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.

Background: Skin rejuvenation has become an increasingly popular noninvasive approach to address age-related changes such as sagging, wrinkles, and skin laxity. Energy-based devices (EBDs) and injectables are widely used, but their application requires careful customization based on individual patient characteristics to optimize outcomes and minimize potential adverse effects. Objective: This study aimed to explore clinical practice patterns among board-certified dermatologists in South Korea, focusing on their strategies for tailoring skin rejuvenation treatments to individual patients, including the integration of EBDs, injectables, and senotherapeutics. Methods: A structured survey comprising 10 questions was administered to 13 experienced dermatologists specializing in skin rejuvenation. The survey covered treatment strategies for patients with varying facial fat volumes, pain management approaches, and the use of EBDs, injectables and senotherapeutics. Results: High-intensity focused ultrasound (HIFU) and radiofrequency (RF) were the most employed EBDs, often combined with injectables for enhanced outcomes. For patients with higher facial fat, HIFU and deoxycholic acid injections were preferred for contouring and tightening. For those with lower facial fat, biostimulatory agents such as poly-D, L-lactic acid and microneedle RF were favored to restore volume and elasticity. Pain management strategies included topical anesthetics and stepwise protocols. Although less commonly used, senotherapeutics were occasionally prescribed for specific conditions, such as melasma and extensive photoaging. Conclusion Dermatologists in South Korea employ a variety of patient-specific strategies for skin rejuvenation, combining various EBDs, injectables, and senotherapeutics. These findings highlight the importance of personalized treatment protocols and the need for further research to optimize treatment efficacy and safety.

This report presents the latest statistics on the stroke population in South Korea, sourced from the Clinical Research Collaborations for Stroke in Korea-National Institute for Health (CRCS-K-NIH), a comprehensive, nationwide, multicenter stroke registry. The Korean cohort, unlike western populations, shows a male-to-female ratio of 1.5, attributed to lower risk factors in Korean women. The average ages for men and women are 67 and 73 years, respectively.Hypertension is the most common risk factor (67%), consistent with global trends, but there is a higher prevalence of diabetes (35%) and smoking (21%). The prevalence of atrial fibrillation (19%) is lower than in western populations, suggesting effective prevention strategies in the general population. A high incidence of large artery atherosclerosis (38%) is observed, likely due to prevalent intracranial arterial disease in East Asians and advanced imaging techniques.There has been a decrease in intravenous thrombolysis rates, from 12% in 2017–2019 to 10% in 2021, with no improvements in door-to-needle and door-to-puncture times, worsened by the coronavirus disease 2019 pandemic. While the use of aspirin plus clopidogrel for noncardioembolic stroke and direct oral anticoagulants for atrial fibrillation is well-established, the application of direct oral anticoagulants for non-atrial fibrillation cardioembolic strokes in the acute phase requires further research. The incidence of early neurological deterioration (13%) and the cumulative incidence of recurrent stroke at 3 months (3%) align with global figures. Favorable outcomes at 3 months (63%) are comparable internationally, yet the lack of improvement in dependency at 3 months highlights the need for advancements in acute stroke care.

Objectives: Presenteeism is known to be a much more economically damaging social cost than disease rest while going to work despite physical pain. Since COVID-19, social discussions on the sickness benefit have been taking place as a countermeasure against presenteeism, and in particular, farmers and fishermen do not have an institutional mechanism for livelihood support when a disease other than work occurs. This study attempted to examine the relationship between agricultural, fishing, and forestry workers and presenteeism using the 6th Korean Work Conditions Survey. Methods: From October 2020 to January 2021, data from the 6th working conditions survey conducted on 17 cities and provinces in Korea were used, and a total of 34,981 people were studied. Control variables were gender, age, self-health assessment, education level, night work, shift work, monthly income, occupation, working hours per week, and employment status. Results: As a result of the analysis, farmers and fishermen showed the characteristics of the self-employed and the elderly, and as a result of the regression analysis, when farmers and fishermen analyzed the relationship with presenteeism tendency compared to other industry workers, farmers and fishermen increased by 23% compared to other industry groups. Conclusion This study is significant in that it has representation by utilizing the 6th working conditions survey and objectively suggests the need for a sickness benefit for farmers and fishermen who may be overlooked in the sickness benefit.

Objectives: Presenteeism is known to be a much more economically damaging social cost than disease rest while going to work despite physical pain. Since COVID-19, social discussions on the sickness benefit have been taking place as a countermeasure against presenteeism, and in particular, farmers and fishermen do not have an institutional mechanism for livelihood support when a disease other than work occurs. This study attempted to examine the relationship between agricultural, fishing, and forestry workers and presenteeism using the 6th Korean Work Conditions Survey. Methods: From October 2020 to January 2021, data from the 6th working conditions survey conducted on 17 cities and provinces in Korea were used, and a total of 34,981 people were studied. Control variables were gender, age, self-health assessment, education level, night work, shift work, monthly income, occupation, working hours per week, and employment status. Results: As a result of the analysis, farmers and fishermen showed the characteristics of the self-employed and the elderly, and as a result of the regression analysis, when farmers and fishermen analyzed the relationship with presenteeism tendency compared to other industry workers, farmers and fishermen increased by 23% compared to other industry groups. Conclusion This study is significant in that it has representation by utilizing the 6th working conditions survey and objectively suggests the need for a sickness benefit for farmers and fishermen who may be overlooked in the sickness benefit.

Objectives: Presenteeism is known to be a much more economically damaging social cost than disease rest while going to work despite physical pain. Since COVID-19, social discussions on the sickness benefit have been taking place as a countermeasure against presenteeism, and in particular, farmers and fishermen do not have an institutional mechanism for livelihood support when a disease other than work occurs. This study attempted to examine the relationship between agricultural, fishing, and forestry workers and presenteeism using the 6th Korean Work Conditions Survey. Methods: From October 2020 to January 2021, data from the 6th working conditions survey conducted on 17 cities and provinces in Korea were used, and a total of 34,981 people were studied. Control variables were gender, age, self-health assessment, education level, night work, shift work, monthly income, occupation, working hours per week, and employment status. Results: As a result of the analysis, farmers and fishermen showed the characteristics of the self-employed and the elderly, and as a result of the regression analysis, when farmers and fishermen analyzed the relationship with presenteeism tendency compared to other industry workers, farmers and fishermen increased by 23% compared to other industry groups. Conclusion This study is significant in that it has representation by utilizing the 6th working conditions survey and objectively suggests the need for a sickness benefit for farmers and fishermen who may be overlooked in the sickness benefit.