Objective: Although maintenance treatment for mood disorders is important, the treatment discontinuation rate is reported to be high. This study aimed to investigate the dropout rates and associated factors in mood disorders. Methods: The patients in a mood disorder clinic (n = 535) were examined. Demographic and clinical factors, scores of psychometric scales, time to dropout from initial treatment in patients with bipolar disorder (BP) (n = 288) and depressive disorder (DD) (n = 143) were evaluated based on database of the mood disorder clinic. Results: Among the studied patients with BP and DD, 50% showed dropout in 4.05 and 2.17 years, respectively. The mean survival times were 8.90 years in bipolar disorder I (BP-I), 5.19 years in bipolar II disorder, 3.22 years in bipolar disorder not otherwise specified, 4.24 years in major depressive disorder, and 4.03 years in other depressive disorders.In the multivariate Cox proportional hazards regression model in the BP group, diagnosis BP-I was found to be significantly related to the decrease in dropout rate (hazard ratio [HR] = 0.22, p = 0.001); however, increased past suicide attempt number was significantly related to the increase in dropout rate (HR = 1.13, p = 0.017). In the DD group, none of anxiety disorders as comorbidity, increased scores of openness, and extraversion personality were related to the increase in dropout rate. Conclusion Patients with BP, especially BP-I, showed a lower dropout rate as compared to patients with other mood disorders.

PURPOSE: The purpose of this study was to identify the influences of recognition on low fertility and views of marriage on childbirth will in university students. METHODS: Participants were 190 university students in Chungchungnamdo province, Korea. The data were collected from May to October 2018 and examined using descriptive statistics, t-test, analysis of variance, Pearson correlation and multiple regression with IBM SPSS Statistics ver. 24.0. RESULTS: Childbirth will was significantly correlated with recognition on low fertility (r=0.20, p=0.002) and views on marriage (r=0.53, p<0.001). Factors associated with childbirth will were views on marriage (β=0.24, p<0.001). CONCLUSION Theses results suggests that views on marriage have important influences on childbirth will in university students. To improve childbirth will, the positive views on marriage need to be formulated in university students.

Many transplant recipients believe that exercise or physical activity after transplantation will have adverse effects on the body and the grafted organ, and even more, some of them believe that the grafted organ will tear off from the vascular bed inside of the abdominal cavity. As a result, many recipients are isolated from social life even after successful recovery of the grafted organ function. However, rehabilitation by physical exercise and activity is essential to return to normal social life. In 1978, a transplantee's sport game known as the Transplant Olympics, which later changed to the World Transplant Games, was started to improve the quality of life and develop friendships between transplant recipients globally. This event promotes improvement of recipient's life quality while delivering an important message to the public. This is because by engaging in sports activities, transplantees can show their healthy life after transplantation to the public. This can also improve self-esteem of the family of organ donors and allow them to verify that their decision to donate was not in vain. Additionally, the public can realize the benefits of transplantation and necessity for organ donation. Finally, the early return to social life and normal family life after transplantation will also reduce the national budget for health insurance. Although sports clubs are located in all transplant centers in Korea, no continuous athletic meetings or transplant sport organization exist nationwide. This problem is exacerbated by the lack of concern that transplant physicians and surgeons show toward recipients' physical activity and exercise. Therefore, in this study, we reviewed the significance of physical activity after transplantation and describe the world transplant games and domestic games to enable development of a recipient rehabilitation plan.
Abdominal Cavity ; Budgets ; Exercise ; Exercise Therapy ; Friends ; Humans ; Insurance, Health ; Korea ; Motor Activity ; Quality of Life ; Rehabilitation* ; Sports ; Surgeons ; Tears ; Tissue and Organ Procurement ; Tissue Donors ; Transplant Recipients ; Transplants

Background: and Purpose The wearing-off (WO) phenomenon is the most common motor complication in advanced Parkinson’s disease (PD), but its identification remains challenging. The 9- and 19-item Wearing-off Questionnaires (WOQ-9 and WOQ-19) are self-assessment tools for motor and nonmotor symptoms that are widely used for WO screening. We produced Korean versions of the WOQ-19 and WOQ-9 (K-WOQ-19 and K-WOQ-9) and investigated their validity and reliability. Methods: We used the translation–back translation method to produce K-WOQ-19 and KWOQ-9, which were self-administered by 124 patients with PD. We conducted in-depth 10-minute interviews for confirming the presence of the WO phenomenon, and then stratified the participants into groups with and without WO. Diagnostic accuracy was assessed by analyzing receiver operating characteristic curves. Concurrent validity was assessed using the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and the Hoehn and Yahr stage with Spearman’s rank correlation analysis. Reliability was assessed based on test–retest Cohen’s kappa (κ) values and intraclass correlation coefficients (ICCs). Results: The optimal cutoff scores on the K-WOQ-19 and K-WOQ-9 for WO screening were 4 and 2, respectively. The test–retest ICCs of K-WOQ-19 and K-WOQ-9 were 0.943 and 0.938, respectively. Nineteen of the combined 20 items in K-WOQ-19 and K-WOQ-9 showed moderate-to-substantial agreement (κ=0.412–0.771, p<0.001). The scores on the translated scales were significantly correlated with MDS-UPDRS IV scores. Conclusions K-WOQ-19 and K-WOQ-9 are reliable and valid tools for detecting WO, with optimal cutoff scores of 4 and 2, respectively.

