Background: Large language models (LLMs) have the potential for clinical decision support; however, their use in specific tasks, such as determining the RhD blood type for transfusion, remains underexplored. Therefore, we evaluated the accuracy of six LLMs in addressing RhD blood type-related issues in Korean healthcare. Methods: Fifteen multiple-choice and true/false questions, based on real-world transfusion scenarios and reviewed by specialists, were developed. The questions were administered twice to six LLMs (Clova X, Gemini 1.0, Gemini 1.5, ChatGPT-3.5, GPT-4.0, and GPT-4o) in both Korean and English. Results were compared against the performance of 22 transfusion medicine experts. For particularly challenging questions, prompt engineering was applied, and the questions were reevaluated. Results: GPT-4o demonstrated the highest accuracy rate in Korean (0.6), with significant differences compared with those of Clova X and Gemini (P < 0.05). In English, the results were similar across all models. The transfusion experts achieved a higher accuracy rate (0.8). Among the five questions subjected to prompt engineering, only GPT-4o correctly responded to one, whereas the other models failed. All LLM models changed their responses or did not respond when the same question was repeated. Conclusions GPT-4o showed the best overall performance among the models tested and may be beneficial in RhD blood product transfusion decision-making. However, its performance suggests that it may serve best in a supportive role rather than as a primary decision-making tool.

Mycophenolate mofetil (MMF) is usually prescribed with a reduced fixed dose in Asian kidney transplant recipients (KTRs). However, the clinical efficacy and safety of the fixed dose have not yet been investigated via therapeutic drug monitoring. We evaluated whether reduced fixed-dose MMF is an optimal dosing strategy to achieve the therapeutic target of mycophenolic acid (MPA) exposure in Korean KTRs. Methods: This open-label, prospective study enrolled 50 de novo KTRs prescribed with tacrolimus, corticosteroid, and fixed-dose MMF (1.0–1.5 g/day). The trough level (C0) and area under the curve (AUC0–12 hr) of MPA were measured at 1 and 24 weeks after kidney transplantation (KT). The relationship of body weight (BW)-adjusted MMF dose with MPA C0 and MPA AUC0–12 hr was assessed using linear regression analysis. Results: The initial fixed dose of MMF of 1.44 ± 0.16 g/day was adjusted in 24 patients (48.0%) and then reduced to a mean dose of 1.19 ± 0.31 g/day at 24 weeks after KT. Most patients (≥84.0%) attained the minimum required MPA C0 of 1.0 μg/mL and MPA AUC0–12 hr of 30 μg × hr/mL at 1 and 24 weeks. The BW-adjusted MMF dose demonstrated significant positive correlations with MPA C0 and MPA AUC0– 12 hr at 1 and 24 weeks after KT. Moreover, 14 patients (28.0%) reported MPA-related adverse events that were predictable based on MPA AUC0–12 hr (cutoff level, 46.4 μg × hr/mL). Conclusion: The current reduced fixed-dose MMF strategy can help achieve the therapeutic target of MPA exposure in tacrolimus- treated Korean KTRs during the early posttransplant period.

Background: Calcineurin inhibitor (CNI) toxicity is a significant cause of graft dysfunction in kidney transplant recipients, yet distinguishing it from acute rejection (AR) and acute tubular necrosis (ATN) remains challenging. This study investigated the use of urinary mRNA biomarkers as a noninvasive tool for identifying CNI toxicity. Methods: We retrospectively enrolled 110 kidney transplant recipients and classified them into four groups based on pathological findings: stable graft function (n=35), CNI toxicity (n=25), AR (n=30), and ATN (n=20). Candidate biomarkers were selected using the GEO database. Urinary mRNA was extracted from cell pellets, reverse-transcribed, and quantified by real-time polymerase chain reaction. Results: Estimated glomerular filtration rates were comparable among the CNI toxicity, AR, and ATN groups. Four transcripts (LTF, NNMT, WFDC2, and HIF1A) were identified as candidate biomarkers. Urinary mRNA levels of LTF, NNMT, and HIF1A were significantly lower in the CNI toxicity group than the AR group. NNMT and HIF1A levels were also significantly lower than those observed in the ATN group. In contrast, WFDC2 levels did not differ significantly across groups. A three-gene signature (LTF, NNMT, and HIF1A) effectively differentiated CNI toxicity from AR and ATN (area under the curve [AUC], 0.867;95% confidence interval [CI], 0.787–0.947) and significantly enhanced the diagnostic performance of the clinical variable-based model (AUC increased from 0.776; 95% CI, 0.660–0.892, to 0.934; 95% CI, 0.881–0.986). Conclusions Urinary mRNA levels of LTF, NNMT, and HIF1A may serve as useful biomarkers for identifying CNI toxicity in kidney transplant recipients with graft dysfunction.

