No abstract

Background: Ineffective inspiratory triggering efforts are a major cause of poor patient-ventilator interactions during mechanical ventilation, but their routine identification requires the insertion of an esophageal catheter. Objectives: We developed a mathematical analysis of ventilatory tracings recorded under noninvasive pressure ventilation in order to identify ineffective triggering efforts and their consequences without recording esophageal pressure. Methods: We assessed 2,183 cycles from 44 pressure support tracings in 14 children with cystic fibrosis treated by noninvasive home ventilation. Airway pressure, flow and esophageal pressure time series were visually analyzed and manually counted. Airway pressure versus time and flow versus time were then analyzed using a dedicated algorithm written by us. Esophageal pressure was only used for validation. Results: A mathematical treatment of flow time series allowed us to draw phase portraits that had specific periodic trajectories for triggered ventilatory cycles and ineffective triggering efforts. From flow and pressure tracings, our algorithm correctly identified 100% of triggered cycles and 53/56 (94.6%) of ineffective triggering efforts. Ineffective triggering was associated with a significant reduction in minute ventilation, inspiratory flows and a significant increase in inspiratory efforts. Conclusions: A noninvasive analysis of flow and airway pressure can reliably identify ineffective triggering efforts during noninvasive pressure support ventilation. This approach may be a valuable tool for evaluating patient-ventilator interactions and their consequences during long-term recordings.

Recurrence plots were introduced to quantify the recurrence properties of chaotic dynamics. Hereafter, the recurrence quantification analysis was introduced to transform graphical interpretations into statistical analysis. In this spirit, a new definition for the Shannon entropy was recently introduced in order to have a measure correlated with the largest Lyapunov exponent. Recurrence plots and this Shannon entropy are thus used for the analysis of the dynamics underlying patient assisted with a mechanical noninvasive ventilation. The quality of the assistance strongly depends on the quality of the interactions between the patient and his ventilator which are crucial for tolerance and acceptability. Recurrence plots provide a global view of these interactions and the Shannon entropy is shown to be a measure of the rate of asynchronisms as well as the breathing rhythm.

Quantifiers were introduced to convert recurrence plots into a statistical analysis of dynamical properties. It is shown that the Shannon entropy, if properly computed, increases as the chaotic regime is developed as expected. Recurrence plots and a new estimator for the Shannon entropy are then used to identify asynchronisms in noninvasive mechanical ventilation. It is thus shown that the phase coherence-easily identified using a Shannon entropy-is relevant in the quality of the mechanical ventilation. In particular, some patients with chronic respiratory diseases or healthy subjects can have a high rate of asynchronisms but a regular breathing rhythm.