Guillaume Carteaux1, Aissam Lyazidi2, Ana Cordoba-Izquierdo2, Laurence Vignaux3, Philippe Jolliet4, Arnaud W Thille2, Jean-Christophe M Richard5, Laurent Brochard6. 1. Réanimation Médicale, AP-HP, Groupe Hospitalier Albert Chenevier-Henri Mondor, Rouen, France; INSERM Unité 955 (Equipe 13), Université Paris EST, Créteil, France. Electronic address: guillaume.carteaux@yahoo.fr. 2. Réanimation Médicale, AP-HP, Groupe Hospitalier Albert Chenevier-Henri Mondor, Rouen, France; INSERM Unité 955 (Equipe 13), Université Paris EST, Créteil, France. 3. Department of Intensive Care, Geneva University Hospital and Geneva University, Geneva. 4. Service de Médecine Intensive Adulte et Centre des brulés, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland; Faculté de biologie et de medicine, Université de Lausanne, Lausanne, Switzerland. 5. Réanimation médicale, Centre Hospitalier Universitaire Charles Nicolle, Rouen, France. 6. Réanimation Médicale, AP-HP, Groupe Hospitalier Albert Chenevier-Henri Mondor, Rouen, France; INSERM Unité 955 (Equipe 13), Université Paris EST, Créteil, France; Department of Intensive Care, Geneva University Hospital and Geneva University, Geneva.
Abstract
BACKGROUND: Different kinds of ventilators are available to perform noninvasive ventilation (NIV) in ICUs. Which type allows the best patient-ventilator synchrony is unknown. The objective was to compare patient-ventilator synchrony during NIV between ICU, transport—both with and without the NIV algorithm engaged—and dedicated NIV ventilators. METHODS: First, a bench model simulating spontaneous breathing efforts was used to assess the respective impact of inspiratory and expiratory leaks on cycling and triggering functions in 19 ventilators. Second, a clinical study evaluated the incidence of patient-ventilator asynchronies in 15 patients during three randomized, consecutive, 20-min periods of NIV using an ICU ventilator with and without its NIV algorithm engaged and a dedicated NIV ventilator. Patient-ventilator asynchrony was assessed using flow, airway pressure, and respiratory muscles surface electromyogram recordings. RESULTS: On the bench, frequent auto-triggering and delayed cycling occurred in the presence of leaks using ICU and transport ventilators. NIV algorithms unevenly minimized these asynchronies, whereas no asynchrony was observed with the dedicated NIV ventilators in all except one. These results were reproduced during the clinical study: The asynchrony index was significantly lower with a dedicated NIV ventilator than with ICU ventilators without or with their NIV algorithm engaged (0.5% [0.4%-1.2%] vs 3.7% [1.4%-10.3%] and 2.0% [1.5%-6.6%], P < .01), especially because of less auto-triggering. CONCLUSIONS:Dedicated NIV ventilators allow better patient-ventilator synchrony than ICU and transport ventilators, even with their NIV algorithm. However, the NIV algorithm improves, at least slightly and with a wide variation among ventilators, triggering and/or cycling off synchronization.
RCT Entities:
BACKGROUND: Different kinds of ventilators are available to perform noninvasive ventilation (NIV) in ICUs. Which type allows the best patient-ventilator synchrony is unknown. The objective was to compare patient-ventilator synchrony during NIV between ICU, transport—both with and without the NIV algorithm engaged—and dedicated NIV ventilators. METHODS: First, a bench model simulating spontaneous breathing efforts was used to assess the respective impact of inspiratory and expiratory leaks on cycling and triggering functions in 19 ventilators. Second, a clinical study evaluated the incidence of patient-ventilator asynchronies in 15 patients during three randomized, consecutive, 20-min periods of NIV using an ICU ventilator with and without its NIV algorithm engaged and a dedicated NIV ventilator. Patient-ventilator asynchrony was assessed using flow, airway pressure, and respiratory muscles surface electromyogram recordings. RESULTS: On the bench, frequent auto-triggering and delayed cycling occurred in the presence of leaks using ICU and transport ventilators. NIV algorithms unevenly minimized these asynchronies, whereas no asynchrony was observed with the dedicated NIV ventilators in all except one. These results were reproduced during the clinical study: The asynchrony index was significantly lower with a dedicated NIV ventilator than with ICU ventilators without or with their NIV algorithm engaged (0.5% [0.4%-1.2%] vs 3.7% [1.4%-10.3%] and 2.0% [1.5%-6.6%], P < .01), especially because of less auto-triggering. CONCLUSIONS: Dedicated NIV ventilators allow better patient-ventilator synchrony than ICU and transport ventilators, even with their NIV algorithm. However, the NIV algorithm improves, at least slightly and with a wide variation among ventilators, triggering and/or cycling off synchronization.
Authors: Josep Masip; W Frank Peacock; Susanna Price; Louise Cullen; F Javier Martin-Sanchez; Petar Seferovic; Alan S Maisel; Oscar Miro; Gerasimos Filippatos; Christiaan Vrints; Michael Christ; Martin Cowie; Elke Platz; John McMurray; Salvatore DiSomma; Uwe Zeymer; Hector Bueno; Chris P Gale; Maddalena Lettino; Mucio Tavares; Frank Ruschitzka; Alexandre Mebazaa; Veli-Pekka Harjola; Christian Mueller Journal: Eur Heart J Date: 2018-01-01 Impact factor: 29.983
Authors: Michael J Banner; Carl G Tams; Neil R Euliano; Paul J Stephan; Trevor J Leavitt; A Daniel Martin; Nawar Al-Rawas; Andrea Gabrielli Journal: J Clin Monit Comput Date: 2015-06-13 Impact factor: 2.502
Authors: Lise Piquilloud; Didier Tassaux; Emilie Bialais; Bernard Lambermont; Thierry Sottiaux; Jean Roeseler; Pierre-François Laterre; Philippe Jolliet; Jean-Pierre Revelly Journal: Intensive Care Med Date: 2012-08-03 Impact factor: 17.440