OBJECTIVES: This study analyzed the incidence and characteristics of in-hospital cardiac arrest (IHCA) in Korea based on a sample group of patients that is representative of the population. METHODS: The incidence of IHCA in adults was extracted from HIRA-NIS-2009, a sample of all patients using medical services in Korea. IHCA patients were analyzed according to gender, age, type of medical institute, and classification under the 6th revision of the Korean Standard Classification of Diseases (KCD-6). In addition, to assess the differences arising from the size of medical institutes, the IHCA incidence was analyzed in relation to the number of inpatient beds. RESULTS: Based on the sample data, the total incidence of IHCA in Korea was found to be 2.46 per 1,000 admissions (95% confidence interval [CI], 2.37–2.55). A higher incidence was found among men at 3.18 (95% CI, 3.03–3.33), compared to women at 1.84 (95% CI, 1.74–1.94). The incidence of IHCA was also higher in hospitals that had more than 600 inpatients beds at 5.40 (95% CI, 5.16–5.66) in comparison to those that had less than 600 inpatients beds at 4.09 (95% CI, 3.76–4.36) (p < 0.001). By primary disease, the incidence was the highest for infectious diseases. CONCLUSIONS: We demonstrated that the IHCA incidence based on gender, age, diagnostic group, and number of beds could be analyzed using the insurance claim data from a national representative sample.
Academies and Institutes ; Adult* ; Cardiopulmonary Resuscitation ; Classification ; Communicable Diseases ; Epidemiology ; Female ; Heart Arrest* ; Humans ; Incidence* ; Inpatients ; Insurance ; Korea* ; Male ; National Health Programs

The conventional radiologic method for liver segmentation is based on the position of the hepatic and portal veins. However, during surgery, liver segments are resected based on the distribution of hepatic portal blood flow. This discrepancy can lead to a number of problems, such as miscommunication among clinicians, missing the location of the segment with the hepatic mass, and the risk of extended hepatic resection. We suggest a novel method to determine hepatic segments based on portal blood flow, as in the surgical approach, but by using high and low mechanical indexes in contrast-enhanced ultrasonography with Sonazoid. This approach is helpful for preoperatively determining hepatic segments and reducing the risk of missing the location of a hepatic tumor or extended hepatic resection.

Background: Autoencoder (AE) is one of the deep learning techniques that uses an artificial neural network to reconstruct its input data in the output layer. We constructed a novel supervised AE model and tested its performance in the prediction of a co-existence of the disease of interest only using diagnostic codes. Methods: Diagnostic codes of one million randomly sampled patients listed in the Korean National Health Information Database in 2019 were used to train, validate, and test the prediction model. The first used AE solely for a feature engineering tool for an input of a classifier. Supervised Multi-Layer Perceptron (sMLP) was added to train a classifier to predict a binary level with latent representation as an input (AE + sMLP). The second model simultaneously updated the parameters in the AE and the connected MLP classifier during the learning process (End-to-End Supervised AE [EEsAE]). We tested the performances of these two models against baseline models, eXtreme Gradient Boosting (XGB) and naïve Bayes, in the prediction of co-existing gastric cancer diagnosis. Results: The proposed EEsAE model yielded the highest F1-score and highest area under the curve (0.86). The EEsAE and AE + sMLP gave the highest recalls. XGB yielded the highest precision. Ablation study revealed that iron deficiency anemia, gastroesophageal reflux disease, essential hypertension, gastric ulcers, benign prostate hyperplasia, and shoulder lesion were the top 6 most influential diagnoses on performance. Conclusion A novel EEsAE model showed promising performance in the prediction of a disease of interest.

Aortic interruption is a very rare disease that can be classified into congenital and acquired aortic interruption. Congenital aortic interruption generally implies an interruption of the aortic arch and no case of congenital abdominal aortic interruption has been reported. Acquired aortic interruption, on the other hand, can be caused by atherosclerosis, thrombosis, saddle embolism, and arteritis such as Takayasu arteritis. We experienced a case of congenital abdominal aortic interruption accompanied by one well-developed collateral flow presented with secondary hypertension in a 28-year-old female patient.
Adult ; Aorta, Abdominal ; Aorta, Thoracic ; Arteritis ; Atherosclerosis ; Embolism ; Female ; Hand ; Humans ; Hypertension* ; Rare Diseases ; Takayasu Arteritis ; Thrombosis

