ≥ 25 kg/m 2 or an underlying disease. The total case fatality rate among severe patients (S-CFR) was 31.0%, and the S-CFR differed according to age and was higher than that during the delta period. The S-CFR was 19.7% for those aged ≤ 50 years, 36.6% for those aged > 50 years, and 38.1% for those aged ≥ 65 years. In multivariate analysis, age (odds ratio [OR], 1.084; 95% confidence interval [CI], 1.043–1.127), initial low-density lipoprotein > 600 IU/L (OR, 4.782; 95% CI, 1.584–14.434), initial C-reactive protein > 8 mg/dL (OR, 2.940; 95% CI, 1.042–8.293), highest aspartate aminotransferase > 200 IU/L (OR, 12.931; 95% CI, 1.691–98.908), and mechanical ventilation implementation (OR, 3.671; 95% CI, 1.294–10.420) were significant independent predictors of mortality in critical COVID-19 patients during the omicron wave. A similar pattern was shown when analyzing the data by age group, but most had no statistical significance owing to the small number of deaths in the young critical group. Although the vaccination completion rate of all the patients (31.0%) was higher than that in the delta wave period (13.6%), it was still lower than that of the general population. Further, only 15 (21.1%) critically ill patients aged ≤ 50 years were fully vaccinated. Overall, the severity of hospitalized critical patients was significantly higher than that in the delta period, indicating that it was difficult to find common risk factors in the two periods only with a simple comparison. Conclusion Overall, the S-CFR of critically ill COVID-19 patients in the omicron period was higher than that in the delta period, especially in those aged ≤ 50 years. All of the patients who died had an underlying disease or obesity. In the same population, the vaccination rate was very low compared to that in the delta wave, indicating that non-vaccination significantly affected the progression to critical illness. Notably, there was a lack of prescription for Paxlovid for these patients although they satisfied the prescription criteria. Early diagnosis and active initial treatment was necessary, along with the proven methods of vaccination and personal hygiene. Further studies are needed to determine how each variant affects critically ill patients.

Background: It is necessary to develop a roadmap for antimicrobial usage monitoring in order to perform monitoring of antimicrobial use at the national level properly. Therefore, this study aimed to develop a roadmap for establishing surveillance and monitoring of antimicrobial use in medical institutions at the national level. Materials and Methods: A modified Delphi study was conducted, including 3 rounds of an online survey and a virtual meeting with 16 expert panels. The survey items were developed based on a literature review of the surveillance systems for antimicrobial use in 12 countries and interviews with experts. The questionnaire was designed to include both the surveillance and benchmarking systems. Results: Regarding the scope of target institutions to be included in the surveillance system, medical institutions for sentinel surveillance had the highest proportion of agreement among the panels (75.0%, 9/12). For the benchmarking system, “tertiary- and secondarycare hospitals” were accepted as the scope of target institutions at the current moment.Furthermore, the National Health Insurance claims and prescription data of individual hospitals were considered appropriate data sources for the surveillance system. As for the measures to promote the participation of hospitals in the benchmarking system, “compensation through the establishment of antimicrobial management fees” and “set the participation in the program as a quality evaluation or accreditation index for hospital evaluation” were accepted. Conclusion This study provides a roadmap for establishing an antimicrobial use monitoring and benchmarking system for medical institutions at a national level in Korea.

Background: The Korea National Antimicrobial Use Analysis System (KONAS), a benchmarking system for antimicrobial use in hospitals, provides Korean Standardized Antimicrobial Administration Ratio (K-SAAR) for benchmarking. This article describes K-SAAR predictive models to enhance the understanding of K-SAAR, an important benchmarking strategy for antimicrobial usage in KONAS. Methods: We obtained medical insurance claims data for all hospitalized patients aged ≥ 28 days in all secondary and tertiary care hospitals in South Korea (n = 347) from January 2019 to December 2019 from the Health Insurance Review & Assessment Service. Modeling was performed to derive a prediction value for antimicrobial use in each institution, which corresponded to the denominator value for calculating K-SAAR. The prediction values of antimicrobial use were modeled separately for each category, for all inpatients and adult patients (aged ≥ 15 years), using stepwise negative binomial regression. Results: The final models for each antimicrobial category were adjusted for different significant risk factors. In the K-SAAR models of all aged patients as well as adult patients, most antimicrobial categories included the number of hospital beds and the number of operations as significant factors, while some antimicrobial categories included mean age for inpatients, hospital type, and the number of patients transferred from other hospitals as significant factors. Conclusion We developed a model to predict antimicrobial use rates in Korean hospitals, and the model was used as the denominator of the K-SAAR.

