Introduction: Influenza rapid diagnostic tests (RDTs) have been developed to supply scientists with more sensitive and specific techniques. Newly developed digital reader-based techniques require test evaluations before their clinical application. Methods: Two types of digital influenza RDTs using a digital readout system and one conventional RDT were compared using 314 nasopharyngeal swabs of influenza. The swabs originated from symptomatic individuals suspected of influenza infection, and the presence of influenza was confirmed with influenza real-time polymerase chain reaction (PCR) testing and influenza subtyping. Methods were the Sofia® Influenza A + B Fluorescence Immunoassay (FIA), which uses a portable fluorescence analyser, the BD Veritor™ System Flu A + B, which uses a colorimetric immunochromatographic method with a reflectance-based measurement digital device, and the SD Bioline assay, which is based on a traditional immunochromatographic method. Results: The Sofia® Influenza A + B system, the BD Veritor™ System Flu A + B and the SD Bioline assay showed sensitivities in relative real-time PCR results of 74.2, 73.0 and 53.9%, respectively, for influenza A, and 82.5, 72.8 and 71.0%, respectively, for influenza B. All three RDTs showed 100% specificities for influenza A and influenza B. The Sofia® Influenza A + B Fluorescence Immunoassay showed sensitive and specific results for the detection of influenza B in contrast to the BD Veritor™ System Flu A + B. The two digital RDTs showed higher sensitivity and specificity than the conventional RDT in the detection of the influenza H3 subtype. Conclusions: Digital-based readout systems for the detection of the influenza virus can be applied for more sensitive diagnosis in clinical settings than conventional RDTs.

Recently, conventional interviews have been replaced with the multiple mini-interviews (MMI) for medical student selection in Korea. We first introduced the MMI as a new admissions tool in Korea. The aim of this study is to determine whether the MMI accurately predicts academic achievement on both written and performance-based examinations during the first 2 years of medical school. The original scores of each station were standardized to T-scores in the candidates group. Three cohorts of students were included depending upon the year they entered medical school. Pearson’s correlations were calculated to estimate the correlations between MMI scores and academic achievements. Additional correlated factors were run through multiple stepwise linear regression analysis to estimate predictive validity. There were no differences between T-scores or grade point averages (GPA) among the cohorts. The correlation coefficients between total MMI scores and academic achievement in Year 1 and the Year 2 performance-based examinations ranged from 0.17 to 0.43. Station 1 significantly predicted academic achievement over the second year. Station 3 significantly predicted only performance-based examination performance over the second year. MMI is a useful tool to assist with medical student selection. In particular, critical thinking, professionalism, and presentation and communication skills may be meaningful topics for predicting academic achievements, especially in performance-based subjects.

Vancomycin, a first-line drug for treating methicillin-resistant Staphylococcus aureus infections, is associated with acute kidney injury (AKI). This study involved an evaluation of biomarkers for AKI detection and their comparison with traditional serum creatinine (SCr). We prospectively enrolled patients scheduled to receive intravenous vancomycin for methicillin-resistant S aureus infection. Blood samples for pharmacokinetic assessment and SCr and cystatin C (CysC) measurements were collected at baseline and on days 3, 7, and 10 from the initiation of vancomycin administration (day 1). Urinary biomarkers, including kidney injury molecule 1 (KIM-1), neutrophil gelatinase-associated lipocalin, and clusterin, were collected from days 1 to 7 and adjusted for urinary creatinine levels. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation. Of the 42 patients, 6 experienced vancomycin-induced AKI. On day 7, the change from baseline eGFR using CysC (ΔeGFR_CysC) showed a stronger correlation with vancomycin area under the curve (r = −0.634, P < .001) than that using SCr (ΔeGFR_SCr; r = −0.437, P = .020). ΔeGFR_SCr showed no significant correlation with vancomycin pharmacokinetic in patients with body mass index ≥23. The median (interquartile range) level of KIM-1 (μg/mg) was significantly higher in the AKI group (0.006 [0.005–0.008]) than in the non-AKI group (0.004 [0.001–0.005]) (P = .039, Mann–Whitney U test), with area under the receiver operating characteristic curve (95% confidence interval) of 0.788 (0.587–0.990). Serum CysC, particularly in overweight individuals or those with obesity, along with urinary KIM-1 are important predictors of vancomycin-induced AKI. These results may aid in selecting better biomarkers than traditional SCr for detecting vancomycin-induced AKI.

Background: This study investigated hematological and biochemical parameters, including cell population data (CPD), to evaluate their association with severity in COVID-19 and non-COVID-19 patients. Identifying these parameters could aid in disease monitoring and clinical decision-making. Methods: A retrospective analysis of 8401 patients, including 603 COVID-19 cases and 7546 non-COVID-19 cases, were conducted. Complete blood count (CBC) and routine chemistry results obtained near the time of real-time polymerase chain reaction testing were analyzed to assess their associations with disease severity. A matched cohort analysis was performed to adjust for potential confounding factors, such as age and sex. Results: COVID-19 patients with elevated neutrophil side fluorescence light (NE-SFL), platelet-to-lymphocyte ratio (PLR), glucose, and aspartate aminotransferase (AST), along with decreased plateletcrit, were more likely to experience severe outcomes, such as hospitalization or death. In addition, decreased hemoglobin, lymphocyte side scatter (LY-SSC), and albumin, as well as increased leukocyte and monocyte side scatter (MO-SSC), were associated with a greater severity, regardless of COVID-19 status. Conclusions: We identified hematologic and chemical assay biomarkers that correlate with severe COVID-19. These findings may provide important information regarding the disease progression and clinical management. Incorporating these biomarkers into clinical decision support systems could facilitate personalized treatment strategies, optimize resource allocation, and enable real-time severity stratification.