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.

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.

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.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Objective: Effective triage of febrile patients in the emergency department is crucial during times of overcrowding to prioritize care and allocate resources, especially during pandemics. However, available triage tools often require laboratory data and lack accuracy. We aimed to develop a simple and accurate triage tool for febrile patients by modifying the quick Sequential Organ Failure Assessment (qSOFA) score. Methods: We retrospectively analyzed data from 7,303 febrile patients and created modified versions of qSOFA using factors identified through multivariable analysis. The performance of these modified qSOFAs in predicting in-hospital mortality and intensive care unit (ICU) admission was compared using the area under the receiver operating characteristic curve (AUROC). Results: Through multivariable analysis, the identified factors were age (“A” factor), male sex (“M” factor), oxygen saturation measured by pulse oximetry (SpO2; “S” factor), and lactate level (“L” factor). The AUROCs of ASqSOFA (in-hospital mortality: 0.812 [95% confidence interval, 0.789–0.835]; ICU admission: 0.794 [95% confidence interval, 0.771–0.817]) were simple and not inferior to those of other more complex models (e.g., ASMqSOFA, ASLqSOFA, and ASMLqSOFA). ASqSOFA also displayed significantly higher AUROC than other triage scales, such as the Modified Early Warning Score and Korean Triage and Acuity Scale. The optimal cutoff score of ASqSOFA for the outcome was 2, and the score for redistribution to a lower level emergency department was 0. Conclusion We demonstrated that ASqSOFA can be employed as a simple and efficient triage tool for emergency febrile patients to aid in resource distribution during overcrowding. It also may be applicable in prehospital settings for febrile patient triage.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

Objective: This study aimed to examine the psychiatric impact of the Seoul Halloween crowd crush on individuals related to the victims compared to the general population. It also explores the moderating effect of resilience on the relationship between trauma exposure and psychiatric symptoms. Methods: In total, 2,220 participants completed various post-incident questionnaires (Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Hwa-byung symptom scale, post-traumatic stress disorder checklist for DSM-5, and Brief Resilience Scale) 30 days after the incident. Moderation analyses were conducted using the PROCESS macro in the statistical package for the social sciences. Results: Individuals related to the victims exhibited higher symptom severity and a greater risk for clinically significant levels of depression, anxiety, anger, and post-traumatic stress disorder (PTSD) (odds ratio=3.28, 3.33, 1.51, and 4.39 respectively). The impact of relevance to victims on anxiety and PTSD symptoms was moderated by resilience, with a stronger effect observed for individuals with low resilience (β=3.51, 95% confidence interval [CI] 2.78–4.24 for anxiety and β=14.53, 95% CI 12.43–16.63 for PTSD) than for those with high resilience (β=1.69, 95% CI 0.72–2.65 for anxiety and β=8.33, 95% CI 5.56–11.09 for PTSD). Conclusion When related to the victims, it was found that not only PTSD, but also depression, anxiety, and anger could intensify. Resilience emerged as a potential buffer against these adverse effects, emphasizing its significance in mitigating the psychiatric impact of community trauma.

This paper provides a comprehensive overview of the Cancer Public Library Database (CPLD), established under the Korean Clinical Data Utilization for Research Excellence project (K-CURE). The CPLD links data from four major population-based public sources: the Korea National Cancer Incidence Database in the Korea Central Cancer Registry, cause-of-death data in Statistics Korea, the National Health Information Database in the National Health Insurance Service, and the National Health Insurance Research Database in the Health Insurance Review & Assessment Service. These databases are linked using an encrypted resident registration number. The CPLD, established in 2022 and updated annually, comprises 1,983,499 men and women newly diagnosed with cancer between 2012 and 2019. It contains data on cancer registration and death, demographics, medical claims, general health checkups, and national cancer screening. The most common cancers among men in the CPLD were stomach (16.1%), lung (14.0%), colorectal (13.3%), prostate (9.6%), and liver (9.3%) cancers. The most common cancers among women were thyroid (20.4%), breast (16.6%), colorectal (9.0%), stomach (7.8%), and lung (6.2%) cancers. Among them, 571,285 died between 2012 and 2020 owing to cancer (89.2%) or other causes (10.8%). Upon approval, the CPLD is accessible to researchers through the K-CURE portal. The CPLD is a unique resource for diverse cancer research to investigate medical use before a cancer diagnosis, during initial diagnosis and treatment, and long-term follow-up. This offers expanded insight into healthcare delivery across the cancer continuum, from screening to end-of-life care.

