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.

Little is known about the transgenerational effects of maternal exposure to fine particulate matter (PM2.5) on offspring kidney health. This study investigated the effect of maternal administration of PM2.5 or PM2.5 with vitamin D during pregnancy and lactation on renal injury in rat dams and their offspring. Methods: Nine pregnant Sprague-Dawley rats received oral administration of normal saline, airborne PM2.5, or PM2.5 with vitamin D from gestational day 11 to postpartum day 21. Kidneys of rat dams (n = 3 for each group) and their male offspring (n = 5 for each group) were taken for analysis on postpartum or postnatal day 21. Results: Maternal PM2.5 exposure increased glomerular damage, tubulointerstitial injury, and cortical macrophage infiltration in both dams and pups; all increases were attenuated by vitamin D administration. In dam kidneys, PM2.5 increased the protein expression of vitamin D receptor (VDR), klotho, and tumor necrosis factor-α; vitamin D lessened these changes. The expressions of renin, nuclear factor erythroid 2-related factor 2 (Nrf2), and nuclear factor-kappa B (NF-κB) p50 decreased in rat dams exposed to PM2.5. In offspring kidneys, exposure to maternal PM2.5 reduced the expression of VDR, renin, angiotensin-converting enzyme (ACE), Nrf2, and NF-κB p50, but increased cytochrome P450 24A1 expression. Maternal vitamin D administration with PM2.5 enhanced VDR, ACE, and NF-κB p50 activities in pup kidneys. Conclusion: PM2.5 exposure during nephrogenesis may exert transgenerational renal impairment, and maternal vitamin D intake could attenuate PM2.5-induced kidney damage in mothers and their offspring.

Little is known about the transgenerational effects of maternal exposure to fine particulate matter (PM2.5) on offspring kidney health. This study investigated the effect of maternal administration of PM2.5 or PM2.5 with vitamin D during pregnancy and lactation on renal injury in rat dams and their offspring. Methods: Nine pregnant Sprague-Dawley rats received oral administration of normal saline, airborne PM2.5, or PM2.5 with vitamin D from gestational day 11 to postpartum day 21. Kidneys of rat dams (n = 3 for each group) and their male offspring (n = 5 for each group) were taken for analysis on postpartum or postnatal day 21. Results: Maternal PM2.5 exposure increased glomerular damage, tubulointerstitial injury, and cortical macrophage infiltration in both dams and pups; all increases were attenuated by vitamin D administration. In dam kidneys, PM2.5 increased the protein expression of vitamin D receptor (VDR), klotho, and tumor necrosis factor-α; vitamin D lessened these changes. The expressions of renin, nuclear factor erythroid 2-related factor 2 (Nrf2), and nuclear factor-kappa B (NF-κB) p50 decreased in rat dams exposed to PM2.5. In offspring kidneys, exposure to maternal PM2.5 reduced the expression of VDR, renin, angiotensin-converting enzyme (ACE), Nrf2, and NF-κB p50, but increased cytochrome P450 24A1 expression. Maternal vitamin D administration with PM2.5 enhanced VDR, ACE, and NF-κB p50 activities in pup kidneys. Conclusion: PM2.5 exposure during nephrogenesis may exert transgenerational renal impairment, and maternal vitamin D intake could attenuate PM2.5-induced kidney damage in mothers and their offspring.

Little is known about the transgenerational effects of maternal exposure to fine particulate matter (PM2.5) on offspring kidney health. This study investigated the effect of maternal administration of PM2.5 or PM2.5 with vitamin D during pregnancy and lactation on renal injury in rat dams and their offspring. Methods: Nine pregnant Sprague-Dawley rats received oral administration of normal saline, airborne PM2.5, or PM2.5 with vitamin D from gestational day 11 to postpartum day 21. Kidneys of rat dams (n = 3 for each group) and their male offspring (n = 5 for each group) were taken for analysis on postpartum or postnatal day 21. Results: Maternal PM2.5 exposure increased glomerular damage, tubulointerstitial injury, and cortical macrophage infiltration in both dams and pups; all increases were attenuated by vitamin D administration. In dam kidneys, PM2.5 increased the protein expression of vitamin D receptor (VDR), klotho, and tumor necrosis factor-α; vitamin D lessened these changes. The expressions of renin, nuclear factor erythroid 2-related factor 2 (Nrf2), and nuclear factor-kappa B (NF-κB) p50 decreased in rat dams exposed to PM2.5. In offspring kidneys, exposure to maternal PM2.5 reduced the expression of VDR, renin, angiotensin-converting enzyme (ACE), Nrf2, and NF-κB p50, but increased cytochrome P450 24A1 expression. Maternal vitamin D administration with PM2.5 enhanced VDR, ACE, and NF-κB p50 activities in pup kidneys. Conclusion: PM2.5 exposure during nephrogenesis may exert transgenerational renal impairment, and maternal vitamin D intake could attenuate PM2.5-induced kidney damage in mothers and their offspring.

Little is known about the transgenerational effects of maternal exposure to fine particulate matter (PM2.5) on offspring kidney health. This study investigated the effect of maternal administration of PM2.5 or PM2.5 with vitamin D during pregnancy and lactation on renal injury in rat dams and their offspring. Methods: Nine pregnant Sprague-Dawley rats received oral administration of normal saline, airborne PM2.5, or PM2.5 with vitamin D from gestational day 11 to postpartum day 21. Kidneys of rat dams (n = 3 for each group) and their male offspring (n = 5 for each group) were taken for analysis on postpartum or postnatal day 21. Results: Maternal PM2.5 exposure increased glomerular damage, tubulointerstitial injury, and cortical macrophage infiltration in both dams and pups; all increases were attenuated by vitamin D administration. In dam kidneys, PM2.5 increased the protein expression of vitamin D receptor (VDR), klotho, and tumor necrosis factor-α; vitamin D lessened these changes. The expressions of renin, nuclear factor erythroid 2-related factor 2 (Nrf2), and nuclear factor-kappa B (NF-κB) p50 decreased in rat dams exposed to PM2.5. In offspring kidneys, exposure to maternal PM2.5 reduced the expression of VDR, renin, angiotensin-converting enzyme (ACE), Nrf2, and NF-κB p50, but increased cytochrome P450 24A1 expression. Maternal vitamin D administration with PM2.5 enhanced VDR, ACE, and NF-κB p50 activities in pup kidneys. Conclusion: PM2.5 exposure during nephrogenesis may exert transgenerational renal impairment, and maternal vitamin D intake could attenuate PM2.5-induced kidney damage in mothers and their offspring.

Allergen immunotherapy (AIT) has been used for over a century and has been demonstrated to be effective in treating patients with various allergic diseases. AIT allergens can be administered through various routes, including subcutaneous, sublingual, intralymphatic, oral, or epicutaneous routes. Sublingual immunotherapy (SLIT) has recently gained clinical interest, and it is considered an alternative treatment for allergic rhinitis (AR) and asthma. This review provides an overview of the current evidence-based studies that address the use of SLIT for treating AR, including (1) mechanisms of action, (2) appropriate patient selection for SLIT, (3) the current available SLIT products in Korea, and (4) updated information on its efficacy and safety. Finally, this guideline aims to provide the clinician with practical considerations for SLIT.