An open-source software for automatic calculation of respiratory parameters based on esophageal pressure

Highlights

• We provide an open-source tool for the estimation of works of breathing and other physiological parameters of respiration.

• We developed a technique for the identification of the beginning of inspiratory effort in esophageal pressure waveform.

• We offer a user-friendly graphical user interface for expert verification of signals and results.

• Our tool was validated in adults and pediatric patients presenting with various conditions.

• The tool can easily be modified to include additional parameters and features.

Abstract

Purpose

We have developed a software that automatically calculates respiratory effort indices, including intrinsic end expiratory pressure (PEEPi) and esophageal pressure–time product (PTPeso).

Materials and methods

The software first identifies respiratory periods. Clean signals are averaged to provide a reference mean cycle from which respiratory parameters are extracted. The onset of the inspiratory effort is detected automatically by looking backward from the onset of inspiratory flow to the first point where the esophageal pressure derivative is equal to zero (inflection point). PEEPi is derived from this point. Twenty-three recordings from 16 patients were analyzed with the algorithm and compared with experts’ manual analysis of signals: 15 recordings were performed during spontaneous breathing, 1 during non-invasive mechanical ventilation, and 7 under both conditions.

Results

For all values, the coefficients of determinations (r²) exceeded 0.94 (p < 0.001). The bias (mean difference) between PEEPi calculated by hand and automatically was −0.26 ± 0.52 cm H₂O during spontaneous breathing and the precisions (standard deviations of the differences) was 0.52 cm H₂O with limits of agreement of 0.78 and −1.30 cm H₂O. The mean difference between PTPeso calculated by hand and automatically was −0.38 ± 1.42 cm H₂O s/cycle with limits of agreement of 2.46 and −3.22 cm H₂O s/cycle.

Conclusions

Our program provides a reliable method for the automatic calculation of PEEPi and respiratory effort indices, which may facilitate the use of these variables in clinical practice. The software is open source and can be improved with the development and validation of new respiratory parameters.

Introduction

Recently, Brochard et al. (2012b) have suggested a list of respiratory parameters to be monitored in critically ill patients. In particular, assessments of respiratory effort in patients with respiratory failure are useful, and even more in patients requiring mechanical ventilation. The esophageal pressure time product (PTPeso) is considered as one of the most useful variables for quantifying respiratory muscle effort (Baydur et al., 1982b, Sassoon et al., 1991, Tobin and Laghi, 1998) and this variable has been broadly used in recent literature (Carr et al., 2012, Jubran, 1999, Man et al., 2012). PTPeso is calculated as the time integral of the difference between the oesophageal pressure (Peso) and the estimated recoil pressure of the chest wall during inspiration (Baydur et al., 1982a, Jubran, 1999).

However, this measurement requires the determination of the onset of the inspiratory effort and the estimation of the intrinsic positive end expiratory pressure (PEEPi) to determine the precise onset of inspiration to the chest wall relaxation line (Baydur et al., 1982a, Chu and Han, 2008, Sassoon et al., 1991). Few commercially available systems for monitoring these indices are available and it is unknown if these systems are able to adequately estimate PEEPi (Baydur et al., 1982a, Sassoon et al., 1991, Tobin and Laghi, 1998).

We have developed a MATLAB-based standalone program, which is designed to automatically detect the onset of the inspiratory effort and calculate the inspiratory effort indices taking into account PEEPi (Tobin and Laghi, 1998).

The aim of our study was to validate this program by comparing automated versus manual (expert) calculation of PEEPi and PTPeso on different patients’ recordings in order to allow an online access of the validated software. The software and its documentation are published online (http://code.google.com/p/respmat/), where source code is available and can easily be improved with the development and validation of new respiratory parameters.