In this multicentre cohort study of 259 critically ill adult patients with COVID-19 initially treated with HFNO, the need for intubation and invasive mechanical ventilation was frequent and occurred in more than 50% of patients. Non-respiratory SOFA and the ROX index were the main predictors of endotracheal intubation.
Unlike previous studies in non-COVID patients2,29, poor oxygenation at baseline, as measured by PaO2/FiO2, was not a reliable predictor of intubation. While hypoxemia seems often homogenously noticeable in this population, its mechanisms may be multifactorial and might change over time as the disease progresses30. Cressoni et al. described the distinction between anatomic to functional shunt in ARDS, and Gattinoni et al. have recently reported that the ratio of the shunt fraction to the gasless compartment in COVID-19 subjects is often higher than the values found in ARDS31,32. Recently, Chiumello et al. highlighted the differential radiologic pattern of COVID-19 patients as compared to non-COVID-19 ARDS. Similar to previous studies in both non-COVID and COVID patients, our study supported how ROX index, which encompasses information from both oxygenation and respiratory rate, was useful to predict intubation23,33. In the absence of non-pulmonary involvement, a ROX index of 3.5 at admission conferred a 50% chance of intubation, which was 83% sensitive and 89% specific for HFNO failure. Of note, the present study differs from previous reports in the percentage of patients receiving HFNO from the total population of patients with COVID-19 related acute respiratory failure13,14. Specifically, the patient population in the present study comprised 24% of the whole database, potentially showing that clinicians seemed to be keener (compared to previously published reports) on using this non-invasive oxygenation strategy in this patient population. This in turn may also explain the lower PaO2/FiO2 ratios that were often observed13,14 and potentially, the lack of impact on the initial decision to switch from HFNO to invasive mechanical ventilation.
Our parsimonious model, which included non-respiratory SOFA and the ROX index, to predict intubation among patients with COVID-19 treated with HFNO showed excellent discrimination and may be helpful in the decision-making process at the bedside. The model also shows strong clinical rationale. It is plausible that as lung mechanics deteriorated in some patients, respiratory drive increased, making the ROX index a valuable tool to predict HFNO failure. Likewise, pH was often lower and PaCO2 higher in subjects who later became intubated, suggesting fatigue or increased lung injury in failing subjects. Non-respiratory SOFA score was higher in intubated patients and this was mostly related to hemodynamic impairment. Finally, our mixed-effects analysis showed that most of the variability for the need of invasive mechanical ventilation can be explained by baseline factors at admission, while differential “ICU culture” does not appear to play a major role in this decision. This needs to be analysed in comparison to previous research showing fairly strong centre effects, both in the care of patients with septic shock and mechanically ventilated critically ill adults17,34.
Our study has several strengths. First, data were collected prospectively in a nationwide project and one of its main goals was to specifically study the relationship between respiratory treatment and outcome. Second, we were able to derive a parsimonious, potentially easy-to-use model that could aid in the identification of patients who may need intubation while being treated with HFNO. However, we acknowledge some limitations of our findings. First, observational studies, especially those multicentre in nature, as our study, are prone to misclassification of relevant covariates and potential predictors. However, a concise manual of procedures was provided to all the participating researchers at the beginning of the study, and two independent investigators checked for the accuracy of the data and unreliable values for all included patients. Second, missing data on candidate predictors was present in the final sample, rendering our reported associations subject to information bias and potentially decreasing the precision of our estimates. However, our results were robust while using multiple imputation.