Rationale: Esophageal manometry is the clinically available method to estimate pleural pressure, thus enabling calculation of transpulmonary pressure (Pl). However, many concerns make it uncertain in which lung region esophageal manometry reflects local Pl. Objectives: To determine the accuracy of esophageal pressure (Pes) and in which regions esophageal manometry reflects pleural pressure (Ppl) and Pl; to assess whether lung stress in nondependent regions can be estimated at end-inspiration from Pl. Methods: In lung-injured pigs (n = 6) and human cadavers (n = 3), Pes was measured across a range of positive end-expiratory pressure, together with directly measured Ppl in nondependent and dependent pleural regions. All measurements were obtained with minimal nonstressed volumes in the pleural sensors and esophageal balloons. Expiratory and inspiratory Pl was calculated by subtracting local Ppl or Pes from airway pressure; inspiratory Pl was also estimated by subtracting Ppl (calculated from chest wall and respiratory system elastance) from the airway plateau pressure. Measurements and Main Results: In pigs and human cadavers, expiratory and inspiratory Pl using Pes closely reflected values in dependent to middle lung (adjacent to the esophagus). Inspiratory Pl estimated from elastance ratio reflected the directly measured nondependent values. Conclusions: These data support the use of esophageal manometry in acute respiratory distress syndrome. Assuming correct calibration, expiratory Pl derived from Pes reflects Pl in dependent to middle lung, where atelectasis usually predominates; inspiratory Pl estimated from elastance ratio may indicate the highest level of lung stress in nondependent “baby” lung, where it is vulnerable to ventilator-induced lung injury.

Acute respiratory distress syndrome (ARDS) is a clinical entity that acutely affects the lung parenchyma, and is characterized by diffuse alveolar damage and increased pulmonary vascular permeability. Currently, computed tomography (CT) is commonly used for classifying and prognosticating ARDS. However, performing this examination in critically ill patients is complex, due to the need to transfer these patients to the CT room. Fortunately, new technologies have been developed that allow the monitoring of patients at the bedside. Electrical impedance tomography (EIT) is a monitoring tool that allows one to evaluate at the bedside the distribution of pulmonary ventilation continuously, in real time, and which has proven to be useful in optimizing mechanical ventilation parameters in critically ill patients. Several clinical applications of EIT have been developed during the last years and the technique has been generating increasing interest among researchers. However, among clinicians, there is still a lack of knowledge regarding the technical principles of EIT and potential applications in ARDS patients. The aim of this review is to present the characteristics, technical concepts, and clinical applications of EIT, which may allow better monitoring of lung function during ARDS.

(1) The use of high-flow nasal cannula (HFNC) combined with frequent respiratory monitoring in patients with acute hypoxic respiratory failure due to COVID-19 has been shown to reduce intubation and mechanical ventilation. (2) This prospective, single-center, observational study included consecutive adult patients with COVID-19 pneumonia treated with a high-flow nasal cannula. Hemodynamic parameters, respiratory rate, inspiratory fraction of oxygen (F_iO₂), saturation of oxygen (S_pO₂), and the ratio of oxygen saturation to respiratory rate (ROX) were recorded prior to treatment initiation and every 2 h for 24 h. A 6-month follow-up questionnaire was also conducted. (3) Over the study period, 153 of 187 patients were eligible for HFNC. Of these patients, 80% required intubation and 37% of the intubated patients died in hospital. Male sex (OR = 4.65; 95% CI [1.28; 20.6], p = 0.03) and higher BMI (OR = 2.63; 95% CI [1.14; 6.76], p = 0.03) were associated with an increased risk for new limitations at 6-months after hospital discharge. (4) 20% of patients who received HFNC did not require intubation and were discharged alive from the hospital. Male sex and higher BMI were associated with poor long-term functional outcomes.

Objective . Understanding a patient’s respiratory effort and mechanics is essential for the provision of individualized care during mechanical ventilation. However, measurement of transpulmonary pressure (the difference between airway and pleural pressures) is not easily performed in practice. While airway pressures are available on most mechanical ventilators, pleural pressures are measured indirectly by an esophageal balloon catheter. In many cases, esophageal pressure readings take other phenomena into account and are not a reliable measure of pleural pressure. Approach. A system identification approach was applied to provide accurate pleural measures from esophageal pressure readings. First, we used a closed pressurized chamber to stimulate an esophageal balloon and model its dynamics. Second, we created a simplified version of an artificial lung and tried the model with different ventilation configurations. For validation, data from 11 patients (five male and six female) were used to estimate respiratory effort profile and patient mechanics. Main results. After correcting the dynamic response of the balloon catheter, the estimates of resistance and compliance and the corresponding respiratory effort waveform were improved when compared with the adjusted quantities in the test bench. The performance of the estimated model was evaluated using the respiratory pause/occlusion maneuver, demonstrating improved agreement between the airway and esophageal pressure waveforms when using the normalized mean squared error metric. Using the corrected muscle pressure waveform, we detected start and peak times 130 ± 50 ms earlier and a peak amplitude 2.04 ± 1.46 cmH ₂ O higher than the corresponding estimates from esophageal catheter readings. Significance. Compensating the acquired measurements with system identification techniques makes the readings more accurate, possibly better portraying the patient’s situation for individualization of ventilation therapy.