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.

While numerous studies have evaluated humoral responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, data on the cellular responses to these vaccines remain sparse. We evaluated T cell responses to ChAdOx1-nCoV-19 and BNT162b2 vaccinations using an interferon gamma (IFN-γ) release assay (IGRA). ChAdOx1-nCoV-19- and BNT162b2-vaccinated participants initially showed stronger T cell responses than unvaccinated controls. The T cell response decreased over time and increased substantially after the administration of a BNT162b2 booster dose. Changes in the T cell response were less significant than those in the anti-receptor-binding domain IgG antibody titer. The study results can serve as baseline data for T cell responses after SARS-CoV-2 vaccination and suggest that the IGRA can be useful in monitoring immunogenicity.

Healthcare workers (HCWs) may be at high risk for exposure to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because of their frequent contact with patients or the direct handling of respiratory samples. We investigated the seroprevalence of SARS-CoV-2 IgG in HCWs in Seoul compared to those in coronavirus disease (COVID-19) patients and community-based individuals to evaluate the antibody response. A total of 358 samples from 348 individuals (155 HCWs, 7 COVID-19 patients, and 186 community-based individuals) were collected from April to November 2020. SARS-CoV-2 IgG was detected in 1 of 155 HCWs (1 of 46 HCWs with direct contact), 7 of 7 COVID-19 patients, and none of the 186 communitybased individuals (95% CI: 0.6%, 0.1 - 3.6%; 100%, 64.5 - 100%; 0.0%, 0.0 - 2.0%, respectively).The single HCW with a positive result showed 2.32 signal-to-cutoff (S/C) and 2.31 S/C at a 3-week interval. Therefore, it was assumed to be a false positive due to autoantibody or medication. The positive samples from 7 patients had a median of 3.79 S/C (range 1.72 - 6.54). The seroprevalence of SARS-CoV-2 IgG in HCWs was very low. The current infection control standard seems to be effective in protecting HCWs from COVID-19.

Background: Neutrophil gelatinase-associated lipocalin (NGAL) is a useful biomarker for acute kidney injury (AKI) prediction. However, studies on whether using both plasma NGAL (PNGAL) and urine NGAL (UNGAL) can improve AKI prediction are limited. We investigated the best approach to predict AKI in high-risk patients when using PNGAL and UNGAL together. Methods: We enrolled 151 AKI suspected patients with one or more AKI risk factors. We assessed the diagnostic performance of PNGAL and UNGAL for predicting AKI according to chronic kidney disease (CKD) status by determining the areas under the receiver operating curve (AuROC). Independent predictors of AKI were assessed using univariate and multivariate logistic regression analyses. Results: In the multivariate logistic regression analysis for all patients (N = 151), Model 2 and 3, including PNGAL (P = 0.012) with initial serum creatinine (S-Cr), showed a better AKI prediction power (R2 = 0.435, both) than Model 0, including S-Cr only (R2 = 0.390). In the non-CKD group (N = 135), the AuROC of PNGAL for AKI prediction was larger than that of UNGAL (0.79 vs 0.66, P = 0.010), whereas in the CKD group (N = 16), the opposite was true (0.94 vs 0.76, P = 0.049). Conclusions PNGAL may serve as a useful biomarker for AKI prediction in high-risk patients. However, UNGAL predicted AKI better than PNGAL in CKD patients. Our findings provide guidance for selecting appropriate specimens for NGAL testing according to the presence of CKD in AKI high-risk patients.

Healthcare workers (HCWs) may be at high risk for exposure to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because of their frequent contact with patients or the direct handling of respiratory samples. We investigated the seroprevalence of SARS-CoV-2 IgG in HCWs in Seoul compared to those in coronavirus disease (COVID-19) patients and community-based individuals to evaluate the antibody response. A total of 358 samples from 348 individuals (155 HCWs, 7 COVID-19 patients, and 186 community-based individuals) were collected from April to November 2020. SARS-CoV-2 IgG was detected in 1 of 155 HCWs (1 of 46 HCWs with direct contact), 7 of 7 COVID-19 patients, and none of the 186 communitybased individuals (95% CI: 0.6%, 0.1 - 3.6%; 100%, 64.5 - 100%; 0.0%, 0.0 - 2.0%, respectively).The single HCW with a positive result showed 2.32 signal-to-cutoff (S/C) and 2.31 S/C at a 3-week interval. Therefore, it was assumed to be a false positive due to autoantibody or medication. The positive samples from 7 patients had a median of 3.79 S/C (range 1.72 - 6.54). The seroprevalence of SARS-CoV-2 IgG in HCWs was very low. The current infection control standard seems to be effective in protecting HCWs from COVID-19.

