Background: Acute deterioration of patients in general wards often leads to major adverse events (MAEs), including unplanned intensive care unit transfers, cardiac arrest, or death. Traditional early warning scores (EWSs) have shown limited predictive accuracy, with frequent false positives. We conducted a prospective observational external validation study of an artificial intelligence (AI)-based EWS, the VitalCare - Major Adverse Event Score (VC-MAES), at a tertiary medical center in the Republic of Korea. Methods: Adult patients from general wards, including internal medicine (IM) and obstetrics and gynecology (OBGYN)—the latter were rarely investigated in prior AI-based EWS studies—were included. The VC-MAES predictions were compared with National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) predictions using the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and logistic regression for baseline EWS values. False-positives per true positive (FPpTP) were assessed based on the power threshold. Results: Of 6,039 encounters, 217 (3.6%) had MAEs (IM: 9.5%, OBGYN: 0.26%). Six hours prior to MAEs, the VC-MAES achieved an AUROC of 0.918 and an AUPRC of 0.352, including the OBGYN subgroup (AUROC, 0.964; AUPRC, 0.388), outperforming the NEWS (0.797 and 0.124) and MEWS (0.722 and 0.079). The FPpTP was reduced by up to 71%. Baseline VC-MAES was strongly associated with MAEs (P<0.001). Conclusions The VC-MAES significantly outperformed traditional EWSs in predicting adverse events in general ward patients. The robust performance and lower FPpTP suggest that broader adoption of the VC-MAES may improve clinical efficiency and resource allocation in general wards.

Background: Atopic dermatitis (AD) is a common skin disease with a wide range of symptoms. Due to the rapidly changing treatment landscape, regular updates to clinical guidelines are needed. Objective: This study aimed to update the guidelines for the treatment of AD to reflect recent therapeutic advances and evidence-based recommendations. Methods: The Patient characteristics, type of Intervention, Control, and Outcome framework was used to determine 48 questions related to AD management. Evidence was graded, recommendations were determined, and, after 2 voting rounds among the Korean Atopic Dermatitis Association (KADA) council members, consensus was achieved. Results: This guideline provides treatment guidance on advanced systemic treatment modalities for AD. In particular, the guideline offers up-to-date treatment recommendations for biologics and Janus-kinase inhibitors used in the treatment of patients with moderate to severe AD.It also provides guidance on other therapies for AD, along with tailored recommendations for children, adolescents, the elderly, and pregnant or breastfeeding women. Conclusion KADA’s updated AD treatment guidelines incorporate the latest evidence and expert opinion to provide a comprehensive approach to AD treatment. The guidelines will help clinicians optimize patient-specific therapies.

Background: Atopic dermatitis (AD) is a common skin disease with a wide range of symptoms. Due to the rapidly changing treatment landscape, regular updates to clinical guidelines are needed. Objective: This study aimed to update the guidelines for the treatment of AD to reflect recent therapeutic advances and evidence-based practices. Methods: The Patient characteristics, type of Intervention, Control, and Outcome framework was used to determine 48 questions related to AD management. Evidence was graded, recommendations were determined, and, after 2 voting rounds among the Korean Atopic Dermatitis Association (KADA) council members, consensus was achieved. Results: The guidelines provide detailed recommendations on foundational therapies, including the use of moisturizers, cleansing and bathing practices, allergen avoidance, and patient education. Guidance on topical therapies, such as topical corticosteroids and calcineurin inhibitors, is also provided to help manage inflammation and maintain skin barrier function in patients with AD. Additionally, recommendations on conventional systemic therapies, including corticosteroids, cyclosporine, and methotrexate, are provided for managing moderate to severe AD. Conclusion KADA’s updated AD guidelines offer clinicians evidence-based strategies focused on basic therapies, topical therapies, and conventional systemic therapies, equipping them to enhance quality of care and improve patient outcomes in AD management.

