Automated detection and quantification of reverse triggering effort under mechanical ventilation
Pham, Tài (Université Paris-Saclay, AP-HP, Service de médecine intensive-réanimation, Hôpital de Bicêtre)
Montanya, Jaume (Better Care SL, Sabadell)
Telias, Irene (Sinai Health System)
Piraino, Thomas (McMaster University. Division of Critical Care, Department of Anesthesia)
Magrans, Rudys (Better Care SL, Sabadell)
Coudroy, Rémi (Université de Poitiers)
Damiani, L. Felipe (Pontificia Universidad Católica de Chile. Departamento Ciencias de la Salud)
Mellado Artigas, Ricard (Hospital Clínic i Provincial de Barcelona)
Madorno, Matías (Instituto Tecnológico de Buenos Aires)
Blanch, Lluís (Parc Taulí Hospital Universitari. Institut d'Investigació i Innovació Parc Taulí (I3PT))
Brochard, Laurent (University of Toronto. Interdepartmental Division of Critical Care Medicine)
Universitat Autònoma de Barcelona. Departament de Medicina

Data:	2021
Resum:	Reverse triggering (RT) is a dyssynchrony defined by a respiratory muscle contraction following a passive mechanical insufflation. It is potentially harmful for the lung and the diaphragm, but its detection is challenging. Magnitude of effort generated by RT is currently unknown. Our objective was to validate supervised methods for automatic detection of RT using only airway pressure (Paw) and flow. A secondary objective was to describe the magnitude of the efforts generated during RT. We developed algorithms for detection of RT using Paw and flow waveforms. Experts having Paw, flow and esophageal pressure (Pes) assessed automatic detection accuracy by comparison against visual assessment. Muscular pressure (Pmus) was measured from Pes during RT, triggered breaths and ineffective efforts. Tracings from 20 hypoxemic patients were used (mean age 65 ± 12 years, 65% male, ICU survival 75%). RT was present in 24% of the breaths ranging from 0 (patients paralyzed or in pressure support ventilation) to 93. 3%. Automatic detection accuracy was 95. 5%: sensitivity 83. 1%, specificity 99. 4%, positive predictive value 97. 6%, negative predictive value 95. 0% and kappa index of 0. 87. Pmus of RT ranged from 1. 3 to 36. 8 cmH0, with a median of 8. 7 cmH0. RT with breath stacking had the highest levels of Pmus, and RTs with no breath stacking were of similar magnitude than pressure support breaths. An automated detection tool using airway pressure and flow can diagnose reverse triggering with excellent accuracy. RT generates a median Pmus of 9 cmHO with important variability between and within patients. BEARDS, NCT03447288.
Ajuts:	Agencia Estatal de Investigación RTC-2017-6193-1
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Reverse triggering ; Dyssynchrony ; Mechanical ventilation ; Lung and diaphragm protection ; Respiratory muscles
Publicat a:	Critical care, Vol. 25 (february 2021) , ISSN 1466-609X

DOI: 10.1186/s13054-020-03387-3
PMID: 33588912

10 p, 1.6 MB

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