Heart failure (HF) is a major cause of mortality and morbidity in South Korea, imposing substantial physical, emotional, and financial burdens on patients and society. Despite the high burden of symptom and complex care needs of HF patients, palliative care and hospice services remain underutilized in South Korea due to cultural, institutional, and knowledge-related barriers. This position statement from the Korean Society of Heart Failure emphasizes the need for integrating palliative and hospice care into HF management to improve quality of life and support holistic care for patients and their families. By clarifying the role of palliative care in HF and proposing practical referral criteria, this position statement aims to bridge the gap between HF and palliative care services in South Korea, ultimately improving patient-centered outcomes and aligning treatment with the goals and values of HF patients.

Background/Aims: We previously reported that patients with moderate-to-severe ulcerative colitis (UC) often experience common mental disorders (CMDs) such as anxiety and depression, necessitating immediate psychological interventions within the first 4 weeks of diagnosis. In this 3-year follow-up study of the MOSAIK cohort in Korea, we examined the effects of CMDs at initial diagnosis on clinical outcomes and health-related quality of life (HRQoL). Methods: We examined differences in clinical outcomes (evaluated based on clinical response, relapse, hospitalization, and medication use) and HRQoL (assessed using the Inflammatory Bowel Disease Questionnaire [IBDQ] and Short Form 12 [SF-12]) according to Hospital Anxiety and Depression Scale (HADS) scores at diagnosis. Results: In a study involving 199 UC patients, 47.7% exhibited significant psychological distress (anxiety and/or depression) at diagnosis. Clinical follow-up showed no major differences in outcomes, including remission rates, response rates, or hospitalization rates, between patients with anxiety or depression at diagnosis and patients without anxiety or depression at diagnosis. The HRQoL at the end of follow-up was notably lower in those with baseline CMDs, particularly anxiety, across all domains of the IBDQ and SF-12. Linear mixed-effect models revealed that higher HADS scores, as well as higher Mayo scores, were independently associated with lower IBDQ scores and both summary domains of the SF-12. Additionally, regular attendance at follow-up visits during the study period was also related to improvements in HRQoL (all p<0.05). Conclusions While CMDs present at the time of UC diagnosis did not influence long-term clinical outcomes, they persistently impaired HRQoL. Our findings support the routine incorporation of psychological interventions into the long-term management of moderate-to-severe UC.

Background/Aims: We previously reported that patients with moderate-to-severe ulcerative colitis (UC) often experience common mental disorders (CMDs) such as anxiety and depression, necessitating immediate psychological interventions within the first 4 weeks of diagnosis. In this 3-year follow-up study of the MOSAIK cohort in Korea, we examined the effects of CMDs at initial diagnosis on clinical outcomes and health-related quality of life (HRQoL). Methods: We examined differences in clinical outcomes (evaluated based on clinical response, relapse, hospitalization, and medication use) and HRQoL (assessed using the Inflammatory Bowel Disease Questionnaire [IBDQ] and Short Form 12 [SF-12]) according to Hospital Anxiety and Depression Scale (HADS) scores at diagnosis. Results: In a study involving 199 UC patients, 47.7% exhibited significant psychological distress (anxiety and/or depression) at diagnosis. Clinical follow-up showed no major differences in outcomes, including remission rates, response rates, or hospitalization rates, between patients with anxiety or depression at diagnosis and patients without anxiety or depression at diagnosis. The HRQoL at the end of follow-up was notably lower in those with baseline CMDs, particularly anxiety, across all domains of the IBDQ and SF-12. Linear mixed-effect models revealed that higher HADS scores, as well as higher Mayo scores, were independently associated with lower IBDQ scores and both summary domains of the SF-12. Additionally, regular attendance at follow-up visits during the study period was also related to improvements in HRQoL (all p<0.05). Conclusions While CMDs present at the time of UC diagnosis did not influence long-term clinical outcomes, they persistently impaired HRQoL. Our findings support the routine incorporation of psychological interventions into the long-term management of moderate-to-severe UC.

Background/Aims: We previously reported that patients with moderate-to-severe ulcerative colitis (UC) often experience common mental disorders (CMDs) such as anxiety and depression, necessitating immediate psychological interventions within the first 4 weeks of diagnosis. In this 3-year follow-up study of the MOSAIK cohort in Korea, we examined the effects of CMDs at initial diagnosis on clinical outcomes and health-related quality of life (HRQoL). Methods: We examined differences in clinical outcomes (evaluated based on clinical response, relapse, hospitalization, and medication use) and HRQoL (assessed using the Inflammatory Bowel Disease Questionnaire [IBDQ] and Short Form 12 [SF-12]) according to Hospital Anxiety and Depression Scale (HADS) scores at diagnosis. Results: In a study involving 199 UC patients, 47.7% exhibited significant psychological distress (anxiety and/or depression) at diagnosis. Clinical follow-up showed no major differences in outcomes, including remission rates, response rates, or hospitalization rates, between patients with anxiety or depression at diagnosis and patients without anxiety or depression at diagnosis. The HRQoL at the end of follow-up was notably lower in those with baseline CMDs, particularly anxiety, across all domains of the IBDQ and SF-12. Linear mixed-effect models revealed that higher HADS scores, as well as higher Mayo scores, were independently associated with lower IBDQ scores and both summary domains of the SF-12. Additionally, regular attendance at follow-up visits during the study period was also related to improvements in HRQoL (all p<0.05). Conclusions While CMDs present at the time of UC diagnosis did not influence long-term clinical outcomes, they persistently impaired HRQoL. Our findings support the routine incorporation of psychological interventions into the long-term management of moderate-to-severe UC.

Background/Aims: We previously reported that patients with moderate-to-severe ulcerative colitis (UC) often experience common mental disorders (CMDs) such as anxiety and depression, necessitating immediate psychological interventions within the first 4 weeks of diagnosis. In this 3-year follow-up study of the MOSAIK cohort in Korea, we examined the effects of CMDs at initial diagnosis on clinical outcomes and health-related quality of life (HRQoL). Methods: We examined differences in clinical outcomes (evaluated based on clinical response, relapse, hospitalization, and medication use) and HRQoL (assessed using the Inflammatory Bowel Disease Questionnaire [IBDQ] and Short Form 12 [SF-12]) according to Hospital Anxiety and Depression Scale (HADS) scores at diagnosis. Results: In a study involving 199 UC patients, 47.7% exhibited significant psychological distress (anxiety and/or depression) at diagnosis. Clinical follow-up showed no major differences in outcomes, including remission rates, response rates, or hospitalization rates, between patients with anxiety or depression at diagnosis and patients without anxiety or depression at diagnosis. The HRQoL at the end of follow-up was notably lower in those with baseline CMDs, particularly anxiety, across all domains of the IBDQ and SF-12. Linear mixed-effect models revealed that higher HADS scores, as well as higher Mayo scores, were independently associated with lower IBDQ scores and both summary domains of the SF-12. Additionally, regular attendance at follow-up visits during the study period was also related to improvements in HRQoL (all p<0.05). Conclusions While CMDs present at the time of UC diagnosis did not influence long-term clinical outcomes, they persistently impaired HRQoL. Our findings support the routine incorporation of psychological interventions into the long-term management of moderate-to-severe UC.

Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.