Background: Limited data are available on hepatitis C virus (HCV) infection in persons who inject drugs (PWID) in South Korea. The present study aimed to investigate the seroprevalence of HCV antibodies, risk factors for HCV seropositivity, and HCV treatment status in PWID between January 2012 and May 2022. Methods: We retrospectively reviewed the medical records of 418 drug users who underwent HCV antibody testing in three hospitals caring for 90% of known PWID in South Korea, of whom 373 were PWID. Results: The HCV seroprevalence was 39.7% (148/373) in PWID vs. 6.7% (3/45) in noninjection drug users (P < 0.001). Age ≥ 40 years, hospital type (58.2% in the prison hospital vs. 34.0% in the private hospital), and enrollment year (68.2% in 2012–2014 vs. 30.0% in 2021–2022) were independently associated with HCV seropositivity. Among the HCVseropositive PWID, 90.5% (134/148) were diagnosed with HCV infection; however, only 6.8% (10/148) received HCV treatment. The hepatitis B virus surface antigen and human immunodeficiency virus antibody positivity were 4.0% (14/352) and 1.9% (6/317) in tested PWID, respectively. Conclusion The HCV seroprevalence in PWID was 39.7% with a very low treatment rate, which prompts active measures to test and treat PWID for HCV infection in South Korea.

Background/Aims: Several prediction models for evaluating the prognosis of nonmetastatic resected pancreatic ductal adenocarcinoma (PDAC) have been developed, and their performances were reported to be superior to that of the 8th edition of the American Joint Committee on Cancer (AJCC) staging system. We developed a prediction model to evaluate the prognosis of resected PDAC and externally validated it with data from a nationwide Korean database. Methods: Data from the Surveillance, Epidemiology and End Results (SEER) database were utilized for model development, and data from the Korea Tumor Registry System-Biliary Pancreas (KOTUS-BP) database were used for external validation. Potential candidate variables for model development were age, sex, histologic differentiation, tumor location, adjuvant chemotherapy, and the AJCC 8th staging system T and N stages. For external validation, the concordance index (C-index) and time-dependent area under the receiver operating characteristic curve (AUC) were evaluated. Results: Between 2004 and 2016, data from 9,624 patients were utilized for model development, and data from 3,282 patients were used for external validation. In the multivariate Cox proportional hazard model, age, sex, tumor location, T and N stages, histologic differentiation, and adjuvant chemotherapy were independent prognostic factors for resected PDAC. After an exhaustive search and 10-fold cross validation, the best model was finally developed, which included all prognostic variables. The C-index, 1-year, 2-year, 3-year, and 5-year time-dependent AUCs were 0.628, 0.650, 0.665, 0.675, and 0.686, respectively. Conclusions The survival prediction model for resected PDAC could provide quantitative survival probabilities with reliable performance. External validation studies with other nationwide databases are needed to evaluate the performance of this model.

The development of drug-resistant influenza and new pathogenic virus strains underscores the need for antiviral therapeutics. Currently, neuraminidase (NA) inhibitors are commonly used antiviral drugs approved by the US Food and Drug Administration (FDA) for the prevention and treatment of influenza. Here, we show that vitisin B (VB) inhibits NA activity and suppresses H1N1 viral replication in MDCK and A549 cells. Reactive oxygen species (ROS), which frequently occur during viral infection, increase virus replication by activating the NF-κB signaling pathway, downmodulating glucose-6-phosphate dehydrogenase (G6PD) expression, and decreasing the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) antioxidant response activity. VB decreased virus-induced ROS generation by increasing G6PD expression and Nrf2 activity, and inhibiting NF-κB translocation to the nucleus through IKK dephosphorylation. In addition, VB reduced body weight loss, increased survival, decreased viral replication and the inflammatory response in the lungs of influenza A virus (IAV)-infected mice. Taken together, our results indicate that VB is a promising therapeutic candidate against IAV infection, complements existing drug limitations targeting viral NA. It modulated the intracellular ROS by G6PD, Nrf2 antioxidant response pathway, and NF-κB signaling pathway. These results demonstrate the feasibility of a multi-targeting drug strategy, providing new approaches for drug discovery against IAV infection.