Anti-Serum polyclonal antibody

Context.-A relevant portion of coronavirus disease 2019 (COVID-19) patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk. Objective.-To evaluate 6 serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin, and cardiac troponin T) for predicting COVID-19 severity and to define related cutoffs able to aid clinicians in risk stratification of hospitalized patients. Design.-A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: nonsurvivors versus survivors and patients admitted to an intensive care unit versus others. Receiver operating characteristic curves and likelihood ratios were employed to define predictive cutoffs for evaluated markers. Results.-Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, whereas only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cutoffs for death prediction were greater than 731 U/L for lactate dehydrogenase and 18 g/L or lower for albumin, whereas a lactate dehydrogenase activity lower than 425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment. Conclusions.-Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cutoffs for their use.

A label-free electrochemical biosensor was developed for the rapid detection of the matrix metalloproteinase 9 (MMP-9) biomarker on the basis of antibody immobilizing on the zinc oxide (ZnO) nanoparticle and ZnO nanorod electrodes. The charge transfer resistance (R-ct) of the electrodes was used as the indicator for MMP-9 concentration, which was obtained through cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The ZnO nanorod-based biosensor exhibited linear behavior in the MMP-9 concentration range of 1-1000 ng/ml, which is a wider range than the available concentration ranges for most of the conventional methods. The biosensor sensitivity was 32.5 mu A/(decade x cm(2)) with a detection time of only 35 min. Moreover, the results from the developed biosensor were comparable with those measured with a commercial enzyme-linked immunosorbent assay (ELISA) for real samples showing less than 8% difference. The presented MMP-9 biosensor is potentially applicable to the analysis of biological samples, especially in point-of-care (POC) diagnosis or urgent cases analysis, considering its simple fabrication, similar accuracy, shorter detection time, and ease of usage compared with traditional methods such as ELISA.