IntroductionThe course of the disease in SARS-CoV-2 infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patients, we designed the prospective observational Maastricht Intensive Care COVID cohort (MaastrICCht). We incorporated serial measurements that harbour aetiological, diagnostic and predictive information. The study aims to investigate the heterogeneity of the natural course of critically ill patients with a SARS-CoV-2 infection.Methods and analysisMechanically ventilated patients admitted to the intensive care with a SARS-CoV-2 infection will be included. We will collect clinical variables, vital parameters, laboratory variables, mechanical ventilator settings, chest electrical impedance tomography, ECGs, echocardiography as well as other imaging modalities to assess heterogeneity of the course of a SARS-CoV-2 infection in critically ill patients. The MaastrICCht is also designed to foster various other studies and registries and intends to create an open-source database for investigators. Therefore, a major part of the data collection is aligned with an existing national intensive care data registry and two international COVID-19 data collection initiatives. Additionally, we create a flexible design, so that additional measures can be added during the ongoing study based on new knowledge obtained from the rapidly growing body of evidence. The spread of the COVID-19 pandemic requires the swift implementation of observational research to unravel heterogeneity of the natural course of the disease of SARS-CoV-2 infection in mechanically ventilated patients. Our study design is expected to enhance aetiological, diagnostic and prognostic understanding of the disease. This paper describes the design of the MaastrICCht.Ethics and disseminationEthical approval has been obtained from the medical ethics committee (Medisch Ethische Toetsingscommissie 2020-1565/3 00 523) of the Maastricht University Medical Centre+ (Maastricht UMC+), which will be performed based on the Declaration of Helsinki. During the pandemic, the board of directors of Maastricht UMC+ adopted a policy to inform patients and ask their consent to use the collected data and to store serum samples for COVID-19 research purposes. All study documentation will be stored securely for fifteen years after recruitment of the last patient. The results will be published in peer-reviewed academic journals, with a preference for open access journals, while particularly considering deposition of the manuscripts on a preprint server early.Trial registration numberThe Netherlands Trial Register (NL8613).

BackgroundHomogeneous ventilation is important for prevention of ventilator-induced lung injury. Electrical impedance tomography (EIT) has been used to identify optimal PEEP by detection of homogenous ventilation in non-dependent and dependent lung regions. We aimed to compare the ability of volumetric capnography and EIT in detecting homogenous ventilation between these lung regions.MethodsFifteen mechanically-ventilated patients after cardiac surgery were studied. Ventilator settings were adjusted to volume-controlled mode with a fixed tidal volume (Vt) of 6–8 ml kg−1 predicted body weight. Different PEEP levels were applied (14 to 0 cm H2O, in steps of 2 cm H2O) and blood gases, Vcap and EIT were measured.ResultsTidal impedance variation of the non-dependent region was highest at 6 cm H2O PEEP, and decreased significantly at 14 cm H2O PEEP indicating decrease in the fraction of Vt in this region. At 12 cm H2O PEEP, homogenous ventilation was seen between both lung regions. Bohr and Enghoff dead space calculations decreased from a PEEP of 10 cm H2O. Alveolar dead space divided by alveolar Vt decreased at PEEP levels ≤6 cm H2O. The normalized slope of phase III significantly changed at PEEP levels ≤4 cm H2O. Airway dead space was higher at higher PEEP levels and decreased at the lower PEEP levels.ConclusionsIn postoperative cardiac patients, calculated dead space agreed well with EIT to detect the optimal PEEP for an equal distribution of inspired volume, amongst non-dependent and dependent lung regions. Airway dead space reduces at decreasing PEEP levels.

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Individual AV optimization increases the effect of CRT. Nexfin is a promising tool in individual CRT optimization, as Nexfin agrees with VTIao on measuring beat-to-beat SV changes and on assessing relative effects of BiVP on SV at various AV delays.