Respiratory physiology & neurobiology · 2013
An open-source software for automatic calculation of respiratory parameters based on esophageal pressure.
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Mayaud Louis, Lejaille Michèle, Prigent Hélène, Louis Bruno, Fauroux Brigitte, Lofaso Frédéric
Аннотация
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 (r(2)) exceeded 0.94 (p<0.001). The bias (mean difference) between PEEPi calculated by hand and automatically was -0.26±0.52cmH2O during spontaneous breathing and the precisions (standard deviations of the differences) was 0.52cmH2O with limits of agreement of 0.78 and -1.30cmH2O. The mean difference between PTPeso calculated by hand and automatically was -0.38±1.42cmH2Os/cycle with limits of agreement of 2.46 and -3.22cmH2Os/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.
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 (r(2)) exceeded 0.94 (p<0.001). The bias (mean difference) between PEEPi calculated by hand and automatically was -0.26±0.52cmH2O during spontaneous breathing and the precisions (standard deviations of the differences) was 0.52cmH2O with limits of agreement of 0.78 and -1.30cmH2O. The mean difference between PTPeso calculated by hand and automatically was -0.38±1.42cmH2Os/cycle with limits of agreement of 2.46 and -3.22cmH2Os/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.