Background and Objectives: Neutrophil extracellular traps (NETs) have been linked to hypercoagulability, immunothrombosis, and organ injury in COVID-19. Digital morphology of peripheral blood smears enables the identification of NET-compatible appearances (NET-like) in circulation, and associations between NET-like derived indices and clinical outcomes have been reported. However, evidence at hospital admission that relates smear NET-like burden to systemic inflammation and clinical severity remains limited. We therefore aimed to compare the burden of NET-like structures on admission smears according to disease severity and systemic inflammatory markers. Materials and Methods: We included 50 consecutively enrolled adults hospitalized for COVID-19; samples were obtained within 24 h of admission. Severity was defined by the World Health Organization Clinical Progression Scale and grouped as moderate or severe. C-reactive protein (CRP), ferritin, and complete blood counts were measured; the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were calculated. Digital morphology assessed 200 leukocytes per patient; the presence of morphological abnormalities, including NET-like events per patient, was recorded. We additionally quantified NET-like events per 100 white blood cells (NET-like/100 WBC) and the neutrophil extracellular trap–segmented neutrophil ratio (NNSR). Results: At admission, CRP, ferritin, NLR, and PLR of patients were above method-specific reference intervals. NET-like events were identified in 66% of patients. NET-like/100 WBC correlated positively with NLR (r = 0.312; p < 0.05). Patients with severe COVID-19 had higher NET-like/100 WBC than those with moderate disease (5.8 ± 7.34 vs. 14.14 ± 15.12; p = 0.0294). Conclusions: Digital morphological identification of NET-like structures on peripheral blood smears is frequent at admission and is associated with systemic inflammatory burden and with greater COVID-19 severity. These findings support the potential complementary value of reporting NET-like events for initial risk stratification in the clinical laboratory.
Rosales et al. (Mon,) studied this question.