Background: Understanding disparities in severe coronavirus disease 2019 (COVID-19) outcomes between people with disabilities (PwD) and people without disabilities (PwoD) is crucial, particularly when considering the heterogeneity within PwD and age differences.This study aimed to compare severe COVID-19 outcomes including deaths between PwD and PwoD with analyses stratified by age group and further examined by disability type. Methods: This retrospective, population-based cohort study used linked data from national COVID-19 cases and health insurance for individuals aged ≥ 19 years with COVID-19 from January 2020 to October 2022 in the Republic of Korea. Severe outcomes included severe cases and deaths, with logistic regression analysis of the risk disparities between PwD and PwoD based on age group and disability types. The subgroup analysis considered epidemic periods, accounting for the severe acute respiratory syndrome coronavirus 2 variant circulation. Results: The risk of severe COVID-19 outcomes and deaths among PwD varied by age and disability type. While severe outcomes were most prevalent in the older age groups for both PwD and PwoD, younger PwD faced a markedly higher risk—up to eightfold—compared to PwoD. The risk of disability status was greater than that of comorbidities in the 19–39 age group. Among disability types, individuals with internal organs-related and intellectual disabilities showed higher risk disparities with PwoD in severe outcomes than other types of disabilities. Throughout the pandemic, the disparity in death risk remained similar, with a slight increase in disparity during the omicron period for all severe outcomes in the age groups 19–39 and 40–64 years. Conclusion Prioritizing younger PwD, along with older age groups and people with comorbidities, is crucial in addressing public health crises. Risk-based prioritization is important to reduce overall risk. This includes prioritizing people with nternal organs-related and intellectural disabilities, who face higher health risks among PwD during a pandemic when resources are limited and time is of the essence.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Purpose: To investigate whether a new phospholipid-releasing soft contact lens can improve symptoms of dry eyes. Methods: The study used 2.5-3.0 kg New Zealand rabbits including both normal non-dry eye rabbits and dry eye rabbits, the latter having undergone electrocauterization of the meibomian glands to block the gland orifices. Each rabbit wore a control contact lens on one eye and a phospholipid-releasing contact lens on the other eye daily. Phospholipid-releasing and control contact lenses were provided by NEOVISION Co., Ltd. The parameters assessed included tear film break-up time, tear osmolarity, ocular surface staining, and central corneal thickness. After the experiment, the rabbits were euthanized and their conjunctival tissue was stained with Periodic Acid Schiff (PAS) to observe conjunctival goblet cells. Results: In both dry eye and normal non-dry eye rabbits, tear film break-up time was longer and tear osmolarity was lower when using the phospholipid-releasing contact lens compared to the control contact lens. The ocular surface remained unstained in normal non-dry eye rabbits while staining was observed in dry eye rabbits. There was no significant difference in central corneal thickness between the control and phospholipid-releasing contact lenses in either group. PAS staining showed no difference in conjunctival goblet cell density between the two lens types in normal non-dry eye rabbits. However, in dry eye rabbits, the conjunctival goblet cell density tended to be slightly higher with the phospholipid-releasing contact lens compared to the control lens. Conclusions Phospholipid-releasing contact lenses may help reduce dry eye symptoms and minimize contact lens-related complications by stabilizing the tear film and lowering tear osmolarity.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

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: Understanding disparities in severe coronavirus disease 2019 (COVID-19) outcomes between people with disabilities (PwD) and people without disabilities (PwoD) is crucial, particularly when considering the heterogeneity within PwD and age differences.This study aimed to compare severe COVID-19 outcomes including deaths between PwD and PwoD with analyses stratified by age group and further examined by disability type. Methods: This retrospective, population-based cohort study used linked data from national COVID-19 cases and health insurance for individuals aged ≥ 19 years with COVID-19 from January 2020 to October 2022 in the Republic of Korea. Severe outcomes included severe cases and deaths, with logistic regression analysis of the risk disparities between PwD and PwoD based on age group and disability types. The subgroup analysis considered epidemic periods, accounting for the severe acute respiratory syndrome coronavirus 2 variant circulation. Results: The risk of severe COVID-19 outcomes and deaths among PwD varied by age and disability type. While severe outcomes were most prevalent in the older age groups for both PwD and PwoD, younger PwD faced a markedly higher risk—up to eightfold—compared to PwoD. The risk of disability status was greater than that of comorbidities in the 19–39 age group. Among disability types, individuals with internal organs-related and intellectual disabilities showed higher risk disparities with PwoD in severe outcomes than other types of disabilities. Throughout the pandemic, the disparity in death risk remained similar, with a slight increase in disparity during the omicron period for all severe outcomes in the age groups 19–39 and 40–64 years. Conclusion Prioritizing younger PwD, along with older age groups and people with comorbidities, is crucial in addressing public health crises. Risk-based prioritization is important to reduce overall risk. This includes prioritizing people with nternal organs-related and intellectural disabilities, who face higher health risks among PwD during a pandemic when resources are limited and time is of the essence.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objective: To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea. Materials and Methods: This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value. Results: A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older. Conclusion Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.

Objectives: We analyzed the demographic and clinical characteristics of patients diagnosedwith coronavirus disease 2019 (COVID-19), focusing specifically on severe/critical cases, andassessed the trends and rates of severity and fatality among these patients in the Republic of Korea. Methods: Clinical data on patients with COVID-19 from January 20, 2020 to August 30, 2023were collected from the Korea Disease Control and Prevention Agency’s database. We identified patients who progressed to severe/critical conditions and analyzed their demographic and clinical profiles. Severity and fatality rates were calculated and compared annually to track thedisease progression over time. Results: During the surveillance period, 34,572,554 COVID-19 cases were confirmed, among whom 38,112 (0.11%) progressed to severe/critical conditions. Most severe/critical cases occurred in individuals aged ≥60 years, with a notable increase in patients aged ≥80 years from 2022.The overall severity rate was 0.19%, with a fatality rate of 0.10%. However, the severity of cases gradually diminished during the study period. In 2022, the severity and fatality rates decreased to 0.14% and 0.09%, respectively. In 2023, while the severity rate remained stable at 0.15%, thefatality rate further decreased to 0.06%. Notably, throughout the study period, individuals aged ≥80 years had a significantly higher severity rate (2.44%), with a fatality rate of 1.75%. Conclusion These findings underscore the importance of prioritizing protection and management strategies for older adults and high-risk groups to mitigate the impact ofCOVID-19. Continued surveillance and analysis are essential to effectively control COVID-19 and minimize its burden on public health.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.