Purpose: To investigate the prevalence of lower urinary tract symptoms/benign prostatic hyperplasia in a Korean population. Materials and Methods: The Korean Prostate & Voiding Health Association provided free prostate-related community health care and conducted surveys in all regions of Korea from 2001 to 2022 with the cooperation of local government public health centers. A total of 72,068 males older than 50 were surveyed and analyzed. History taking, International Prostate Symptom Score (IPSS), transrectal ultrasonography, prostate-specific antigen (PSA) testing, uroflowmetry, and urine volume testing were performed. Results: The mean prostate volumes in males in their 50s, 60s, 70s, and 80s or above were 24.7 g, 27.7 g, 31 g, and 33.7 g, respectively. The proportion of males with high PSA greater than 3 ng/mL was 3.8% among males in their 50s, 7.7% among males in their 60s, 13.1% among males in their 70s, and 17.9% among males 80 years of age or older. The mean IPSS total scores in males in their 50s, 60s, 70s, and 80s or above were 10.7, 12.7, 14.5, and 16, respectively. Severe symptoms were reported by 27.3% of males, whereas 51.7% reported moderate symptoms. The mean Qmax in males in their 50s, 60s, 70s, and 80s or above were 20 mL/s, 17.4 mL/s, 15.4 mL/s, and 13.8 mL/s, respectively. Conclusions In this population-based study, mean prostate volume, IPSS, PSA, and Qmax were 30.6±15.1 g, 14.8±8.2, 1.9±4.7 ng/mL, and 15.6±6.5 mL/s, respectively. Aging was significantly associated with increased prostate volume, PSA levels, and IPSS scores, and with decreased Qmax and urine volume.

Paramyotonia congenita (PMC) is characterized by nondystrophic myotonia aggravated by exercise and cold exposure. SCN4A mutations manifest as various phenotypes of channelopathy, including PMC, myotonia congenita, and periodic paralysis. SCN4A-related channelopathy is characterized by autosomal dominant inheritance. Parental gonadal mosaicism is suspected in cases of recurrent de novo mutation in an autosomal dominantly inherited disease. We report a case of two Korean brothers presenting with PMC due to same de novo SCN4A point mutation, probably due to parental gonadal mosaicism.

Purpose: The integration of artificial intelligence (AI) and magnetic resonance imaging in rectal cancer has the potential to enhance diagnostic accuracy by identifying subtle patterns and aiding tumor delineation and lymph node assessment. According to our systematic review focusing on convolutional neural networks, AI-driven tumor staging and the prediction of treatment response facilitate tailored treat­ment strategies for patients with rectal cancer. Methods: This paper summarizes the current landscape of AI in the imaging field of rectal cancer, emphasizing the performance reporting design based on the quality of the dataset, model performance, and external validation. Results: AI-driven tumor segmentation has demonstrated promising results using various convolutional neural network models. AI-based predictions of staging and treatment response have exhibited potential as auxiliary tools for personalized treatment strategies. Some studies have indicated superior performance than conventional models in predicting microsatellite instability and KRAS status, offer­ing noninvasive and cost-effective alternatives for identifying genetic mutations. Conclusion Image-based AI studies for rectal can­cer have shown acceptable diagnostic performance but face several challenges, including limited dataset sizes with standardized data, the need for multicenter studies, and the absence of oncologic relevance and external validation for clinical implantation. Overcoming these pitfalls and hurdles is essential for the feasible integration of AI models in clinical settings for rectal cancer, warranting further research.

OBJECTIVES: The escalating burden of cardiovascular disease (CVD) is a critical public health issue worldwide. CVD, especially acute myocardial infarction (AMI) and stroke, is the leading contributor to morbidity and mortality in Korea. We aimed to develop algorithms for identifying AMI and stroke events from the National Health Insurance Service (NHIS) database and validate these algorithms through medical record review. METHODS: We first established a concept and definition of “hospitalization episode,” taking into account the unique features of health claims-based NHIS database. We then developed first and recurrent event identification algorithms, separately for AMI and stroke, to determine whether each hospitalization episode represents a true incident case of AMI or stroke. Finally, we assessed our algorithms’ accuracy by calculating their positive predictive values (PPVs) based on medical records of algorithm- identified events. RESULTS: We developed identification algorithms for both AMI and stroke. To validate them, we conducted retrospective review of medical records for 3,140 algorithm-identified events (1,399 AMI and 1,741 stroke events) across 24 hospitals throughout Korea. The overall PPVs for the first and recurrent AMI events were around 92% and 78%, respectively, while those for the first and recurrent stroke events were around 88% and 81%, respectively. CONCLUSIONS We successfully developed algorithms for identifying AMI and stroke events. The algorithms demonstrated high accuracy, with PPVs of approximately 90% for first events and 80% for recurrent events. These findings indicate that our algorithms hold promise as an instrumental tool for the consistent and reliable production of national CVD statistics in Korea.

