Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Purpose: Identifying and managing risk factors for lower urinary tract symptoms (LUTS) is crucial because it impacts the quality of life of elderly individuals. Lifestyle factors, including physical activity (PA), and their relationship with LUTS have not been well studied. This objective of this study was to investigate the association between PA and LUTS. Materials and Methods: A total of 7,296 men were included in this cross-sectional study. PA was quantified in metabolic equivalent (MET)-hours per week, and LUTS severity was assessed using the international prostate symptom score. Logistic regression was used to analyze the association between PA and LUTS, including voiding and storage symptoms. Results: The average age of the participants was 57.8 years, and the prevalence of LUTS was 41.3%. After adjusting for potential confounders, PA was inversely associated with the prevalence and severity of moderate-to-severe LUTS, showing a dose-response pattern (all p for trend <0.01). Compared to the minimal activity group, which engaged in <5 MET-hours per week of PA, the odds ratios for moderate to severe LUTS were 0.83 (95% confidence interval [CI]: 0.72–0.97) for men engaging in 15–30 MET-hours per week, 0.82 (95% CI: 0.71–0.95) for 30–60 MET-hours per week, and 0.72 (95% CI: 0.62–0.84) for ≥60 MET-hours per week. The possible protective effect of PA was still observed in the additional analysis for voiding and storage symptoms showing the same dose-response pattern (all p for trend <0.01). Conclusions A higher PA level was associated with a lower prevalence and severity of total, voiding, and storage LUTS in a dose-dependent manner in Korean men.

Purpose: This study aimed to develop a comprehensive practical guide for enteral nutrition (EN) designed to enhance patient safety and reduce complications in Korea. Under the leadership of the Korean Society for Parenteral and Enteral Nutrition (KSPEN), the initiative sought to standardize EN procedures, improve decision-making, and promote effective multidisciplinary communication. Methods: The KSPEN EN committee identified key questions related to EN practices and organized them into seven sections such as prescribing, delivery route selection, formula preparation, administration, and quality management. Twenty-one experts, selected based on their expertise, conducted a thorough literature review to formulate evidence-based recommendations. Drafts underwent peer review both within and across disciplines, with final revisions completed by the KSPEN Guideline Committee. The guide, which will be published in three installments, addresses critical elements of EN therapy and safety protocols. Results: The practical guide recommends that EN orders include detailed elements and advocates the use of electronic medical records for communication. Standardized prescription forms and supplementary safety measures are outlined. Review frequency is adjusted according to patient condition—daily for critically ill or unstable patients and as dictated by institutional protocols for stable patients. Evidence indicates that adherence to these protocols reduces mortality, complications, and prescription errors. Conclusion The KSPEN practical guide offers a robust framework for the safe delivery of EN tailored to Korea’s healthcare context. It emphasizes standardized protocols and interdisciplinary collaboration to improve nutritional outcomes, patient safety, and operational efficiency. Rigorous implementation and monitoring of adherence are critical for its success.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Purpose: Identifying and managing risk factors for lower urinary tract symptoms (LUTS) is crucial because it impacts the quality of life of elderly individuals. Lifestyle factors, including physical activity (PA), and their relationship with LUTS have not been well studied. This objective of this study was to investigate the association between PA and LUTS. Materials and Methods: A total of 7,296 men were included in this cross-sectional study. PA was quantified in metabolic equivalent (MET)-hours per week, and LUTS severity was assessed using the international prostate symptom score. Logistic regression was used to analyze the association between PA and LUTS, including voiding and storage symptoms. Results: The average age of the participants was 57.8 years, and the prevalence of LUTS was 41.3%. After adjusting for potential confounders, PA was inversely associated with the prevalence and severity of moderate-to-severe LUTS, showing a dose-response pattern (all p for trend <0.01). Compared to the minimal activity group, which engaged in <5 MET-hours per week of PA, the odds ratios for moderate to severe LUTS were 0.83 (95% confidence interval [CI]: 0.72–0.97) for men engaging in 15–30 MET-hours per week, 0.82 (95% CI: 0.71–0.95) for 30–60 MET-hours per week, and 0.72 (95% CI: 0.62–0.84) for ≥60 MET-hours per week. The possible protective effect of PA was still observed in the additional analysis for voiding and storage symptoms showing the same dose-response pattern (all p for trend <0.01). Conclusions A higher PA level was associated with a lower prevalence and severity of total, voiding, and storage LUTS in a dose-dependent manner in Korean men.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Purpose: Identifying and managing risk factors for lower urinary tract symptoms (LUTS) is crucial because it impacts the quality of life of elderly individuals. Lifestyle factors, including physical activity (PA), and their relationship with LUTS have not been well studied. This objective of this study was to investigate the association between PA and LUTS. Materials and Methods: A total of 7,296 men were included in this cross-sectional study. PA was quantified in metabolic equivalent (MET)-hours per week, and LUTS severity was assessed using the international prostate symptom score. Logistic regression was used to analyze the association between PA and LUTS, including voiding and storage symptoms. Results: The average age of the participants was 57.8 years, and the prevalence of LUTS was 41.3%. After adjusting for potential confounders, PA was inversely associated with the prevalence and severity of moderate-to-severe LUTS, showing a dose-response pattern (all p for trend <0.01). Compared to the minimal activity group, which engaged in <5 MET-hours per week of PA, the odds ratios for moderate to severe LUTS were 0.83 (95% confidence interval [CI]: 0.72–0.97) for men engaging in 15–30 MET-hours per week, 0.82 (95% CI: 0.71–0.95) for 30–60 MET-hours per week, and 0.72 (95% CI: 0.62–0.84) for ≥60 MET-hours per week. The possible protective effect of PA was still observed in the additional analysis for voiding and storage symptoms showing the same dose-response pattern (all p for trend <0.01). Conclusions A higher PA level was associated with a lower prevalence and severity of total, voiding, and storage LUTS in a dose-dependent manner in Korean men.