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: 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.

Endometriosis, a prevalent but debilitating condition affecting women, poses significant challenges in diagnosis and management. The current 2024 guideline, developed by the Korean Society of Endometriosis (KSE), builds upon the 2018 KSE guideline. This guideline aims to provide customized recommendations tailored to Korea’s unique clinical aspects and medical environment, and addresses key areas such as diagnosis, medical and surgical management, considerations for special populations, and its complex relationship with cancer.

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.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

South Korea’s current vaccination policies leave a surveillance gap for non-National Immunization Program (NIP) vaccines. In this study, we proposed a sentinel surveillance approach for monitoring the safety of non-NIP vaccines. Vaccination data were collected retrospectively among patients hospitalized with pre-defined adverse events of special interest (AESI) by reviewing electronic medical records in five university hospitals. This approach incorporates expert assessment to determine the causal relationship. We confirmed that 16 patients had received non-NIP vaccines among 860 patients diagnosed with AESI.We concluded one case of preeclampsia was possibly related to tetanus-diphtheria-pertussis vaccination. We propose a multi-hospital-based, retrospective assessment system for predefined AESIs as an alternative to active vaccine safety monitoring method. These efforts are expected to enhance both the accuracy and timeliness of safety monitoring in South Korea.

South Korea’s current vaccination policies leave a surveillance gap for non-National Immunization Program (NIP) vaccines. In this study, we proposed a sentinel surveillance approach for monitoring the safety of non-NIP vaccines. Vaccination data were collected retrospectively among patients hospitalized with pre-defined adverse events of special interest (AESI) by reviewing electronic medical records in five university hospitals. This approach incorporates expert assessment to determine the causal relationship. We confirmed that 16 patients had received non-NIP vaccines among 860 patients diagnosed with AESI.We concluded one case of preeclampsia was possibly related to tetanus-diphtheria-pertussis vaccination. We propose a multi-hospital-based, retrospective assessment system for predefined AESIs as an alternative to active vaccine safety monitoring method. These efforts are expected to enhance both the accuracy and timeliness of safety monitoring in South Korea.

The Korean Society of Gynecologic Oncology has updated its clinical practice guidelines for endometrial cancer to incorporate advancements in recent high-quality randomized controlled trials. These guidelines address evolving treatment paradigms, and are tailored to the Korean medical context. Key updates include a strong recommendation for doxorubicin/trabectedin combination therapy in metastatic or recurrent unresectable leiomyosarcoma based on the significant survival benefits demonstrated in a randomized controlled trial. For advanced or recurrent endometrial cancer, immune checkpoint inhibitors combined with chemotherapy have received strong recommendations, owing to their proven efficacy and increased accessibility in Korea. Conditional recommendations were made for combination therapies involving durvalumab and olaparib, reflecting their potential benefits, but acknowledging regulatory and accessibility constraints. These guidelines aim to provide evidence-based, practical strategies to optimize care for patients with endometrial cancer while addressing unmet clinical needs and adapting global advancements to Korea’s healthcare environment.

Purpose: Compassion is integral to nursing, yet the concept of compassionate care is not thoroughly understood. This study aimed to clarify the nature of compassionate care among Korean clinical nurses using a hybrid model. Methods: This study utilized a mixed methods approach involving hybrid concept analysis to explore the nature and attributes of compassionate care, encompassing both theoretical and empirical stages. In the theoretical stage, the domains, attributes, and a preliminary definition of compassionate care were formulated. In the fieldwork stage, in-depth interviews with 18 nurses were conducted to gather insights, which were integrated in the final stage. Results: Compassionate care was categorized into three domains: cognitive, relational, and behavioral, with 11 defining attributes. It was defined as the capacity to recognize individual patient needs, engage empathetically with their suffering, establish trust through emotional connection, and deliver therapeutic partnership, specialized, personalized, ethical, and holistic care. Conclusion This study advances the understanding of compassionate care in nursing by providing a multidimensional framework. It lays the groundwork for future research and practical applications, emphasizing the need for measurement tools and strategies to promote compassionate care among clinical nurses.

Endometriosis, a prevalent but debilitating condition affecting women, poses significant challenges in diagnosis and management. The current 2024 guideline, developed by the Korean Society of Endometriosis (KSE), builds upon the 2018 KSE guideline. This guideline aims to provide customized recommendations tailored to Korea’s unique clinical aspects and medical environment, and addresses key areas such as diagnosis, medical and surgical management, considerations for special populations, and its complex relationship with cancer.