Background: Because persistent fever often occurs in adrenal insufficiency, it might be confused with infectious diseases. This study aimed to identify clinical characteristics and risk factors of patients with adrenal insufficiency and fever. Methods: All adult patients (n = 150) admitted to a tertiary care hospital in South Korea and diagnosed with adrenal insufficiency between 1 March 2018, and 30 June 2019, were recruited. Patients were excluded if they had: 1) proven structural problems in the adrenal or pituitary gland; 2) a history of chemotherapy within 6 months prior to the diagnosis of adrenal insufficiency; and 3) other medical conditions that may cause fever. Results: Among the included patients, 45 (30.0%) had fever at the time of the diagnosis of adrenal insufficiency. The mean C-reactive protein level was higher (11.25 ± 8.54 vs. 4.36 ± 7.13 mg/dL) in patients with fever than in those without fever. A higher proportion of patients with fever changed antibiotics (33.3% vs. 1.0%). On multivariate logistic regression analysis, female sex (odds ratio [OR], 0.32) lowered the risk of adrenal insufficiency with fever, while a history of surgery within 6 months (OR, 4.35), general weakness (OR, 7.21), and cough (OR, 17.29) were significantly associated with that. Conclusion The possibility of adrenal insufficiency should be considered in patients with fever of unknown origin, especially those with risk factors.

Background: Because persistent fever often occurs in adrenal insufficiency, it might be confused with infectious diseases. This study aimed to identify clinical characteristics and risk factors of patients with adrenal insufficiency and fever. Methods: All adult patients (n = 150) admitted to a tertiary care hospital in South Korea and diagnosed with adrenal insufficiency between 1 March 2018, and 30 June 2019, were recruited. Patients were excluded if they had: 1) proven structural problems in the adrenal or pituitary gland; 2) a history of chemotherapy within 6 months prior to the diagnosis of adrenal insufficiency; and 3) other medical conditions that may cause fever. Results: Among the included patients, 45 (30.0%) had fever at the time of the diagnosis of adrenal insufficiency. The mean C-reactive protein level was higher (11.25 ± 8.54 vs. 4.36 ± 7.13 mg/dL) in patients with fever than in those without fever. A higher proportion of patients with fever changed antibiotics (33.3% vs. 1.0%). On multivariate logistic regression analysis, female sex (odds ratio [OR], 0.32) lowered the risk of adrenal insufficiency with fever, while a history of surgery within 6 months (OR, 4.35), general weakness (OR, 7.21), and cough (OR, 17.29) were significantly associated with that. Conclusion The possibility of adrenal insufficiency should be considered in patients with fever of unknown origin, especially those with risk factors.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

This study employed focus group interviews (FGIs) to evaluate the preparedness and training requirements for an emerging infectious disease response system in the Republic of Korea.Based on the FGIs, the critical role of interdepartmental cooperation in responding to emerging infectious diseases was identified, with agencies such as public health centers, police, and fire services playing key roles in scene control, decontamination, and patient transport. Frequent staff turnover and a lack of trained personnel at local government levels were significant challenges, necessitating the development of training materials for unskilled workers. Civil complaints, common during outbreaks, require public officials to be educated on legal frameworks and the management of patients’ rights. The absence of standardized procedures for managing patients, such as bed assignments considering underlying conditions and sample collection, underscores the need for comprehensive guidelines.Interviewees emphasized cross-departmental training, detailed manuals, and legal education to improve infectious disease response capabilities.

This study employed focus group interviews (FGIs) to evaluate the preparedness and training requirements for an emerging infectious disease response system in the Republic of Korea.Based on the FGIs, the critical role of interdepartmental cooperation in responding to emerging infectious diseases was identified, with agencies such as public health centers, police, and fire services playing key roles in scene control, decontamination, and patient transport. Frequent staff turnover and a lack of trained personnel at local government levels were significant challenges, necessitating the development of training materials for unskilled workers. Civil complaints, common during outbreaks, require public officials to be educated on legal frameworks and the management of patients’ rights. The absence of standardized procedures for managing patients, such as bed assignments considering underlying conditions and sample collection, underscores the need for comprehensive guidelines.Interviewees emphasized cross-departmental training, detailed manuals, and legal education to improve infectious disease response capabilities.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.