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.

With Industry 4.0, big data and artificial intelligence have become paramount in the field of medicine. Electronic health records, the primary source of medical data, are not collected for research purposes but represent real-world data; therefore, they have various constraints. Although structured, laboratory data often contain unstandardized terminology or missing information. The major challenge lies in the lack of standardization of test results in terms of metrology, which complicates comparisons across laboratories. In this review, we delve into the essential components necessary for integrating real-world laboratory data into high-quality big data, including the standardization of terminology, data formats, equations, and the harmonization and standardization of results. Moreover, we address the transference and adjustment of laboratory results, along with the certification for quality of laboratory data. By discussing these critical aspects, we seek to shed light on the challenges and opportunities inherent to utilizing real-world laboratory data within the framework of healthcare big data and artificial intelligence.

Vancomycin, a vital antibiotic for treating gram-positive bacterial infections, requires therapeutic drug monitoring (TDM) because of its substantial pharmacokinetic variability. While traditional TDM relies on steady-state trough concentrations, recent guidelines advocate the area under the concentration–time curve (AUC) as the target index. However, detailed protocols for AUC estimation are lacking, leading to potential discrepancies among institutions. We surveyed medical institutions in Korea regarding vancomycin TDM, including AUC estimation. Nineteen participants responded to the TDM case challenge under three patient scenarios. For an ordinary patient in Case 1, the overall CV for AUC values was 0.4% when both trough and peak concentrations were included in the AUC calculation and 1.9% when utilizing only the trough concentration. For Case 2, an older patient with obesity, the corresponding CV was 6.6%. For Case 3 with multiple trough concentrations, the CV was 15.6%, reflecting variations in the selective use of data. Although the agreements in Case 1 were good, significant variability in AUC estimation was noted in cases involving atypical patient characteristics or old TDM data. Our study provides insight into the current status of vancomycin TDM in Korea and underscores the need for standardized operational protocols for AUC estimation.

Background: Circulating tumor DNA (ctDNA) profiling from peripheral blood allows relatively noninvasive monitoring of solid tumors; however, its utility post-surgery or chemotherapy in colorectal cancer remains underexplored. We evaluated the clinical implications of a ctDNA next-generation sequencing (NGS) panel post-surgery or chemotherapy in patients with colorectal cancer. Methods: We collected samples from 23 patients with colorectal cancer (17 men, median age 65 yrs) at baseline and post-surgery or chemotherapy at the National Cancer Center, Korea, between January 2021 and September 2023. ctDNA was analyzed using an NGS panel including 46 genes, and variant allele frequencies (VAFs) were determined. Followup samples were analyzed using the NGS panel or droplet digital PCR (ddPCR) when probes were available. Clinical status was compared with ctDNA results, and survival was analyzed using a time-dependent Cox model. Results: Mutations were identified in 13 out of 14 patients (92.8%) with stage II/III cancer and in all nine patients (100%) with stage IV cancer. Mutations were detected in KRAS (N = 15, 65%), APC (N = 8, 35%), TP53 (N = 7, 30%), PIK3CA (N = 5, 22%), and RET (N = 4, 17%). A 1% increase in KRAS and TP53 VAFs was associated with 48% and 32% increased mortality risk, respectively. Changes in VAF correlated well with clinical findings. Conclusions The detection of and an increase in KRAS and TP53 VAFs were associated with poor prognosis. ddPCR-based ctDNA monitoring results were comparable to those obtained with the NGS panel. ctDNA monitoring during treatment is clinically informative in managing colorectal cancer.

Background: Genetic alterations play a pivotal role in multiple myeloma (MM) development and therapeutic resistance. Traditionally, the genetic profiling of MM requires invasive bone marrow (BM) procedures; however, these procedures are associated with patient discomfort and cannot fully capture the spatial and temporal heterogeneity of the disease.Therefore, we investigated the clinical implications of liquid biopsy using targeted deep sequencing. Methods: We analyzed the genetic profiles of circulating tumor DNA (ctDNA) by targeted deep sequencing from 102 patients, including those with monoclonal gammopathy of undetermined significance (MGUS, N = 7), smoldering MM (N = 6), and symptomatic MM (N = 89). Results: The number of ctDNA mutations increased with disease progression from MGUS to MM, with averages of 1.0 mutations in MGUS, 1.8 mutations in smoldering MM, and 1.9 mutations in MM, respectively. Shared mutations between BM and ctDNA were more prevalent in MM (68.9%) than in MGUS (25.0%). RAS/RAF and TP53 mutations were significantly enriched in MM ctDNA. Specific mutations were associated with clinical features in patients with MM: hypercalcemia and TET2 (P = 0.006), renal insufficiency and NRAS (P = 0.012), paramedullary myeloma and TP53(P = 0.02), and extramedullary myeloma and NRAS (P = 0.007). TET2 mutations significantly affected 2-yr progression-free survival (hazard ratio = 7.11, P = 0.003). Serial ctDNA profiling accurately predicted treatment response in patients with MM. Conclusions Our findings highlight the potential of liquid biopsy for understanding MM progression and prognosis utilizing a minimally invasive approach, paving the way for its integration into personalized treatment strategies and real-time disease monitoring.