Background: An increased incidence of hair loss disorders has been noted among patients with coronavirus disease 2019 (COVID-19) and individuals vaccinated against COVID-19. However, research involving large populations on this topic is lacking. Objective: To investigate the risks associated with developing hair loss disorders in patients with COVID-19 and individuals vaccinated against COVID-19. Methods: This nationwide, population-based, cross-sectional study included patients diagnosed with COVID-19 and healthy individuals without a history of COVID-19 infection registered in the Korean National Health Insurance Service (NHIS) database between January 1, 2021, and December 31, 2021. COVID-19 infection and vaccine databases were integrated using this NHIS database. The odds ratios of hair loss disorders were compared using multivariate logistic regression models. Results: COVID-19 infection was associated with an increased risk of total alopecia (adjusted odds ratio [aOR], 1.076; 95% confidence interval [CI], 1.002–1.156), although this association was not significant after propensity score matching. No significant associations were found between COVID-19 infection and alopecia areata or telogen effluvium. However, COVID-19 vaccination was positively correlated with total alopecia (aOR, 1.266; 95% CI, 1.191–1.346), alopecia areata (aOR, 1.243; 95% CI, 1.154–1.339), and telogen effluvium (aOR, 1.495; 95% CI, 1.133–1.974). Conclusion COVID-19 vaccination was positively correlated with hair loss disorders but not COVID-19 infection. However, given the advantages of vaccines in reducing COVID-19 mortality and morbidity, alopecia may be relatively reversible and less severe. Physicians need to understand the benefits and possible side effects of the COVID-19 vaccine.

Background: TP53 mutations are associated with poor prognosis in myelodysplastic neoplasm (MDS) and AML. The updated 5th WHO classification and International Consensus Classification (ICC) categorize TP53-mutated MDS and AML as unique entities. We conducted a multicenter study in Korea to investigate the characteristics of TP53-mutated MDS and AML, focusing on diagnostic aspects based on updated classifications. Methods: This study included patients aged ≥ 18 yrs who were diagnosed as having MDS(N = 1,244) or AML (N = 2,115) at six institutions. The results of bone marrow examination, cytogenetic studies, and targeted next-generation sequencing, including TP53, were collected and analyzed. Results: TP53 mutations were detected in 9.3% and 9.2% of patients with MDS and AML, respectively. Missense mutation was the most common, with hotspot codons R248/ R273/G245/Y220/R175/C238 accounting for 25.4% of TP53 mutations. Ten percent of patients had multiple TP53 mutations, and 78.4% had a complex karyotype. The median variant allele frequency (VAF) of TP53 mutations was 41.5%, with a notable difference according to the presence of a complex karyotype. According to the 5th WHO classification and ICC, the multi-hit TP53 mutation criteria were met in 58.6% and 75% of MDS patients, respectively, and the primary determinants were a TP53 VAF > 50% for the 5th WHO classification and the presence of a complex karyotype for the ICC. Conclusions Collectively, we elucidated the molecular genetic characteristics of patients with TP53-mutated MDS and AML, highlighting key factors in applying TP53 mutation-related criteria in updated classifications, which will aid in establishing diagnostic strategies.

Background: An international reference measurement laboratory network for creatinine (Cr) is lacking; therefore, Korea developed an independent evaluation and certification system. The in vitro diagnostics (IVD) certification program, launched in 2017, formed part of a broader Cr standardization initiative intended to enhance accuracy at the manufacturing stage. Methods: The program was designed to evaluate analytical systems, including all reagent lots, calibrators, and instrument models, twice annually. Bias, imprecision, total error (TE), and linearity were evaluated based on established acceptance criteria. A post-certification process allows submission for a second challenge and validation of corrective actions. Results: Between 2017 and 2023, 489 analytical systems were evaluated. Average acceptance rates for bias, imprecision, TE, and linearity were 70.8%, 95.9%, 87.7%, and 87.8%, respectively. The lowest acceptance rate for bias evaluation was 8.7% for the kinetic Jaffe method without compensation in 2018. Over the 7-year period, the mean absolute percentage bias (absBias%), coefficient of variation (CV), and TE were 4.62%, 1.37%,and 7.29%, respectively. The highest absBias% (7.94%) was observed in the 0.0 ≤ Cr < 1.0target value range. Since 2019, a consistent reduction in absBias% has been observed. Conclusions This program is a pioneering response to the absence of a global certification program for Cr assays. It offers significant advantages, including comprehensive evaluations, fee-free participation, and a robust post-certification process. Continuous participation and improvement efforts by manufacturers have contributed to enhanced accuracy in Cr assays.

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.

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.