Respiratory mechanics assessment for reverse-triggered breathing cycles using pressure reconstruction. (January 2016)

• Record Type: Journal Article
• Authors: Major, Vincent; Corbett, Simon; Redmond, Daniel; Beatson, Alex; Glassenbury, Daniel; Chiew, Yeong Shiong; Pretty, Christopher; Desaive, Thomas; Szlávecz, Ákos; Benyó, Balázs; Shaw, Geoffrey M.; Chase, J. Geoffrey
• Is Part Of: Biomedical signal processing and control. Volume 23(2016)
• Page Start: 1
• Page End: 9
• Publication Date: 2016-01
• Subjects: CV coefficient of variation -- MV mechanical ventilation -- PEEP positive end-expiratory pressure -- SB spontaneous breathing; Respiratory mechanics -- Decision support -- Mechanical ventilation -- Spontaneous breathing -- Reverse-triggering; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2015.07.007
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Pooling breaths to rebuild a pressure waveform unaffected by spontaneous breathing. Reduced variability compared to conventional identification. Using pre- and post-paralysis data to validate the approach. Before and after a recruitment manoeuvre to investigate weakening paralysis. Most effective during severe spontaneous breathing. Abstract: Monitoring patient-specific respiratory mechanics can be used to guide mechanical ventilation (MV) therapy in critically ill patients. However, many patients can exhibit spontaneous breathing (SB) efforts during ventilator supported breaths, altering airway pressure waveforms and hindering model-based (or other) identification of the true, underlying respiratory mechanics necessary to guide MV. This study aims to accurately assess respiratory mechanics for breathing cycles masked by SB efforts. A cumulative pressure reconstruction method is used to ameliorate SB by identifying SB affected waveforms and reconstructing unaffected pressure waveforms for respiratory mechanics identification using a single-compartment model. Performance is compared to conventional identification without reconstruction, where identified values from reconstructed waveforms should be less variable. Results are validated with 9485 breaths affected by SB, including periods of muscle paralysis that eliminates SB, as a validation test set where reconstruction should have no effect. In this analysis, the patients are their own control, with versus without reconstruction, as assessed by breath-to-breath variation using the non-parametric coefficient of variation (CV) of respiratory mechanics. Pressure reconstruction successfully estimates more consistent respiratory mechanics. CV of estimated respiratory elastance is reduced up to 78% compared to conventional identification ( p < 0.05). Pressure reconstruction is comparable ( p > 0.05) to conventional identification during paralysis, and generally performs better as paralysis weakens, validating the algorithm's purpose. Pressure reconstruction provides less-affected pressure waveforms, ameliorating the effect of SB, resulting in more accurate respiratory mechanics identification. Thus providing the opportunity to use respiratory mechanics to guide mechanical ventilation without additional muscle relaxants, simplifying clinical care and reducing risk. Australian New Zealand Trial Registry Number: ACTRN12613001006730.