Background: SARS-CoV2 can cause pulmonary failure requiring prolonged invasive mechanical ventilation (MV). Lung protective ventilation strategies are recommended in order to minimize ventilator induced lung injury. Whether patients with COVID-19 have the same risk for complications including barotrauma is still unknown. Therefore, we investigated barotrauma in patients with COVID-19 pneumonia requiring prolonged MV. Methods: All patients meeting diagnosis criteria for ARDS according to the Berlin Definition, with PCR positive SARS-CoV2 infection and prolonged mechanical ventilation, defined as ≥2 days, treated at our ARDS referral center between March and April 2020 were included in a retrospective registry analysis. Complications were detected by manual review of all patient data including respiratory data, imaging studies, and patient files. Results: A total of 20 patients with severe COVID-19 pulmonary failure (Overall characteristics: median age: 61 years, female gender 6, median duration of MV 22 days) were analyzed. Eight patients (40%) developed severe barotrauma during MV (after median 18 days, range: 1-32) including pneumothorax (5/20), pneumomediastinum (5/20), pneumopericard (1/20), and extended subcutaneous emphysema (5/20). Median respirator settings 24 hours before barotrauma were: Peak inspiratory pressure (Ppeak) 29 cm H2O (range: 27-35), positive end-expiratory pressure (PEEP) 14 cm H2O (range: 5-24), tidal volume (VT) 5.4ml/kg predicted body weight (range 0.4-8.6), plateau pressure (Pplateau) 27 cm H2O (range: 19-30). Mechanical ventilation was significantly more invasive on several occasions in patients without barotrauma. Conclusion: Barotrauma in COVID-19 induced respiratory failure requiring mechanical ventilation was found in 40% of patients included in this registry. Our data suggest that barotrauma in COVID-19 may occur even when following recommendations for lung protective MV.
Patients hospitalized for infection with SARS-CoV-2 typically present with pneumonia. The respiratory failure is frequently complicated by pulmonary embolism in segmental pulmonary arteries. The distribution of pulmonary embolism in regard to lung parenchymal opacifications has not been investigated yet. Methods: All patients with COVID-19 treated at a medical intensive care unit between March 8th and April 15th, 2020 undergoing computed tomography pulmonary angiography (CTPA) were included. All CTPA were assessed by two radiologists independently in respect to parenchymal changes and pulmonary embolism on a lung segment basis. Results: Out of 22 patients with severe COVID-19 treated within the observed time period, 16 (age 60.4 ± 10.2 years, 6 female SAPS2 score 49.2 ± 13.9) underwent CT. A total of 288 lung segment were analyzed. Thrombi were detectable in 9/16 (56.3%) patients, with 4.4 ± 2.9 segments occluded per patient and 40/288 (13.9%) segments affected in the whole cohort. Patients with thrombi had significantly worse segmental opacifications in CT (p < 0.05) and all thrombi were located in opacitated segments. There was no correlation between d-dimer level and number of occluded segmental arteries. Conclusions: Thrombi in segmental pulmonary arteries are common in COVID-19 and are located in opacitated lung segments. This might suggest local clot formation.
Background Reported mortality of hospitalised Coronavirus Disease-2019 (COVID-19) patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under state of the art care have not been systematically studied. Methods This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced acute respiratory distress syndrome (ARDS) and extracorporeal membrane-oxygenation (ECMO) referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers. Results Between February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) ECMO support. Using multistate methodology, the estimated probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the intensive care unit (ICU) and 57% if mechanical ventilation was required at study entry. Age ≥65 years and male sex were predictors for in-hospital death. Predominant complications–as judged by two independent reviewers–determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications. Conclusion In a dynamic care model COVID-19-related in-hospital mortality remained very high. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.