title: Effectiveness of Inspiratory Termination Synchrony with Automatic Cycling During Noninvasive Pressure Support Ventilation.
abstract: BACKGROUND Pressure support ventilation (PSV) is a standard method for non-invasive home ventilation. A bench study was designed to compare the effectiveness of patient-ventilator inspiratory termination synchronization with automated and conventional triggering in various respiratory mechanics models. MATERIAL AND METHODS Two ventilators, the Respironics V60 and Curative Flexo ST 30, connected to a Hans Rudolph Series 1101 lung simulator, were evaluated using settings that simulate lung mechanics in patients with chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), or normal lungs. Ventilators were operated with automated (Auto-Trak) or conventional high-, moderate-, and low-sensitivity flow-cycling software algorithms, 5 cmH2O or 15 cmH2O pressure support, 5 cmH2O positive end-expiratory pressure (PEEP), and an air leak of 25-28 L/min. RESULTS Both ventilators adapted to the system leak without requiring adjustment of triggering settings. In all simulated lung conditions, automated cycling resulted in shorter triggering delay times (<100 ms) and lower triggering pressure-time product (PTPt) values. Tidal volumes (VT) increased with lower conventional cycling sensitivity level. In the COPD model, automated cycling had higher leak volumes and shorter cycling delay times than in conventional cycling. Asynchronous events were rare. Inspiratory time (Tinsp), peak expiratory flow (PEF), and cycling off delay time (Cdelay) increased as a result of reduction in conventional cycling sensitivity level. In the ARDS and normal adult lung models, premature cycling was frequent at the high-sensitive cycling level. CONCLUSIONS Overall, the Auto-Trak protocol showed better patient-machine cycling synchronization than conventional triggering. This was evident by shorter triggering time delays and lower PTPt.
authors.affiliation: Department of Respiratory Medicine, Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai, China (mainland).
authors.forename: Yuqing
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Department of Respiratory Medicine, Huashan Hospital Baoshan Branch, Fudan University, Shanghai, China (mainland).
authors.forename: Kewen
authors.initials: K
authors.lastname: Cheng
authors.affiliation: Department of Respiratory Medicine, Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai, China (mainland).
authors.forename: Xin
authors.initials: X
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D004867:Equipment Design; D006801:Humans; D008168:Lung / Q000502:physiology; D008954:Models, Biological; D063087:Noninvasive Ventilation / Q000295:instrumentation / Q000379:methods*; D011175:Positive-Pressure Respiration / Q000295:instrumentation* / Q000379:methods; D015656:Respiratory Mechanics; D012122:Ventilators, Mechanical