Background: Flow cytometric immunophenotyping of hematolymphoid neoplasms (FCIHLN) is essential for diagnosis, classification, and minimal residual disease (MRD) monitoring. FCI-HLN is typically performed using in-house protocols, raising the need for standardization. Therefore, we surveyed the current status of FCI-HLN in Korea to obtain fundamental data for quality improvement and standardization. Methods: Eight university hospitals actively conducting FCI-HLN participated in our survey.We analyzed responses to a questionnaire that included inquiries regarding test items, reagent antibodies (RAs), fluorophores, sample amounts (SAs), reagent antibody amounts (RAAs), acquisition cell number (ACN), isotype control (IC) usage, positiveegative criteria, and reporting. Results: Most hospitals used acute HLN, chronic HLN, plasma cell neoplasm (PCN), and MRD panels. The numbers of RAs were heterogeneous, with a maximum of 32, 26, 12, 14, and 10 antibodies used for acute HLN, chronic HLN, PCN, ALL-MRD, and multiple myeloma-MRD, respectively. The number of fluorophores ranged from 4 to 10. RAs, SAs, RAAs, and ACN were diverse. Most hospitals used a positive criterion of 20%, whereas one used 10% for acute and chronic HLN panels. Five hospitals used ICs for the negative criterion. Positiveegative assignments, percentages, and general opinions were commonly reported. In MRD reporting, the limit of detection and lower limit of quantification were included. Conclusions This is the first comprehensive study on the current status of FCI-HLN in Korea, confirming the high heterogeneity and complexity of FCI-HLN practices. Standardization of FCI-HLN is urgently needed. The findings provide a reference for establishing standard FCI-HLN guidelines.

Background: Considering the interactions between heavy metals, a comprehensive evaluation of the effects of exposure to various types of co-interacting heavy metals on health is required.This study assessed the association between dyslipidemia markers and blood mercury, lead, cadmium, iron, zinc, and nickel levels in residents of an abandoned refinery plant. Methods: A total of 972 individuals (exposed group: 567, control group: 405) living near the Janghang refinery plant in the Republic of Korea were included. Blood mercury, lead, cadmium, iron, zinc, nickel, cholesterol, and triglyceride levels were measured. The combined effect of the six heavy metals on dyslipidemia markers was evaluated using a Bayesian kernel machine regression (BKMR) model and compared with the results of a linear regression analysis. The BKMR model results were compared using a stratified analysis of the exposed and control groups. Results: In the BKMR model, the combined effect of the six heavy metals was significantly associated with total cholesterol (TC) levels both below the 45th percentile and above the 55th percentile in the total population. The combined effect range between the 25th and 75th percentiles of the six metals on TC levels was larger in the exposed group than that in the total population. In the control group, the combined effects of the changes in concentration of the six heavy metals on the TC concentration were not statistically significant. Conclusion These results suggest that the cholesterol levels of residents around the Janghang refinery plant may be elevated owing to exposure to multiple heavy metals.

Purpose: Plasma circulating tumor DNA (ctDNA) could reflect the genetic alterations present in tumor tissues. However, there is little information about the clinical relevance of cell-free DNA genotyping in peripheral T-cell lymphoma (PTCL). Materials and Methods: After targeted sequencing plasma cell-free DNA of patients with various subtypes of PTCL (n=94), we analyzed the mutation profiles of plasma ctDNA samples and their predictive value of dynamic ctDNA monitoring for treatment outcomes. Results: Plasma ctDNA mutations were detected in 53 patients (56%, 53/94), and the detection rate of somatic mutations was highest in angioimmunoblastic T-cell lymphoma (24/31, 77%) and PTCL, not otherwise specified (18/29, 62.1%). Somatic mutations were detected in 51 of 66 genes that were sequenced, including the following top 10 ranked genes: RHOA, CREBBP, KMT2D, TP53, IDH2, ALK, MEF2B, SOCS1, CARD11, and KRAS. In the longitudinal assessment of ctDNA mutation, the difference in ctDNA mutation volume after treatment showed a significant correlation with disease relapse or progression. Thus, a ≥ 1.5-log decrease in genome equivalent (GE) between baseline and the end of treatment showed a significant association with better survival outcomes than a < 1.5-log decrease in GE. Conclusion Our results suggest the clinical relevance of plasma ctDNA analysis in patients with PTCL. However, our findings should be validated by a subsequent study with a larger study population and using a broader gene panel.

