Ultrasonography (US) is a sensitive and radiation-free technique for diagnosing deep vein thrombosis (DVT). Therefore, when DVT is clinically suspected but not detected on US, radiologists should consider a range of alternative differential diagnoses. This review article presents the imaging findings of clinical conditions that mimic DVT, which can be distinguished using a multimodal radiologic approach. Additionally, DVT mimics can be categorized into two groups based on whether a flat or normal waveform is observed on Doppler US. This article details the imaging findings and clinical presentations of DVT mimics, organized by these classifications. This information may help radiologists make more accurate diagnoses, enabling patients to receive appropriate treatment in a timely manner.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

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.

Ultrasonography (US) is a sensitive and radiation-free technique for diagnosing deep vein thrombosis (DVT). Therefore, when DVT is clinically suspected but not detected on US, radiologists should consider a range of alternative differential diagnoses. This review article presents the imaging findings of clinical conditions that mimic DVT, which can be distinguished using a multimodal radiologic approach. Additionally, DVT mimics can be categorized into two groups based on whether a flat or normal waveform is observed on Doppler US. This article details the imaging findings and clinical presentations of DVT mimics, organized by these classifications. This information may help radiologists make more accurate diagnoses, enabling patients to receive appropriate treatment in a timely manner.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Ultrasonography (US) is a sensitive and radiation-free technique for diagnosing deep vein thrombosis (DVT). Therefore, when DVT is clinically suspected but not detected on US, radiologists should consider a range of alternative differential diagnoses. This review article presents the imaging findings of clinical conditions that mimic DVT, which can be distinguished using a multimodal radiologic approach. Additionally, DVT mimics can be categorized into two groups based on whether a flat or normal waveform is observed on Doppler US. This article details the imaging findings and clinical presentations of DVT mimics, organized by these classifications. This information may help radiologists make more accurate diagnoses, enabling patients to receive appropriate treatment in a timely manner.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: As nursing continues to advance through digital health, clinical specialization, and interdisciplinary research, early-career nurse scientists are central to advancing innovation. However, Korea lacks a structured platform to support their research, collaboration, and career development. This review aimed to identify the needs of early-career nurse scientists and examine international best practices to guide the creation of an effective communication platform. Methods: This study involved a secondary analysis of the final report from the project “Establishment of a communication platform for young nursing scientists,” carried out by the Korean Society of Nursing Science. The report comprises data from focus group interviews with domestic graduate students and early-career researchers, a literature review of international communication and support systems, and a global policy analysis related to young nursing scientists. Based on this report, the present review synthesizes key findings and draws implications for the development of a communication platform in Korea. Results: International examples, such as grant writing programs, mentoring initiatives, and digital collaboration hubs, showed positive outcomes in strengthening research capacity and promoting the professional growth of nurse scientists. Based on these findings, key considerations for platform development include: (1) establishing clear leadership and a participatory governance model; (2) providing demand-driven content such as research guides, mentoring, and mental health resources; (3) implementing mechanisms to ensure sustainability, content quality, and user data protection; and (4) designing an integrated platform that fosters synergy across research, policy development, education, and global networking. Conclusion A digital platform for early-career nurse scientists should function not merely as an information portal, but also as dynamic infrastructure for collaboration, mentorship, and growth. It is recommended that the Korean Society of Nursing Science spearhead this initiative, with governmental support, to enhance the research capacity and expand the global engagement of Korean nursing scientists.

Purpose: As nursing continues to advance through digital health, clinical specialization, and interdisciplinary research, early-career nurse scientists are central to advancing innovation. However, Korea lacks a structured platform to support their research, collaboration, and career development. This review aimed to identify the needs of early-career nurse scientists and examine international best practices to guide the creation of an effective communication platform. Methods: This study involved a secondary analysis of the final report from the project “Establishment of a communication platform for young nursing scientists,” carried out by the Korean Society of Nursing Science. The report comprises data from focus group interviews with domestic graduate students and early-career researchers, a literature review of international communication and support systems, and a global policy analysis related to young nursing scientists. Based on this report, the present review synthesizes key findings and draws implications for the development of a communication platform in Korea. Results: International examples, such as grant writing programs, mentoring initiatives, and digital collaboration hubs, showed positive outcomes in strengthening research capacity and promoting the professional growth of nurse scientists. Based on these findings, key considerations for platform development include: (1) establishing clear leadership and a participatory governance model; (2) providing demand-driven content such as research guides, mentoring, and mental health resources; (3) implementing mechanisms to ensure sustainability, content quality, and user data protection; and (4) designing an integrated platform that fosters synergy across research, policy development, education, and global networking. Conclusion A digital platform for early-career nurse scientists should function not merely as an information portal, but also as dynamic infrastructure for collaboration, mentorship, and growth. It is recommended that the Korean Society of Nursing Science spearhead this initiative, with governmental support, to enhance the research capacity and expand the global engagement of Korean nursing scientists.

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.