Carbapenemase-producing Enterobacteriaceae (CPE) is an important and increasing threat to global health. From July to September 2017, 20 inpatients at a tertiary care hospital in Korea were either colonized or infected with carbapenem-resistant Escherichia coli strains. All of E. coli isolates co-produced bla(NDM-5) and bla(OXA-181) carbapenemase genes and shared ≥88% clonal relatedness on the basis of a cladistic calculation of the distribution of pulsed-field gel electrophoresis patterns. Rapid detection of CPE is one of the most important factors to prevent CPE dissemination because it takes long time for CPE to become negative.

BACKGROUND: Liver fibrosis evaluation is an important issue in chronic liver disease patients. We aimed to develop noninvasive liver fibrosis biomarkers based on transient elastography (TE, FibroScan®) through retrospective review of clinicopathological data. METHODS: We recruited 278 chronic hepatitis B patients who underwent Fibroscan and HBV DNA testing. A total of 115 HBeAg-positive and 159 HBeAg-negative chronic hepatitis B patients were analyzed. A total of 100 hepatitis C patients were analyzed. Successful fibroscan data, gamma-glutamyl transferase (GGT) to platelet ratio (GPR), platelet count, AST, ALT, international normalized ratio of prothrombin time, total cholesterol, triglycerides, bilirubin, mean platelet volume, AST to platelet ratio index, fibrosis index based on four factors (FIB-4), neutrophil to lymphocyte ratio (NLR), and NLR to platelet ratio were analyzed to determine the new noninvasive markers for assessing liver fibrosis. RESULTS: Elevated GPR (OR=9.1, P=0.011) and FIB-4 (OR=2.3, P=0.01) were associated with greater risk of liver fibrosis in chronic hepatitis B patients. FIB-4 (OR=6.04, P=0.005) was a risk factor for liver fibrosis in HBeAg-positive patients. FIB-4 (OR=2.371, P=0.015) and GPR (OR=33.78, P=0.003) were liver fibrosis risk factor in HBeAg-negative patients. In chronic hepatitis C patients, GGT (OR=1.033, P=0.002), triglyceride (OR=−0.990, P=0.038) and FIB-4 (OR=3.499, P=0.006) showed statistical significances. The AUCs were 0.816 in FIB-4 (P<0.001) and 0.849 in GPR (P<0.001). CONCLUSIONS: FIB-4 and GPR may be useful blood markers for assessing liver fibrosis in chronic hepatitis B and hepatitis C patients. Further well-designed prospective study is required to validate these noninvasive blood markers in clinical practice.
Area Under Curve ; Bilirubin ; Biomarkers ; Blood Platelets ; Cholesterol ; DNA ; Elasticity Imaging Techniques ; Fibrosis ; Hepatitis B ; Hepatitis B, Chronic ; Hepatitis C ; Hepatitis C, Chronic ; Hepatitis ; Hepatitis, Chronic ; Humans ; International Normalized Ratio ; Liver Cirrhosis ; Liver Diseases ; Liver ; Lymphocytes ; Mean Platelet Volume ; Neutrophils ; Platelet Count ; Prospective Studies ; Prothrombin Time ; Retrospective Studies ; Risk Factors ; Transferases ; Triglycerides

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious zoonosis caused by the SFTS virus. Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening syndrome associated with excessive immune activation. Cytokine storms are often seen in both SFTS and HLH, resulting in rapid disease progression and poor prognosis. The aim of this study was to identify whether SFTS cases complicated by HLH are related to higher rates of mortality. Descriptive analysis of the frequency of clinical and laboratory data, complications, treatment outcomes, and HLH-2004 criteria was performed. Cases presenting with five or more clinical or laboratory findings corresponding to the HLH-2004 diagnostic criteria were defined as SFTS cases complicated by HLH. Eighteen cases of SFTS were identified during a 2-year study period, with a case-fatality proportion of 22.2% (4 among 18 cases, 95% confidence interval 9%–45.2%). SFTS cases complicated by HLH were identified in 33.3% (6 among 18 cases). A mortality rate of 75% (3 among 4 cases) was recorded among SFTS cases complicated by HLH. Although there were no statistically significant differences in outcomes, fatal cases exhibited more frequent correlation with HLH-2004 criteria than non-fatal cases [3/14 (21.4%) vs. 3/4 (75%), p=0.083]. In conclusion, the present study suggests the possibility that SFTS cases complicated by HLH are at higher risk of poor prognosis.
Disease Progression ; Fatal Outcome ; Fever ; Lymphohistiocytosis, Hemophagocytic ; Mortality ; Prognosis ; Thrombocytopenia

No abstract available.
Bacteremia* ; Korea* ; Pasteurella multocida* ; Pasteurella*