Purpose: This retrospective study aimed to determine the number of times the ultrasound-guided attenuation parameter (UGAP) should be measured during the evaluation of hepatic steatosis. Methods: Patients with suspected nonalcoholic fatty liver disease who underwent two UGAP repetition protocols (six-repetition [UGAP_6] and 12-repetition [UGAP_12]) and measurement of the controlled attenuation parameter (CAP) using transient elastography between October 2020 and June 2021 were enrolled. The mean attenuation coefficient (AC), interquartile range (IQR)/median, and coefficient of variance (CV) of the two repetition protocols were compared using the paired t test. Moreover, the diagnostic performances of UGAP_6 and UGAP_12 were compared using the area under the receiver operating characteristic (AUROC) curve, considering the CAP value as a reference standard. Results: The study included 160 patients (100 men; mean age, 50.9 years). There were no significant differences between UGAP_6 and UGAP_12 (0.731±0.116 dB/cm/MHz vs. 0.734±0.113 dB/cm/MHz, P=0.156) and mean CV (7.6±0.3% vs. 8.0±0.3%, P=0.062). However, the mean IQR/median of UGAP_6 was significantly lower than that of UGAP_12 (8.9%±6.0% vs. 9.8%±5.2%, P=0.012). In diagnosing the hepatic steatosis stage, UGAP_6 and UGAP_12 yielded comparable AUROCs (≥S1, 0.908 vs. 0.897, P=0.466; ≥S2, 0.883 vs. 0.897, P=0.126; S3, 0.832 vs. 0.834, P=0.799). Conclusion UGAP had high diagnostic performance in diagnosing hepatic steatosis, regardless of the number of repetitions (six repetitions vs. 12 repetitions), with maintained reliability. Therefore, six UGAP measurements seem sufficient for evaluating hepatic steatosis using UGAP.

Purpose: Analysis of circulating tumor DNA (ctDNA) in blood could allow noninvasive genetic analysis of primary tumors. Although there have been unmet needs for noninvasive methods in patients with primary central nervous system lymphoma (PCNSL), it is still not determined whether plasma ctDNA analysis could be useful for patients with PCNSL. Materials and Methods: Targeted deep sequencing of 54 genes was performed in cell-free DNA isolated from plasma samples collected pretreatment, during treatment, and at the end of treatment in 42 consecutively diagnosed PCNSL patients between January 2017 and December 2018. Results: Targeted sequencing of plasma cell-free DNA detected somatic mutations representing ctDNA in 11 cases (11/41, 27%). The detection of ctDNA was not related to the concentration of cell-free DNA or tumor volume. The mutation profiles of these 11 cases varied between patients. The most frequently mutated gene was PIM1 (4/11, 36.4%), whereas KMT2D, PIK3CA, and MYD88 were each observed in three patients (3/11, 27%). The mutations of 13 genes were concordantly found in primary tumor tissue and plasma ctDNA, giving a detection sensitivity of 45%. During the serial tracking of seven patients with complete response, the disappearance of ctDNA mutations was found in four patients, whereas three patients had detected ctDNA mutation at the end of treatment. Conclusion The plasma ctDNA mutation analysis still has limited value for surveillance and predicting treatment outcomes of PCNSL because the detection efficiency was lower than other systemic lymphomas. Thus, analytical platforms should be improved to overcome anatomical hurdles associated with PCNSL.

Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients.

Background: Although particulate matter likely provokes inflammatory reactions in those with chronic skin disorders like atopic dermatitis, no study has examined the relationship between particulate matter and psoriasis exacerbation. Objective: This study evaluated possible associations between particulate matter and hospital visits for psoriasis patients in 7 major cities in South Korea. Methods: We investigated the relationship between psoriasis and particulate matter. To do this, we used psoriasis patient data from the Korean National Health Insurance Service database. In addition, PM 10 and PM 2.5 concentration data spanning a 3-year time frame were obtained from the Korea Environment Corporation. Results: A pattern analysis generated by the sample cross-correlation function and time series regression showed a correlation between particulate matter concentration and the number of hospital visits by psoriasis patients. However, the prewhitening method, which minimizes the effects of other variables besides particulate matter, revealed no correlation between the two. Conclusion This study suggests that particulate matter has no impact on hospital visit frequency among psoriasis patients in South Korean urban areas.