SARS-CoV-2 is a member of the family of coronaviruses associated with severe outbreaks of respiratory diseases in recent decades and is the causative agent of the COVID-19 pandemic. The recognition by and activation of the innate immune response recruits neutrophils, which, through their different mechanisms of action, form extracellular neutrophil traps, playing a role in infection control and trapping viral, bacterial, and fungal etiological agents. However, in patients with COVID-19, activation at the vascular level, combined with other cells and inflammatory mediators, leads to thrombotic events and disseminated intravascular coagulation, thus leading to a series of clinical manifestations in cerebrovascular, cardiac, pulmonary, and kidney disease while promoting severe disease and mortality. Previous studies of hospitalized patients with COVID-19 have shown that elevated levels of markers specific for NETs, such as free DNA, MPO, and H3Cit, are strongly associated with the total neutrophil count; with acute phase reactants that include CRP, D-dimer, lactate dehydrogenase, and interleukin secretion; and with an increased risk of severe COVID-19. This study analyzed the interactions between NETs and the activation pathways involved in immunothrombotic processes in patients with COVID-19.

Background: Information about angiotensin II (Ang II), angiotensin-converting enzyme 2 (ACE2), and Ang-(1–7) levels in patients with COVID-19 is scarce. Objective: To characterize the Ang II–ACE2–Ang-(1–7) axis in patients with SARS-CoV-2 infection to understand its role in pathogenesis and prognosis. Methods: Patients greater than 18 years diagnosed with COVID-19, based on clinical findings and positive RT-PCR test, who required hospitalization and treatment were included. We compared Ang II, aldosterone, Ang-(1–7), and Ang-(1–9) concentrations and ACE2 concentration and activity between COVID-19 patients and historic controls. We compared baseline demographics, laboratory results (enzyme, peptide, and inflammatory marker levels), and outcome (patients who survived versus those who died). Results: Serum from 74 patients [age: 58 (48–67.2) years; 68% men] with moderate (20%) or severe (80%) COVID-19 were analyzed. During 13 (10–21) days of hospitalization, 25 patients died from COVID-19 and 49 patients survived. Compared with controls, Ang II concentration was higher and Ang-(1–7) concentration was lower, despite significantly higher ACE2 activity in patients. Ang II concentration was higher and Ang-(1–7) concentration was lower in patients who died. The Ang II/Ang-(1–7) ratio was significantly higher in patients who died. In multivariate analysis, Ang II/Ang-(1–7) ratio greater than 3.45 (OR = 5.87) and lymphocyte count ⩽0.65 × 103/µl (OR = 8.43) were independent predictors of mortality from COVID-19. Conclusion: In patients with severe SARS-CoV-2 infection, imbalance in the Ang II–ACE2–Ang-(1–7) axis may reflect deleterious effects of Ang II and may indicate a worse outcome.

Objective To investigate whether a simplified inflammation-based risk scoring system comprising three readily available biomarkers (albumin, C-reactive protein, and leukocytes) may predict major adverse outcomes in patients with COVID-19. Methods Upon admission to the emergency room, the inflammation-based risk scoring system was applied and patients were classified as having mild, moderate, or severe inflammation. In-hospital occurrence of thrombosis, need for mechanical ventilation, and death were recorded. Results One-hundred patients (55 ± 13 years; 71% men) were included and classified as having mild (29%), moderate (12%), or severe (59%) inflammation. The need for mechanical ventilation differed among patients in each group (16%, 50%, and 71%, respectively; P < 0.0001), yielding a 4.1-fold increased risk of requiring mechanical ventilation in patients with moderate inflammation and 5.4 for those with severe inflammation. On the contrary, there were no differences for the occurrence of thrombosis (10%, 8%, and 22%, respectively; P = 0.142) or death (21%, 42%, and 39%, respectively; P = 0.106). In the multivariate analysis, only severe inflammation (hazard ratio [HR] = 4.1), D-dimer > 574 ng/mL (HR = 3.0), and troponin I ≥ 6.7 ng/mL (HR = 2.4) at hospital admission were independent predictors of the need for mechanical ventilation. Conclusion The inflammation-based risk scoring system predicts the need for mechanical ventilation in patients with severe COVID-19.

Background: Several easy-to-use risk scoring systems have been built to identify patients at risk of developing complications associated with COVID-19. However, information about the ability of each score to early predict major adverse outcomes during hospitalization of severe COVID-19 patients is still scarce. Methods: Eight risk scoring systems were rated upon arrival at the Emergency Department, and the occurrence of thrombosis, need for mechanical ventilation, death, and a composite that included all major adverse outcomes were assessed during the hospital stay. The clinical performance of each risk scoring system was evaluated to predict each major outcome. Finally, the diagnostic characteristics of the risk scoring system that showed the best performance for each major outcome were obtained. Results: One hundred and fifty-seven adult patients (55 ± 12 years, 66% men) were assessed at admission to the Emergency Department and included in the study. A total of 96 patients (61%) had at least one major outcome during hospitalization; 32 had thrombosis (20%), 80 required mechanical ventilation (50%), and 52 eventually died (33%). Of all the scores, Obesity and Diabetes (based on a history of comorbid conditions) showed the best performance for predicting mechanical ventilation (area under the ROC curve (AUC), 0.96; positive likelihood ratio (LR+), 23.7), death (AUC, 0.86; LR+, 4.6), and the composite outcome (AUC, 0.89; LR+, 15.6). Meanwhile, the inflammation-based risk scoring system (including leukocyte count, albumin, and C-reactive protein levels) was the best at predicting thrombosis (AUC, 0.63; LR+, 2.0). Conclusions: Both the Obesity and Diabetes score and the inflammation-based risk scoring system appeared to be efficient enough to be integrated into the evaluation of COVID-19 patients upon arrival at the Emergency Department.