BACKGROUND: Hemolytic specimens contain components that interfere with clinical laboratory results. We evaluated previously published hemolysis indices (HI) and developed an algorithm for differentiating between mechanical hemolysis and immune-mediated hemolysis based on complete blood count (CBC). METHODS: Sixty-three residual EDTA (ethylenediamine tetraacetic acid)-anticoagulated blood specimens were obtained during regular health check-ups, and each specimen was divided into 3 aliquots (A control, B, and C group). Aliquots B and C were mechanically hemolysed by 2 and 5 aspirations, respectively, using a 25-gauge needle before testing; aliquot A was analysed immediately without hemolysis. Additionally, we collected 36 specimens from patients suspected of having immune-mediated hemolysis after thorough reviewing their various laboratory results including direct antiglobulin test. We compared CBC parameters between the groups (A, B, C, D [B+C], and E [immune-mediated hemolysis group]). RESULTS: Our HI scoring system using the sum of red blood cell ghosts, measured hemoglobin-calculated hemoglobin, mean corpuscular hemoglobin concentration-corpuscular hemoglobin concentration mean, and mean platelet volume rather than mean corpuscular hemoglobin, effectively identified mechanical hemolysis; the results were similar to those of previous studies. Furthermore, the HI score using the sum of mean corpuscular volume, red cell distribution width, hemoglobin distribution width, polymorphonuclear %, and neutrophil % differentiated mechanical hemolysis from immune-mediated hemolysis (cut-off, 9; sensitivity, 91.7%; specificity, 92.9%; area under the receiver operating characteristic curve, 0.965 [95% confidence interval, 0.924–0.988]). CONCLUSIONS: The newly developed algorithm may provide effective screening for detecting hemolysis and differential diagnosis of mechanical hemolysis and immune-mediated hemolysis based on CBC results.
Aspirations (Psychology) ; Blood Cell Count ; Coombs Test ; Diagnosis, Differential* ; Edetic Acid ; Erythrocyte Indices ; Erythrocytes ; Hemolysis* ; Humans ; In Vitro Techniques* ; Mass Screening ; Mean Platelet Volume ; Needles ; Neutrophils ; ROC Curve ; Sensitivity and Specificity

BACKGROUND: Liver biopsy is the gold standard for assessing liver fibrosis; however, it has a relatively high risk of resulting in complications. Although a non-invasive method (i.e., transient elastography—fibroscan) was introduced, it is expensive and is dependent on the patient's status. Thus, the FIB-4 score, a non-invasive formula, has been used to predict the degree of liver fibrosis. The aim of this study was to evaluate the usefulness of the FIB-4 score in predicting stages of liver fibrosis. METHODS: We analysed the age, diagnosis, and liver stiffness of 282 patients by measuring the levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) as well as their platelet count. Liver elasticity was evaluated by two classification criteria (Foucher et al. and Mueller et al.). The FIB-4 score was calculated using the formula: age×AST/(platelet count×ALT½). The cut-off value of the FIB-4 score was determined according to the area under the relative operating characteristic curve (AUC) based on liver elasticity. RESULTS: The FIB-4 cut-off values, as determined using two different criteria, have the highest AUC, thereby indicating a robust ability to distinguish between healthy liver tissue and the presence of any liver fibrosis. The FIB-4 score with a cut-off value of 2.07, as determined by Mueller et al., had the highest AUC (0.837) and odds ratio (2.741) with a sensitivity of 78.3% and a specificity of 76.5%. CONCLUSIONS: An FIB-4 score of 2.07 is a cut-off value that is useful in detecting fibrotic progression in chronic liver disease in our laboratory. Each laboratory should determine an appropriate FIB-4 cut-off value that is relative to the particular characteristics of their patient population.
Alanine Transaminase ; Area Under Curve ; Aspartate Aminotransferases ; Biopsy ; Classification ; Diagnosis ; Elasticity ; Humans ; Liver Cirrhosis* ; Liver Diseases ; Liver* ; Mass Screening* ; Methods ; Odds Ratio ; Platelet Count ; Sensitivity and Specificity

Streptococcus bovis bacteremia in humans has been traditionally associated with infective endocarditis, colorectal cancer, and liver cirrhosis. S. bovis strains were previously categorized by biotype, but since the 2000s, they have been reclassified by DNA homology. We report a case of S. gallolyticus subsp. gallolyticus bacteremia, identified by 16S rRNA sequencing, in a patient diagnosed with liver cirrhosis. A 61-yr-old man with a history of liver cirrhosis presented to the hospital with a complaint of fever. Blood culture revealed the presence of gram-positive cocci, and the isolated organism was identified as S. bovis by the MicroScan identification kit (Beckman Coulter, USA), but as Enterococcus saccharolyticus by the Vitek 2 identification kit (bioMérieux, USA). The organism was finally confirmed as S. gallolyticus subsp. gallolyticus by 16S rRNA sequencing.
Bacteremia* ; Colorectal Neoplasms ; DNA ; Endocarditis ; Enterococcus ; Fever ; Gram-Positive Cocci ; Humans ; Liver Cirrhosis* ; Liver* ; Streptococcus bovis ; Streptococcus*