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.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Purpose: This study aimed to project cancer incidence and mortality for 2025 to estimate Korea’s current cancer burden. Materials and Methods: Cancer incidence data from 1999 to 2022 were obtained from the Korea National Cancer Incidence Database, while cancer mortality data from 1993 to 2023 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observed age-specific cancer rates against their respective years and then by multiplying the projected age-specific rates by the anticipated age-specific population for 2025. A joinpoint regression model was applied to identify significant changes in trends, using only the most recent trend data for predictions. Results: A total of 304,754 new cancer cases and 84,019 cancer deaths are expected in Korea in 2025. The most commonly diagnosed cancer is projected to be thyroid cancer, followed by the colorectal, lung, breast, prostate and stomach cancers. These six cancers are expected to account for 63.8% of the total cancer burden. Lung cancer is expected to be the leading cause of cancer-related deaths, followed by liver, colorectal, pancreatic, stomach, and gallbladder cancers, together comprising 66.6% of total cancer deaths. Conclusion The increasing incidence of female breast cancer and the rise in prostate and pancreatic cancers are expected to continue. As aging accelerates, cancer commonly found in older adults are projected to rise significantly.

Purpose: The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2022, with international comparisons. Materials and Methods: Cancer incidence, survival, and prevalence rates were calculated using the Korea National Cancer Incidence Database (1999-2022), with survival follow-up until December 31, 2023. Mortality data obtained from Statistics Korea, while international comparisons were based on GLOBOCAN data. Results: In 2022, 282,047 newly diagnosed cancer cases (age-standardized rate [ASR], 287.0 per 100,000) and 83,378 deaths from cancer (ASR, 65.7 per 100,000) were reported. The proportion of localized-stage cancers increased from 45.6% in 2005 to 50.9% in 2022. Stomach, colorectal, and breast cancer showed increased localized-stage diagnoses by 18.1, 18.5, and 9.9 percentage points, respectively. Compared to 2001-2005, the 5-year relative survival (2018-2022) increased by 20.4 percentage points for stomach cancer, 7.6 for colorectal cancer, and 5.6 for breast cancer. Korea had the lowest cancer mortality among countries with similar incidence rates and the lowest mortality-to-incidence (M/I) ratios for these cancers. The 5-year relative survival (2018-2022) was 72.9%, contributing to over 2.59 million prevalent cases in 2022. Conclusion Since the launch of the National Cancer Screening Program in 2002, early detection has improved, increasing the diagnosis of localized-stage cancers and survival rates. Korea recorded the lowest M/I ratio among major comparison countries, demonstrating the effectiveness of its National Cancer Control Program.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Purpose: This study aimed to present a novel method for estimating the effective atomic number(Zeff ) using dual-energy computed tomography (DECT) designed to improve accuracy andstreamline clinical workflows by reducing computational complexity. Methods: The proposed model leverages the DECT-derived mass attenuation coefficients without detailed compositional analysis. By incorporating additional parameters into the conventional Rutherford model, such as exponential and trigonometric functions, the model effectively capturescomplex variations in attenuation, enabling precise Zeff estimation. Model fitting was performedusing dual-energy data and evaluated using the percentage difference in error rates. Results: Compared with the Rutherford model, which recorded a maximum error rate of 0.55%, the proposed model demonstrated a significantly lower maximum error rate of 0.15%, highlightingits precision. Zeff estimates for various materials closely matched the reference values, confirmingthe improved accuracy of the model. Conclusions The proposed DECT-based model provides a practical and efficient approach to Zeff estimation, with potential applications in radiation oncology, particularly for accurate stopping power ratio calculations in proton and heavy ion therapies.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.

Background: Factors influencing the decline in forced expiratory volume in one second (FEV1 )/forced vital capacity (FVC) for chronic obstructive pulmonary disease (COPD) progression remain uncertain. We aimed to identify risk factors associated with rapid FEV1 / FVC decline in patients with COPD. Methods: This multi-center observational study was conducted from January 2012 to December 2022. Eligible patients were monitored with symptoms, spirometric tests, and treatment patterns over 3 years. Rapid FEV1 /FVC decliners were defined as the quartile of patients exhibiting the highest annualized percentage decline in FEV1 /FVC. Results: Among 1,725 patients, 435 exhibited rapid FEV1 /FVC decline, with an annual change of −2.5%p (interquartile range, −3.5 to −2.0). Rapid FEV1 /FVC decliners exhibited lower body mass index (BMI), higher smoking rates, elevated post-bronchodilator (BD) FEV1 , higher post-BD FEV1 / FVC, and a lower prevalence of Staging of Airflow Obstruction by Ratio (STAR) stage IV. Rapid FEV1 /FVC decline was not linked to the annual exacerbation rate, but there was an association with symptom deterioration and FEV1 decline. In multivariable analyses, low BMI, current smoking, increased modified Medical Research Council dyspnoea score, low post-BD FEV1 , low STAR stage, high forced mid-expiratory flow (FEF 25-75% ), accelerated FEV1 decline, and not initiating dual BD therapy were identified as independent risk factors for rapid FEV1 /FVC decline. Conclusion We identified the risk factors for rapid FEV1 /FVC decline, including BMI, smoking, symptoms deterioration, FEV1 decline, and adherence to standard inhaler treatment. Our findings underscore the potential benefits of maintaining consistent use of long-acting beta-agonist/long-acting muscarinic antagonist even in the presence of worsening symptoms, in attenuating FEV1 /FVC decline.