Relationship between SARS-CoV-2 infection and the incidence of ventilator-associated lower respiratory tract infections: a European multicenter cohort study

Purpose Although patients with SARS-CoV-2 infection have several risk factors for ventilator-associated lower respiratory tract infections (VA-LRTI), the reported incidence of hospital-acquired infections is low. We aimed to determine the relationship between SARS-CoV-2 pneumonia, as compared to influenza pneumonia or no viral infection, and the incidence of VA-LRTI. Methods Multicenter retrospective European cohort performed in 36 ICUs. All adult patients receiving invasive mechanical ventilation > 48 h were eligible if they had: SARS-CoV-2 pneumonia, influenza pneumonia, or no viral infection at ICU admission. VA-LRTI, including ventilator-associated tracheobronchitis (VAT) and ventilator-associated pneumonia (VAP), were diagnosed using clinical, radiological and quantitative microbiological criteria. All VA-LRTI were prospectively identified, and chest-X rays were analyzed by at least two physicians. Cumulative incidence of first episodes of VA-LRTI was estimated using the Kalbfleisch and Prentice method, and compared using Fine-and Gray models. Results 1576 patients were included (568 in SARS-CoV-2, 482 in influenza, and 526 in no viral infection groups). VA-LRTI incidence was significantly higher in SARS-CoV-2 patients (287, 50.5%), as compared to influenza patients (146, 30.3%, adjusted sub hazard ratio (sHR) 1.60 (95% confidence interval (CI) 1.26 to 2.04)) or patients with no viral infection (133, 25.3%, adjusted sHR 1.7 (95% CI 1.2 to 2.39)). Gram-negative bacilli were responsible for a large proportion (82% to 89.7%) of VA-LRTI, mainly Pseudomonas aeruginosa , Enterobacter spp., and Klebsiella spp. Conclusions The incidence of VA-LRTI is significantly higher in patients with SARS-CoV-2 infection, as compared to patients with influenza pneumonia, or no viral infection after statistical adjustment, but residual confounding may still play a role in the effect estimates.