Background: and Purpose Advances in serological tests are transforming the classification of idiopathic inflammatory myopathy (IIM). The new criteria suggested by the 119th European Neuromuscular Center international workshop divide IIM cases into four main diseases according to clinical and pathological findings, adding immune-mediated necrotizing myositis and nonspecific myositis to the classic categories of polymyositis and dermatomyositis. Methods: Seventy one cases of IIM with sufficient available clinical and pathological data were reviewed to be reclassified according to the new criteria. Results: Most of the cases previously classified as polymyositis (77.8%, 35/45) were reclassified as immune-mediated necrotizing myopathy. The results of myositis-specific antibodies matched well with the new clinicopathological classification. Conclusions This new clinicopathological classification for IIM in combination with serological test results could be applied to our previous case series. Adoption of the new criteria will lead to a better understanding of the disease and hence new therapeutic insights.

Background: During the coronavirus disease 2019 (COVID-19) pandemic, patients with myasthenia gravis (MG) were more susceptible to poor outcomes owing to respiratory muscle weakness and immunotherapy. Several studies conducted in the early stages of the COVID-19 pandemic reported higher mortality in patients with MG compared to the general population. This study aimed to investigate the clinical course and prognosis of COVID-19 in patients with MG and to compare these parameters between vaccinated and unvaccinated patients in South Korea. Methods: This multicenter, retrospective study, which was conducted at 14 tertiary hospitals in South Korea, reviewed the medical records and identified MG patients who contracted COVID-19 between February 2022 and April 2022. The demographic and clinical characteristics associated with MG and vaccination status were collected. The clinical outcomes of COVID-19 infection and MG were investigated and compared between the vaccinated and unvaccinated patients. Results: Ninety-two patients with MG contracted COVID-19 during the study. Nine (9.8%) patients required hospitalization, 4 (4.3%) of whom were admitted to the intensive care unit. Seventy-five of 92 patients were vaccinated before contracting COVID-19 infection, and 17 were not. During the COVID-19 infection, 6 of 17 (35.3%) unvaccinated patients were hospitalized, whereas 3 of 75 (4.0%) vaccinated patients were hospitalized (P < 0.001). The frequencies of ICU admission and mechanical ventilation were significantly lower in the vaccinated patients than in the unvaccinated patients (P = 0.019 and P = 0.032, respectively). The rate of MG deterioration was significantly lower in the vaccinated patients than in the unvaccinated patients (P = 0.041). Logistic regression after weighting revealed that the risk of hospitalization and MG deterioration after COVID-19 infection was significantly lower in the vaccinated patients than in the unvaccinated patients. Conclusion This study suggests that the clinical course and prognosis of patients with MG who contracted COVID-19 during the dominance of the omicron variant of COVID-19 may be milder than those at the early phase of the COVID-19 pandemic when vaccination was unavailable. Vaccination may reduce the morbidity of COVID-19 in patients with MG and effectively prevent MG deterioration induced by COVID-19 infection.

The number of migrant workers is increasing worldwide every year, and their number and role in Korean society is also increasing. However, the poor conditions faced by migrant workers often become a social issue, and it is not uncommon for them to be the subject of forensic autopsies. This study aimed to investigate the current status of medicolegal autopsy on migrant workers in Korea. We collected data of medicolegal autopsies on migrant workers conducted in Korea from 2016 to 2020 by requesting data from the institutions performing medicolegal autopsy. We calculated the autopsy rate and analyzed manner of death and cause of death. The medicolegal autopsy rate for foreign deaths was 16.4%, which was more than five times higher than the autopsy rate for Korean deaths. By manner of death, 43.7% were natural death, 6.4% were homicides, 8.5% were suicides, 23.6% were accidental deaths, 2.7% were undetermined unnatural deaths and 15.0% were unknown. These results showed a high rate of homicide, accidental death, and unknown death compared to Korean. And the proportion of industrial accident deaths and sudden manhood death syndrome were high. Through this study, it was confirmed that medicolegal autopsies are performed at a relatively high frequency when migrant workers die, and the characteristics related to the deaths of migrant workers were identified.

Objective: The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. Materials and Methods: We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. Results: Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the nonsarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the nonmyosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25–2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84–3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08–3.54]; P = 0.027). Conclusion Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.