Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This phenomenological study aimed to comprehend the altered parenting experience of nurses during the coronavirus disease 2019 (COVID-19) pandemic.Method: Using a qualitative approach, the research design employed a phenomenological methodology. The participants were 6 nurses with elementary school-aged children. The nurses were employed in tertiary general hospitals, working on rotating shifts during the COVID-19 pandemic. In-depth interviews were conducted to collect individual data, which were then analyzed using Colaizzi phenomenological method. Results: Analyzing the collected data led to 178 significant results, from which 13 themes were derived. These 13 themes were further integrated into 5 distinct theme clusters: (1) struggling as a nurse-mom, (2) providing a supportive presence, (3) facing challenges in facilitating children's learning activities, (4) navigating parental roles in a chaotic situation, and (5) pursuing physical safety. These clusters were subsequently categorized into four overarching categories: “suffering,” which encompassed the themes of pressure of infection and providing a supportive presence, as well as “controlling,” “parenting,” and “seeking,” representing the remaining clusters, respectively. Conclusion The parenting experiences of shift nurses during the COVID-19 pandemic encompassed various aspects, including the challenges posed by the pressure of infection, the importance of providing a supportive presence, difficulties in managing children’s learning activities, navigating parental roles amid chaotic circumstances, and the pursuit of physical safety. These experiences significantly impact the stability of shift nurses’ caregiving abilities for both their patients and their children. Therefore, it is crucial to establish a comprehensive nationallevel care support system in times of disaster situations like the COVID-19 pandemic.

Gastric cancer is one of the most common cancers in Korea and the world. Since 2004, this is the 4th gastric cancer guideline published in Korea which is the revised version of previous evidence-based approach in 2018. Current guideline is a collaborative work of the interdisciplinary working group including experts in the field of gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology and guideline development methodology. Total of 33 key questions were updated or proposed after a collaborative review by the working group and 40 statements were developed according to the systematic review using the MEDLINE, Embase, Cochrane Library and KoreaMed database. The level of evidence and the grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation proposition. Evidence level, benefit, harm, and clinical applicability was considered as the significant factors for recommendation. The working group reviewed recommendations and discussed for consensus. In the earlier part, general consideration discusses screening, diagnosis and staging of endoscopy, pathology, radiology, and nuclear medicine. Flowchart is depicted with statements which is supported by meta-analysis and references. Since clinical trial and systematic review was not suitable for postoperative oncologic and nutritional follow-up, working group agreed to conduct a nationwide survey investigating the clinical practice of all tertiary or general hospitals in Korea. The purpose of this survey was to provide baseline information on follow up. Herein we present a multidisciplinary-evidence based gastric cancer guideline.

Background/Aims: The prospective Crohn’s Disease Clinical Network and Cohort Study is a nationwide multicenter cohort study of patients with Crohn’s disease (CD) in Korea, aiming to prospectively investigate the clinical features and long-term prognosis associated with CD. Methods: Patients diagnosed with CD between January 2009 and September 2019 were prospectively enrolled. They were divided into two cohorts according to the year of diagnosis: cohort 1 (diagnosed between 2009 and 2011) versus cohort 2 (between 2012 and 2019). Results: A total of 1,175 patients were included, and the median follow-up duration was 68 months (interquartile range, 39.0 to 91.0 months). The treatment-free durations for thiopurines (p<0.001) and anti-tumor necrosis factor agents (p=0.018) of cohort 2 were shorter than those of cohort 1. Among 887 patients with B1 behavior at diagnosis, 149 patients (16.8%) progressed to either B2 or B3 behavior during follow-up. Early use of thiopurine was associated with a reduced risk of behavioral progression (adjusted hazard ratio [aHR], 0.69; 95% confidence interval [CI], 0.50 to 0.90), and family history of inflammatory bowel disease was associated with an increased risk of behavioral progression (aHR, 2.29; 95% CI, 1.16 to 4.50). One hundred forty-one patients (12.0%) underwent intestinal resection, and the intestinal resection-free survival time was significantly longer in cohort 2 than in cohort 1 (p=0.003). The early use of thiopurines (aHR, 0.35;95% CI, 0.23 to 0.51) was independently associated with a reduced risk of intestinal resection. Conclusions The prognosis of CD in Korea appears to have improved over time, as evidenced by the decreasing intestinal resection rate. Early use of thiopurines was associated with an improved prognosis represented by a reduced risk of intestinal resection.

Objectives: The aim of this study was to examine the antibacterial effect of mastic oil on a representative caries-inducing bacterium, Streptococcus mutans. Methods: S. mutans UA159 was maintained in a BHI medium containing 0.1% sugar at 37℃ and 10% CO2 . Strains were treated with six different concentrations of mastic oil (0, 0.1, 0.2, 0.3, 0.4, 0.5%). After incubation for 16 h, the antibacterial effect was evaluated by measuring the optical density (OD) and observing the colony-forming unit. A microtiter plate assay was performed to analyze the anti-adhesion ability of mastic oil on S. mutans. Results: More than 0.1% of mastic oil inhibited the growth of S. mutans. In addition, 0.4% mastic oil exterminated S. mutans. Mastic oil induced an anti-adhesive ability in S. mutans. Conclusions These results suggest that mastic oil may be used as a preventive measure against dental caries.