Transpulmonary pressure, that is the difference between airway pressure (Paw) and pleural pressure, is considered one of the most important parameters to know in order to set a safe mechanical ventilation in acute respiratory distress syndrome (ARDS) patients but also in critically ill obese patients, in abdominal pathologies or in pathologies affecting the chest wall itself. Transpulmonary pressure should rely on the assessment of intrathoracic pleural pressure. Esophageal pressure (Pes) is considered the best surrogate of pleural pressure in critically ill patients, but concerns about its reliability exist. The aim of this article is to describe the technique of Pes measurement in mechanically ventilated patients: the catheter insertion, the proper balloon placement and filling, the validation test and specific procedures to remove the main artifacts will be discussed.

SARS-CoV-2 infection is associated with frequent thrombotic events, at the micro and macro-vascular level, due to the perpetuation of a state of hypercoagulability. The so-called ‘COVID-19 associated coagulopathy’ (CAC) represents a key aspect in the genesis of organ damage from SARS-CoV-2. The main coagulative alterations described in the literature are represented by high levels of D-dimer and fibrinogen. Although CAC has some common features with disseminated intravascular coagulation and sepsis-induced coagulopathy, there are important differences between these clinical pictures and the phenotype of CAC is unique. The pathogenesis of CAC is complex and is affected by the strong interconnection between the inflammatory system and coagulation, in the phenomenon of immunothrombosis and thrombo-inflammation. Several mechanisms come into play, such as inflammatory cytokines, neutrophils, the complement system as well as an alteration of the fibrinolytic system. Finally, an altered platelet function and especially endothelial dysfunction also play a central role in the pathophysiology of CAC. Heparin has several potential effects in CAC, in fact in addition to the anticoagulant effect, it could have a direct antiviral effect and anti-inflammatory properties. The high incidence of thrombo-embolic phenomena despite the use of antithrombotic prophylaxis have led some experts to recommend the use of anticoagulant doses of heparin, but at present the optimal anticoagulant regimen remains to be determined.

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.

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Background Whether respiratory efforts and their timing can be reliably detected during pressure support ventilation using standard ventilator waveforms is unclear. This would give the opportunity to assess and improve patient–ventilator interaction without the need of special equipment. Methods In 16 patients under invasive pressure support ventilation, flow and pressure waveforms were obtained from proximal sensors and analyzed by three trained physicians and one resident to assess patient’s spontaneous activity. A systematic method (the waveform method) based on explicit rules was adopted. Esophageal pressure tracings were analyzed independently and used as reference. Breaths were classified as assisted or auto-triggered, double-triggered or ineffective. For assisted breaths, trigger delay, early and late cycling (minor asynchronies) were diagnosed. The percentage of breaths with major asynchronies (asynchrony index) and total asynchrony time were computed. Results Out of 4426 analyzed breaths, 94.1% (70.4–99.4) were assisted, 0.0% (0.0–0.2) auto-triggered and 5.8% (0.4–29.6) ineffective. Asynchrony index was 5.9% (0.6–29.6). Total asynchrony time represented 22.4% (16.3–30.1) of recording time and was mainly due to minor asynchronies. Applying the waveform method resulted in an inter-operator agreement of 0.99 (0.98–0.99); 99.5% of efforts were detected on waveforms and agreement with the reference in detecting major asynchronies was 0.99 (0.98–0.99). Timing of respiratory efforts was accurately detected on waveforms: AUC for trigger delay, cycling delay and early cycling was 0.865 (0.853–0.876), 0.903 (0.892–0.914) and 0.983 (0.970–0.991), respectively. Conclusions Ventilator waveforms can be used alone to reliably assess patient’s spontaneous activity and patient–ventilator interaction provided that a systematic method is adopted.