N-antigenemia detection by a rapid lateral flow test predicts 90-day mortality in COVID-19: A prospective cohort study. (October 2022) - Almansa, Raquel; Eiros, Jose María; de Gonzalo-Calvo, David; Postigo, Tamara; Ortega, Alicia; Lopez-Izquierdo, Raul; Moncusí-Moix, Anna; Gort-Paniello, Clara; Dominguez-Gil, Marta; de la Fuente, Amanda; González-González, Laura; Luis-García, Tania; et al.
Abstract: 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. Graphical abstract: Image 1