Synergistic impact of N-antigenemia profiled by a rapid antigen test and low anti-S1 antibodies on the risk of hospitalization in COVID-19.

OBJECTIVES: Identifying patients with COVID-19 who are at risk of poor evolution is key to early decide on their hospitalization. We evaluated the combined impact of nucleocapsid (N)-antigenemia profiled by a rapid test and antibodies against the S1 subunit of the SARS-CoV S protein (S1) on the hospitalization risk of patients with COVID-19. METHODS: N-antigenemia and anti-S1 antibodies were profiled at admission to the emergency department in 146 patients with COVID-19 using the Panbio® antigen Rapid Test and the SARS-CoV-2 immunoglobulin G II Quant/SARS-CoV-2 immunoglobulin G assay from Abbott. A multivariable analysis was used to evaluate the impact of these factors on hospitalization. RESULTS: Patients with a positive N-antigen test in plasma and anti-S1 levels <2821 arbitrary units/mL needed hospitalization more frequently (20 of 23, 87%). A total of 20 of 71 (28.2%) of those showing a negative N-antigen test and anti-S1 ≥2821 arbitrary units/mL were hospitalized for 18 of 52 (34.6%) of the patients with only one of these conditions. Patients with a positive N-antigen test and low antibody levels showed an odds ratio, 95% confidence interval, and P-value for hospitalization of 18.21, 2.74-121.18, and 0.003, respectively, and exhibited the highest mortality (30.4%). CONCLUSIONS: Simultaneous profiling of a rapid N-antigen test in plasma and anti-S1 levels could help to early identify patients with COVID-19 needing hospitalization.

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study.

BACKGROUND: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. METHODS: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. RESULTS: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. CONCLUSIONS: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.

N-antigenemia detection by a rapid lateral flow test predicts 90-day mortality in COVID-19: A prospective cohort study.

OBJECTIVES: To evaluate if the detection of N antigen of SARS-CoV-2 in plasma by a rapid lateral flow test predicts 90-day mortality in COVID-19 patients hospitalized at the wards. METHODS: The presence of N-antigenemia was evaluated in the first 36 hours after hospitalization in 600 unvaccinated COVID-19 patients, by using the Panbio COVID-19 Ag Rapid Test Device from Abbott (Abbott Laboratories Inc., Chicago, IL, USA). The impact of N-antigenemia on 90-day mortality was assessed by multivariable Cox regression analysis. RESULTS: Prevalence of N-antigenemia at hospitalization was higher in nonsurvivors (69% (82/118) vs. 52% (250/482); p < 0.001). The patients with N-antigenemia showed more frequently RNAemia (45.7% (148/324) vs. 19.8% (51/257); p < 0.001), absence of anti-SARS-CoV-2 N antibodies (80.7% (264/327) vs. 26.6% (69/259); p < 0.001) and absence of S1 antibodies (73.4% (240/327) vs. 23.6% (61/259); p < 0.001). The patients with antigenemia showed more frequently acute respiratory distress syndrome (30.1% (100/332) vs. 18.7% (50/268); p = 0.001) and nosocomial infections (13.6% (45/331) vs. 7.9% (21/267); p = 0.026). N-antigenemia was a risk factor for increased 90-day mortality in the multivariable analysis (HR, 1.99 (95% CI,1.09-3.61), whereas the presence of anti-SARS-CoV-2 N-antibodies represented a protective factor (HR, 0.47 (95% CI, 0.26-0.85). DISCUSSION: The presence of N-antigenemia or the absence of anti-SARS-CoV-2 N-antibodies after hospitalization is associated to increased 90-day mortality in unvaccinated COVID-19 patients. Detection of N-antigenemia by using lateral flow tests is a quick, widely available tool that could contribute to early identify those COVID-19 patients at risk of deterioration.