Background: Recently, deep learning techniques have been used in medical imaging studies. We present an algorithm that measures radiologic parameters of distal radius fractures using a deep learning technique and compares the predicted parameters with those measured by an orthopedic hand surgeon. Methods: We collected anteroposterior (AP) and lateral X-ray images of 634 wrists in 624 patients with distal radius fractures treated conservatively with a follow-up of at least 2 months. We allocated 507 AP and 507 lateral images to the training set (80% of the images were used to train the model, and 20% were utilized for validation) and 127 AP and 127 lateral images to the test set. The margins of the radius and ulna were annotated for ground truth, and the scaphoid in the lateral views was annotated in the box configuration to determine the volar side of the images. Radius segmentation was performed using attention U-Net, and the volar/dorsal side was identified using a detection and classification model based on RetinaNet. The proposed algorithm measures the radial inclination, dorsal or volar tilt, and radial height by index axes and points from the segmented radius and ulna. Results: The segmentation model for the radius exhibited an accuracy of 99.98% and a Dice similarity coefficient (DSC) of 98.07% for AP images, and an accuracy of 99.75% and a DSC of 94.84% for lateral images. The segmentation model for the ulna showed an accuracy of 99.84% and a DSC of 96.48%. Based on the comparison of the radial inclinations measured by the algorithm and the manual method, the Pearson correlation coefficient was 0.952, and the intraclass correlation coefficient was 0.975. For dorsal/ volar tilt, the correlation coefficient was 0.940, and the intraclass correlation coefficient was 0.968. For radial height, it was 0.768 and 0.868, respectively. Conclusions The deep learning-based algorithm demonstrated excellent segmentation of the distal radius and ulna in AP and lateral radiographs of the wrist with distal radius fractures and afforded automatic measurements of radiologic parameters.

Background: It is unclear how exposure to and perception of community trauma creates a mental health burden. This study aimed to examine the psychological distress trends among community residents in acute stress reaction, acute stress disorder, and post-traumatic stress disorder phases following the Seoul Halloween crowd crush. Methods: A three-wave repeated cross-sectional survey was conducted with participants after the incident. Analysis of covariance (ANCOVA) with post hoc Bonferroni test was adopted to examine temporal changes in psychological distress and psychological outcomes resulting from media impacts. A two-way ANCOVA was adopted to examine the interaction effects of time and relevance to victims on psychological distress. Results: A total of 807, 1,703, and 2,220 individuals participated in the three waves. Anxiety (estimated mean [standard error of the mean]: 2.28 [0.03] vs. 2.12 [0.02] vs. 2.03 [0.02]; P < 0.001), depression (2.22 [0.03] vs. 2.01 [0.02] vs. 1.90 [0.02]; P < 0.001), and anger (2.70 [0.03] vs. 2.66 [0.02] vs. 2.49 [0.02]; P < 0.001) gradually improved. However, sense of safety initially worsened and did not recover well (2.96 [0.03] vs. 2.75 [0.02] vs. 2.77 [0.02];P < 0.001). The interaction effect of time and relevance to the victim were significant in depression (P for interaction = 0.049), anger (P for interaction = 0.016), and sense of safety (P for interaction = 0.004). Among participants unrelated to the victim, those exposed to graphics exhibited higher levels of anxiety (2.09 [0.02] vs. 1.87 [0.07]; P = 0.002), depression (1.99 [0.02] vs. 1.83 [0.07]; P = 0.020), and anger (2.71 [0.03] vs. 2.47 [0.08]; P = 0.003) at W2 and higher anger (2.49 [0.02] vs. 2.31 [0.06]; P = 0.005) at W3. Conclusion Community residents indirectly exposed to trauma also experienced psychological distress in the early stages after the incident. A significant impact of media which might have served as a conduit for unfiltered graphics and rumors was also indicated.