Background: The Xpert MTB/RIF Ultra (Xpert Ultra) was introduced to enhance the sensitivity of tuberculosis detection, particularly in smear-negative cases, compared with its predecessor, Xpert MTB/RIF (Xpert). However, its performance in high-resource, intermediateburden settings remains unassessed. We prospectively compared the diagnostic accuracy of Xpert Ultra and Xpert for detecting Mycobacterium tuberculosis (MTB) and rifampin resistance in Korea. Methods: In total, 309 respiratory specimens were analyzed using both assays. We used two reference standards: mycobacterial culture and a composite reference standard based on clinical diagnosis and treatment decisions. Diagnostic performance, including sensitivity, specificity, and agreement between the two assays, was assessed. Spiking experiments using 13 MTB isolates with known rpoB mutations were performed to evaluate rifampin resistance detection. Results: Xpert Ultra showed increased, albeit not significantly, sensitivity (73.7% vs. 65.8% with culture; 63.8% vs. 53.2% with the composite reference standard) over Xpert. Its specificity was comparable to that of Xpert; however, a few false-positive results were observed among trace- and very low-positives. Among six culture-negative but Xpert Ultra-positive cases, two were clinically diagnosed as tuberculosis. Of the 13 rpoB mutant strains, Xpert correctly detected all mutations in the rifampin resistance-determining region, whereas Xpert Ultra yielded indeterminate results for Q432P and Q429H/L430P/H445Q. Conclusions Xpert Ultra tends to have increased sensitivity; however, it shows potential diagnostic ambiguity associated with trace- or very low-positive results. These findings highlight the importance of clinical correlation, particularly in culture-negative cases. Indeterminate results in certain rpoB mutations require cautious interpretation.

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: Alcoholic liver disease (ALD) includes a wide clinical spectrum from acute alcoholic hepatitis to severe cirrhosis and/or hepatocellular carcinoma. Until now, there has been no report revealing the bleeding tendency of ALD compared to other diseases in liver transplantation (LT). Thus, we analyzed blood loss and transfusion amounts during operation according to the etiologies of liver disease and model for end-stage liver disease (MELD) score. Methods: Out of 874 recipients who underwent LT, a total of 146 patients were excluded by our exclusion criteria. We compared 728 recipients’ baseline characteristics, operation time, blood loss, and transfusion amounts between ALD and nonALD according to MELD score. Results: The number of patients in the ALD group was 130 (17.9%), and 598 (82.1%) in the non-ALD group. The ALD group showed younger age, higher MELD score, and a higher proportion of deceased donor LT than the non-ALD group. Intraoperative blood loss and transfusions of red blood cells (RBCs), fresh frozen plasma, and platelets were significantly higher in the ALD group. When stratified by MELD score (cut-off: 20), ALD patients in both high and low MELD subgroups demonstrated greater blood loss and RBC transfusion requirements, even when international normalized ratio and platelet counts were similar. In multivariate logistic regression analysis, ALD was a significant risk factor for massive transfusion (odds ratio 1.813, 95% confidence interval 1.158–2.840, p=0.009). Conclusion The ALD group showed increased bleeding tendency than the non-ALD group during LT, irrespective of MELD score. This suggests that transplant surgeons should anticipate greater blood loss and ensure adequate transfusion resources during LT for ALD patients.

Background: Fishing is a physically demanding occupation with a high risk of musculoskeletal disabilities (MSDs). Although previous studies have focused on ergonomic risk factors, little attention has been paid to sex differences in the prevalence of MSDs among fishers. This study aimed to assess whether female fishers experience a higher prevalence of MSDs than male fishers and to examine whether this difference persists after adjusting for socioeconomic and occupational factors. Methods: We analyzed cross-sectional data from 898 Korean fishers (513 men and 385 women) who participated in the 2021–2022 Fisher Health Survey. MSDs in the upper extremities, lower back, and knees were defined as scores in the top 25% of the Quick Disabilities of the Arm, Shoulder, and Hand (QuickDASH), Oswestry Disability Index, and Western Ontario and McMaster Universities Arthritis Index Short Form (WOMAC-SF), respectively. Modified Poisson regression was used to calculate the prevalence ratios (PRs) by sex, with stepwise adjustments for age, socioeconomic factors, and occupational factors. Results: Female fishers had significantly higher MSD risk than male fishers across all body regions (fully adjusted PRs: upper extremity, 1.59; lower back, 1.63; knee, 1.44). Sex disparities were most pronounced among those under 60 years of age and remained significant even in older age groups. Conclusions The elevated MSD risk among female fishers persisted despite adjusting for conventional risk factors, suggesting the influence of additional factors such as biological susceptibility, domestic labor, and gendered health reporting. Therefore, MSD prevention strategies should include sex-sensitive multidimensional approaches beyond ergonomic interventions.