Mucormycosis is a fungal infection, which is difficult to treat due to its rapid dissemination and low susceptibility to anti-fungal agents. Peritonitis preceded by gastrointestinal mucormycosis is very rare, and only a few cases have been reported. We present a case of peritonitis and disseminated mucormycosis caused by Mucor circinelloides in an immunocompromised patient. A 59-year-old man, diagnosed with nodal marginal zone B-cell lymphoma, was diagnosed with liver failure due to severe septic shock. A white, woolly cotton-like growth, which was consistent with that of Mucor species, was isolated from ascites and sputum specimens. Targeted DNA sequencing confirmed the isolate as M. circinelloides with 100% identity. Despite anti-fungal treatment, the patient died after four days. This is a rare case of peritonitis and disseminated mucormycosis that was probably preceded by gastrointestinal mucormycosis caused by M. circinelloides, as determined by molecular methods. Accurate and rapid identification of mold using molecular methods might be necessary for early treatment in critical cases, and more cases should be clinically evaluated further.

Accurate detection of BCR-ABL fusion transcripts at and below molecular response (MR) 4 (0.01% International Scale [IS]) is required for disease monitoring in patients with chronic myeloid leukemia (CML). We evaluated the analytical performance of the QXDx BCR-ABL %IS (Bio-Rad, Hercules, CA, USA) droplet digital PCR (ddPCR) assay, which is the first commercially available ddPCR-based in vitro diagnostics product. In precision analysis, the %CV was 9.3% and 3.0%, with mean values of 0.031% IS and 9.4% IS, respectively. The assay was linear in the first order, ranging from 0.032% IS to 20% IS. The manufacturer-claimed limit of blank, limit of detection, and limit of quantification were verified successfully. There was a very strong correlation between the results of the QXDx BCR-ABL %IS ddPCR assay and the ipsogen BCR-ABL1 Mbcr IS-MMR (Qiagen, Hilden, Germany) real-time quantitative PCR assay (r=0.996). In conclusion, the QXDx BCR-ABL %IS ddPCR assay can provide reliable results for CML patients.

BACKGROUND: High-density lipoprotein cholesterol (HDL-C) is a complex mixture of subclasses with heterogeneous atheroprotective activities. We analyzed HDL-C subclass in relation to cardiovascular risk and metabolic syndrome (MetS) in a population with high HDL-C levels. METHODS: A total of 300 Korean individuals with high HDL-C levels (≥2.331 mmol/L) were enrolled following a comprehensive general medical examination including body composition analysis. HDL3-C levels were measured using the HDL3-EX SEIKEN kit (Randox Ltd., Crumlin, UK) and non-HDL3-C levels were calculated by subtracting HDL3-C levels from total HDL-C levels. RESULTS: HDL3-C levels and HDL3-C proportion had a weak positive correlation with low-density lipoprotein cholesterol (LDL-C) and triglycerides (r=0.21, r=0.25; r=0.26, r=0.34, respectively, all P<0.001); in contrast, non-HDL3-C levels had a weak negative correlation with these parameters (r=−0.17 and r=−0.25, respectively, both P<0.005). HDL3-C levels and HDL3-C proportion were significantly higher in the MetS group (N=8) than in the non-MetS group (0.71 vs 0.63 mmol/L, P=0.001; 29.7 vs 25.8%, P=0.001, respectively); these were the only predictors of MetS among the lipid variables (areas under the curves [AUC]=0.84 and 0.83, respectively, both P=0.001). CONCLUSIONS In populations with high HDL-C levels, HDL-C subclass may provide a greater amount of information on cardiovascular risk and MetS than HDL-C levels alone.

Background: Kidney failure occurs frequently and is associated with high mortality during sepsis. Proenkephalin (PENK) is an emerging biomarker of kidney function. We explored whether PENK levels could predict severity, organ failure, and mortality in septic patients. Methods: We measured the PENK level in the plasma of 215 septic patients using the sphingotest penKid assay (Sphingotec GmbH, Hennigsdorf, Germany). This was analyzed in terms of sepsis severity, vasopressor use, 30-day mortality, sequential organ failure assessment (SOFA) renal subscore, the Chronic Kidney Disease Epidemiology Collaboration estimated glomerular filtration rate (CKD-EPI eGFR) categories, and renal replacement therapy (RRT) requirement. Results: The PENK levels were significantly higher in patients with septic shock, vasopressor use, and non-survivors than in patients with solitary sepsis, no vasopressor use, and survivors, respectively (P = 0.02, P = 0.007, P < 0.001, respectively). The PENK levels were significantly associated with SOFA renal subscore and CKD-EPI eGFR categories (both P < 0.001). The distribution of lower eGFR ( < 60 mL/min/1.73 m2 ), RRT requirement, SOFA renal subscore, and the number of organ failures differed significantly according to the PENK quartile (P for trend < 0.001 or 0.017). The 30-day mortality rate also differed significantly according to the PENK quartile (P for trend < 0.001). Conclusions PENK could be an objective and reliable marker to predict severity, organ failure, and 30-day mortality in septic patients.