Background/Aims: This study investigated the clinical efficacy of low-dose mepolizumab (100 mg) in controlling severe eosinophilic asthma, aiming to induce eosinophilic granulomatosis with polyangiitis (EGPA) remission and reduce systemic steroid usage. Additionally, we constructed a basic frame for our longitudinal EGPA cohort by collecting serial blood samples before, during, and after mepolizumab treatment in EGPA patients. Methods: We conducted a 2-year prospective observational cohort study in patients with uncontrolled severe eosinophilic asthma and refractory EGPA who used systemic steroids (≥ 7.5 mg/day of prednisolone) or other immunosuppressant drugs for at least 6 months. All patients were treated with 100 mg of mepolizumab every 4 weeks for 1 year to control severe eosinophilic asthma and then were followed for an additional 1 year to monitor their disease course. We analyzed total systemic steroid use and EGPA remission/relapse during the study period. Results: Three EGPA patients were included in this study and completed 16 study visits over a 2-year period. After 1 year of treatment with mepolizumab (100 mg monthly), all 3 patients were able to reduce their maintenance dose of systemic steroids, with 2 patients completely discontinuing use. These 2 patients achieved EGPA remission during mepolizumab treatment, and their remission status remained stable for 1 year after they stopped receiving the medication. Conclusions Low-dose mepolizumab treatment demonstrated clinical efficacy in reducing the maintenance dose of systemic steroids required for severe refractory EGPA. While not all patients achieved EGPA remission with low-dose mepolizumab, some did, and their remission persisted even after treatment discontinuation.

Background: Current guidelines recommend factor IIa- or Xa-specific inhibitors over warfarin analogs for preventing thromboembolic stroke in patients with atrial fibrillation (AF).However, their plasma concentrations in Korean patients are not well understood. Methods: We conducted a single-center laboratory study to determine the distribution ranges of peak and trough concentrations of three factor Xa inhibitors (apixaban, edoxaban, and rivaroxaban) prescribed for preventing strokes in patients with AF. Patients receiving one of these drugs and undergoing blood specimen collection for laboratory tests were screened. Blood specimens were obtained from patients who had adhered to the prescribed drug regimen consistently for at least 1 week. Drug plasma concentrations were measured using heparin liquid-reagent technology-based anti-Xa chromogenic assays. Results: We selected 459 patients who were taking standard or on-label-reduced doses of apixaban (N = 252), edoxaban (N = 182), or rivaroxaban (N = 25). The 5th–95th percentile ranges of the peak concentrations were 84–414 ng/mL (apixaban), 72–424 ng/mL (edoxaban), and 97–517 ng/mL (rivaroxaban). The respective 5th–95th percentile ranges of the trough concentrations were 44–237 ng/mL, 23–93 ng/mL, and 13–219 ng/mL. Approximately 19.6% (apixaban), 33.3% (edoxaban), and 64.0% (rivaroxaban) of patients in each group had peak concentrations out of the predicted distribution ranges based on pharmacokinetic data. Approximately 7.3%, 52.8%, and 8.3% of patients had trough concentrations out of the predicted distribution ranges. Conclusions A considerable proportion of Korean patients with AF taking factor Xa inhibitors may require population-specific reference ranges to guide therapeutic monitoring.

Background: Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is among the most important multidrug-resistant pathogens causing bloodstream infections (BSIs).Cefotaximase (CTX-M) enzymes are the most common and highly diverse ESBL family in E.coli. CTX-M-15 in group CTX-M-1 and CTX-M-14 in group CTX-M-9 are the most extensively disseminated enzymes. Multidrug-resistant E. coli strains complicate empirical therapy and increase healthcare burden globally and in Korea. We investigated the molecular epidemiology, sequence types (STs), and ESBL genotypes of E. coli bloodstream isolates in Korea and identified clinical risk factors for cefotaxime resistance. Methods: We collected all non-duplicated isolates of E. coli and related clinical information from patients with BSIs at eight sentinel hospitals in the Korean Global Antimicrobial Resistance Surveillance System (Kor-GLASS) collection network during 2017–2021. Duplicate isolates were removed to ensure representativeness of the data. Antimicrobial susceptibility was tested using disk diffusion tests, and multilocus sequence typing and betalactamase genotyping were performed. Results: Among 9,232 E. coli blood isolates, resistance rates to cefotaxime and ceftazidime were 36.4% and 11.4%, respectively. Among the clinical factors, age > 65 yrs (adjusted odds ratio [aOR], 1.36), hospital-origin infection (aOR, 2.55), and admission type (intensive care unit [ICU] vs. general ward; aOR, 1.34) were significant cefotaxime resistance risk factors. ST131 was the most prevalent among cefotaxime-resistant E. coli (64.8%, 2,180/3,363), followed by ST1193 (5.3%, N = 177), and ST69 (5.1%, N = 170).ST131, ST648, ST405, and ST410 cefotaxime-resistant E. coli isolates frequently harbored blaCTX-M-15, whereas ST1193 and ST68 showed a high proportion of blaCTX-M-27 carriers, and most ST457 and ST5150 isolates carried blaCTX-M-55. Conclusions Continuous monitoring of ESBL-producing E. coli is required to prevent further dissemination, guide empirical therapy, inform infection control policies, and ensure early detection of multidrug-resistant clones with the potential for widespread transmission.

