Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

Vaccine-induced hypermetabolic lymph nodes have been clinically observed following coronavirus disease 2019 (COVID-19) mRNA vaccination. Specifically, the booster dose of the mRNA vaccines, produced by Pfizer and Moderna, has been linked to a relatively high incidence of lymphadenopathy. We present the case of a kidney transplant recipient who developed an enlarged abdominal mass after receiving a booster dose of the COVID-19 mRNA vaccine. This mass occupied the retroperitoneal space, infiltrated the psoas muscle, and resulted in ureteric compression and hydronephrosis. Percutaneous drainage and analysis of the perirenal fluid revealed the presence of lymphatic fluid. In summary, lymphadenopathy is a recognized adverse reaction to the Pfizer and Moderna vaccines. Patients with compromised immune systems should be informed about the incidence and potential severity of lymphadenopathy following booster vaccination.

Background: and Purpose: This clinical practice guideline provides evidence-based recommendations for treatment of dementia, focusing on cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists for Alzheimer’s disease (AD) and other types of dementia. Methods: Using the Population, Intervention, Comparison, Outcomes (PICO) framework, we developed key clinical questions and conducted systematic literature reviews. A multidisciplinary panel of experts, organized by the Korean Dementia Association, evaluated randomized controlled trials and observational studies. Recommendations were graded for evidence quality and strength using Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. Results: Three main recommendations are presented: (1) For AD, cholinesterase inhibitors (donepezil, rivastigmine, galantamine) are strongly recommended for improving cognition and daily function based on moderate evidence; (2) Cholinesterase inhibitors are conditionally recommended for vascular dementia and Parkinson’s disease dementia, with a strong recommendation for Lewy body dementia; (3) For moderate to severe AD, NMDA receptor antagonist (memantine) is strongly recommended, demonstrating significant cognitive and functional improvements. Both drug classes showed favorable safety profiles with manageable side effects. Conclusions This guideline offers standardized, evidence-based pharmacologic recommendations for dementia management, with specific guidance on cholinesterase inhibitors and NMDA receptor antagonists. It aims to support clinical decision-making and improve patient outcomes in dementia care. Further updates will address emerging treatments, including amyloid-targeting therapies, to reflect advances in dementia management.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background: and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes. Methods: We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data. Results: Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4. Conclusion Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.

In 2023, blood donations from registered donors at the Korean Red Cross Blood Centers accounted for 72.6% of blood donations from the Korean Red Cross, helping secure blood equivalent to 65.9% of entire blood donations, 87.6% of plasmapheresis, and 95.1% of platelets component donations. The number of newly registered blood donors increased from 94,998 in 2017 to 218,767 in 2023, and 1,928,053 donors were registered as of December 2023. The age distribution of registered blood donors showed that teenagers and people in their 20s accounted for approximately 70% of the total. Nevertheless, additional research on the blood donation status according to the age of new and cumulative registered blood donors is needed to manage blood donation resources.

Vaccine-induced hypermetabolic lymph nodes have been clinically observed following coronavirus disease 2019 (COVID-19) mRNA vaccination. Specifically, the booster dose of the mRNA vaccines, produced by Pfizer and Moderna, has been linked to a relatively high incidence of lymphadenopathy. We present the case of a kidney transplant recipient who developed an enlarged abdominal mass after receiving a booster dose of the COVID-19 mRNA vaccine. This mass occupied the retroperitoneal space, infiltrated the psoas muscle, and resulted in ureteric compression and hydronephrosis. Percutaneous drainage and analysis of the perirenal fluid revealed the presence of lymphatic fluid. In summary, lymphadenopathy is a recognized adverse reaction to the Pfizer and Moderna vaccines. Patients with compromised immune systems should be informed about the incidence and potential severity of lymphadenopathy following booster vaccination.

Background: and Purpose: This clinical practice guideline provides evidence-based recommendations for treatment of dementia, focusing on cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists for Alzheimer’s disease (AD) and other types of dementia. Methods: Using the Population, Intervention, Comparison, Outcomes (PICO) framework, we developed key clinical questions and conducted systematic literature reviews. A multidisciplinary panel of experts, organized by the Korean Dementia Association, evaluated randomized controlled trials and observational studies. Recommendations were graded for evidence quality and strength using Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. Results: Three main recommendations are presented: (1) For AD, cholinesterase inhibitors (donepezil, rivastigmine, galantamine) are strongly recommended for improving cognition and daily function based on moderate evidence; (2) Cholinesterase inhibitors are conditionally recommended for vascular dementia and Parkinson’s disease dementia, with a strong recommendation for Lewy body dementia; (3) For moderate to severe AD, NMDA receptor antagonist (memantine) is strongly recommended, demonstrating significant cognitive and functional improvements. Both drug classes showed favorable safety profiles with manageable side effects. Conclusions This guideline offers standardized, evidence-based pharmacologic recommendations for dementia management, with specific guidance on cholinesterase inhibitors and NMDA receptor antagonists. It aims to support clinical decision-making and improve patient outcomes in dementia care. Further updates will address emerging treatments, including amyloid-targeting therapies, to reflect advances in dementia management.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.