Development of clinical tools to estimate the breathing effort during high-flow oxygen therapy: the BREF models

Introduction and objectives: Quantifying breathing effort in non-intubated patients is important but not easy. We aimed to develop two prediction models to estimate it in patients treated with high-flow oxygen therapy. Patients and Methods: We analyzed the data of 260 patients from previous studies who received high-flow oxygen therapy. Their breathing effort was measured as the maximal deflection of esophageal pressure (ΔPes). We developed a multivariable linear regression model to estimate ΔPes (in cmH2O) and a multivariable logistic regression model to predict the risk of ΔPes being >10 cmH2O. Candidate predictors included age, sex, diagnosis of the novel coronavirus disease (COVID-19), respiratory rate, heart rate, mean arterial pressure, the results of arterial blood gas analysis, including base excess concentration (BEa) and the ratio of arterial tension to the inspiratory fraction of oxygen (PaO2:FiO2), and the product term between COVID-19 and PaO2:FiO2. Results: ΔPes can be estimated from the presence or absence of COVID-19, BEa, respiratory rate, PaO2:FiO2, and the product term between COVID-19 and PaO2:FiO2. The adjusted R2 was 0.39. The risk of ΔPes being >10 cmH2O can be predicted from BEa, respiratory rate, and PaO2:FiO2. The area under the ROC curve was 0.79 (0.73–0.85). We called these two models BREF, where BREF stands for BReathing EFfort and the three common predictors: BEa (B), respiratory rate (RE), and PaO2:FiO2 (F). Conclusions: We developed two models to estimate the breathing effort of patients on high flow oxygen therapy. Our initial findings are promising and suggest that these models merit further evaluation.