Background: As nationwide government-led whole-genome sequencing (WGS) projects progress, optimizing the clinical integration of large-scale WGS results is crucial. We explored how the initial analysis from Korea’s First WGS Pilot Study for Rare Diseases was applied in clinical practice, and then we reanalyzed the data comprehensively at Samsung Medical Center (SMC) Seoul, Korea. Methods: A prospective cohort study designed to collect WGS data under a Korean national initiative was conducted from August 2020 to December 2021. We focused on patients with rare diseases recruited from 16 university hospitals. The participants included 5,000 individuals (2,200 probands and 2,800 family members). The initial WGS data and diagnostic reference reports (from 682 probands and 484 family members), generated based on the First Korean WGS Pilot Study for Rare Diseases, were subsequently reanalyzed by SMC. Results: The initial analysis of the First Korean WGS Pilot Study data revealed a diagnostic rate of 17%. Upon receiving these results, the SMC conducted two rounds of reanalysis, increasing the diagnostic rate from 15% in the first analysis, to 18% in the second, and finally to 24% in the third (P = 1.6 × 10 −5 ). Key factors in improving the genetic diagnosis included increased detection of novel (likely) pathogenic variants (P = 1.0 × 10 −4 ), improved diagnostic rates with larger family recruitment (P = 0.004), and refined clinical information for more precise genotype–phenotype correlation analysis (40%). Conclusions Although national WGS projects lay a foundation for rare disease diagnosis, hospital-level reanalysis and multidisciplinary collaborations are crucial for optimizing diagnostic outcomes.

Background: The 2020 European Society of Cardiology (ESC) 0-hr/1-hr algorithm using high-sensitivity cardiac troponin I (hs-cTnI) for non-ST-segment elevation acute coronary syndrome (NSTE-ACS) aims at early diagnosis and shorter emergency department (ED) stays. While this algorithm has been well-established in controlled studies, real-world implementation remains challenging. We evaluated the algorithm’s clinical performance and risk stratification capability in patients with chest pain or discomfort. Methods: We measured hs-cTnI in 4,678 patients suspected of NSTE-ACS between August 2022 and July 2023, using an Atellica IM Analyzer (Siemens Healthineers, Erlangen, Germany). We categorized patients into rule-in, observe, or rule-out groups according to the algorithm and assessed its diagnostic performance for NSTE-ACS. The final diagnosis of NSTE-ACS was adjudicated by two independent physicians. Additionally, we evaluated 30-day all-cause mortality, hazard risk, and ED length of stay across the three groups. Results: The algorithm categorized 3,408 (72.9%), 573 (12.2%), and 697 (14.9%) patients into the rule-out, observe, and rule-in groups, respectively. Among 90 patients diagnosed as having NSTE-ACS, none were falsely categorized into the rule-out group. Survival analysis revealed significant differences (P < 0.001), with Cox hazard ratios of 2.38 (95% confidence interval: 1.20–4.71) and 6.39 (3.45–11.86) in the observe and rule-in groups, respectively. ED stays shortened in the order of rule-out, observe, and rule-in groups (P < 0.001). Conclusions The 2020 ESC 0-hr/1-hr algorithm demonstrates excellent diagnostic accuracy without false rule-outs and effective risk stratification, and contributes to efficient ED throughput, supporting its clinical utility in real-world emergency settings.

Flow cytometric lymphocyte subset analysis (FCLSA) is essential for assessing immune status across various diseases and clinical settings. We surveyed current clinical laboratory practices related to FCLSA to establish a baseline reference for future standardization in Korea. Nine university hospitals actively performing FCLSA responded to the 22-question survey, which covered seven categories of laboratory practice. These hospitals used commercial reagent antibody kits from either Beckton Dickinson Biosciences (N = 4) or Beckman Coulter Diagnostics (N = 5). Most hospitals performed daily instrument setup and scheduled maintenance every 2–6 months. Two levels of commercial quality control materials were routinely used each day. Sample and reagent antibody volumes varied across hospitals, even when the same reagent kit was used. Acquired cell counts ranged from 5 × 10 3 to 5 × 10 4 cells, with two hospitals adjusting counts based on the cell type analyzed. Most laboratories reported percentages and general opinions; some additionally reported white blood cell and lymphocyte counts, along with lymphocyte percentages. This is the first comprehensive survey on the clinical laboratory practice of FCLSA in Korea.Standardization of FCLSA should be accelerated to ensure reliable and reproducible results.

