Pentraxin-3 (PTX-3) as a potential biomarker for predicting death in hospitalized patients with COVID-19.

Background: Pentraxin 3 (PTX3) is an acute-phase protein that belongs to the pentraxin family, which plays an important role in the body's defense against pathogens. PTX3 levels have been associated with inflammatory processes, and it is a possible biomarker for the diagnosis and prognosis of different infectious diseases, including COVID-19. The objective of this study was to analyze the potential of PTX3 as a plasma biomarker for predicting death in patients hospitalized with COVID-19.

Methods: The study included a total of 312 patients with COVID-19, admitted from July 2020 to August 2021 to hospital ward and intensive care unit beds at two hospitals in the Northeast Region of Brazil. PTX3 was measured using ELISA in samples collected within 24 h after hospital admission. Maximally selected rank statistics were used to determine the PTX3 cutoff point that best distinguished patients who died from those who survived. A receiver operating characteristic (ROC) curve was used to determine the performance of the biomarker. Survival analysis was performed using a Kaplan-Meier curve, and a Cox regression model was used to determine predictors associated with death.

Results: Of the 312 patients included in the study, 233 recovered and 79 died. Patients who died had higher PTX3 levels at the time of admission, when compared to those who recovered (median: 52.84 versus 10.79 ng/mL; p < 0.001). PTX3 showed area under the ROC (AUC) = 0.834, higher than other markers used in clinical practice, such as C-reactive protein (AUC = 0.72) and D-dimer (AUC = 0.77). Furthermore, according to the Kaplan-Meier survival curve, patients with PTX3 concentrations above the cutoff point (27.3 ng/mL) had a lower survival rate (p = 0.014). In multivariate Cox regression, PTX3 > 27.3 ng/mL was an important predictor of death, regardless of other confounding factors (hazard ratio = 1.79; p = 0.027).

Conclusion: PTX3 can be considered as a potential biomarker for predicting death in patients hospitalized with COVID-19.