Background: Recent advancements in large language models (LLMs) have accelerated their integration into clinical domains, including laboratory medicine. The performance of LLMs in answering board-level laboratory medicine questions has not been comprehensively evaluated. Given the importance of diagnostic accuracy in this field, rigorous and objective evaluations of LLM capabilities are essential. Methods: We assessed 12 LLMs from OpenAI, Anthropic, and Google using 320 Korean Residency Examination questions (2021–2024) spanning six laboratory medicine subspecialties. Standardized prompts were provided via their application programming interfaces under deterministic settings (temperature = 0). Questions were administered thrice to assess response reproducibility. Outputs were compared with validated answers and analyzed for accuracy, reasoning quality, and error typology. Results: Google’s Gemini 2.0 Pro achieved the highest accuracy (80.0%), followed by OpenAI’s GPT-4.5 (77.2%) and Anthropic’s Claude 3.7 Sonnet (74.1%). Accuracy decreased as the difficulty of questions increased (78.0% for easy vs. 45.1% for challenging). Subspecialty performance varied. Al models underperformed on questions on transfusion medicine (mean accuracy: 38.8%), primarily because of limitations in domain-specific and regional knowledge representations. Incorrect answers primarily resulted from reasoning errors. Reproducibility exceeded 95% for most models; however, some residual non-determinism appeared even with greedy decoding (temperature = 0). Conclusions LLMs demonstrated substantial potential for integration into laboratory medicine, particularly in clinical chemistry and immunology. Performance inconsistencies (particularly for high-difficulty questions) and knowledge gaps (notably for transfusion medicine) highlight the necessity for further development—potentially including domain-specific fine-tuning and retrieval-augmented generation integration—and robust expert oversight before clinical application.

Background: Transthyretin amyloidosis, a protein-misfolding disorder characterized by systemic amyloid deposition, can be classified as wild-type transthyretin amyloidosis (ATTRwt) or hereditary transthyretin amyloidosis (ATTRv), depending on the presence of transthyretin (TTR) gene variants. We examined the genetic distribution of TTR variants in Korean patients diagnosed with ATTRv. Methods: We retrospectively reviewed 801 participants who underwent TTR analysis at Samsung Medical Center from 2012 to 2024. The participants were categorized into two groups: in-house probands or relatives, and externally referred probands or relatives. Results: Pathogenic or likely pathogenic TTR variants were detected in 36 of 165 in-house probands (21.8%), among which D38A was the most frequent variant (50.0%; 18/36), followed by M13dup and E89K (8.3% each). Among referred probands, D38A was predominant (54.5%; 12/22), followed by M13dup (22.7%; 5/22). Cardiac amyloid involvement was the most common manifestation, observed in 97.2% (35/36) of in-house probands with ATTRv, followed by peripheral nervous system (PNS; 94.4%) and autonomic nervous system (ANS; 88.9%) involvement. In contrast, ANS involvement was most prevalent among in-house relatives who underwent organ evaluation (61.5%; 24/39), followed by cardiac (52.1%; 25/48) and PNS (48.7%; 19/39) involvement. Five of the eight in-house relatives harboring M13dup (62.5%) showed organ involvement, primarily in the ANS, supporting the pathogenicity of this variant. Conclusions This study provides the largest single-institution dataset of Korean patients with ATTRv, incorporating systematic organ assessments. The predominance of the unique TTR variants D38A and M13dup delineates a distinct genetic landscape that may facilitate accurate and timely diagnosis of ATTRv in the Korean population.

Background: Fusion genes are major drivers of acute leukemia. Conventional diagnostics are limited in detecting the diverse fusions included in recently updated acute leukemia classifications. We evaluated the fusion detection performance of RNA sequencing (RNAseq) compared with that of conventional diagnostics in patients with acute leukemia. Methods: We retrospectively obtained the data of 101 patients with acute leukemia who underwent conventional diagnostics (i.e., karyotyping, FISH, or multiplex reverse transcription PCR) at diagnosis at Samsung Medical Center, Seoul, Korea, between September 2022 and September 2023. Whole RNA-seq was performed using the Illumina Stranded mRNA Prep kit (Illumina, San Diego, CA, USA). The concordance, sensitivity, and specificity of RNA-seq for fusion gene detection were compared with those of conventional diagnostics. Results: RNA-seq helped identify 52 fusion genes in 51 (50.5%) of 101 patients, with detection rates of 40.7%, 70.3%, 37.5%, and 50% in acute myeloid leukemia, B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, and mixed-phenotype acute leukemia, respectively. RNA-seq showed 83.3% sensitivity and 80.8% concordance with conventional diagnostics; it missed eight fusions, likely because of low transcript abundance or enhancer hijacking. RNA-seq also helped clarify three previously unspecified rearrangements and detected 12 fusions (21.4%) in 56 cases that tested negative with conventional diagnostics, including four novel (KMT2A::THAP12 , RUNX1::PRPF19 , MLLT10::UBE2L6, and FUS::ZNF362) and three rare (HNRNPH1::ERG, RUNX1::USP42, and ETV6::NCOA2) fusions. Conclusions This was the first study to evaluate the performance of whole RNA-seq in fusion detection in patients with acute leukemia in Korea. Incorporating RNA-seq into diagnostic workflows may facilitate earlier and more precise therapeutic decisions and improve prognostic assessment in patients with acute leukemia.