• I I Ramírez, R S Adasme, D H Arellano, A R M Rocha, F M D Andrade, J Núñez-Silveira, N A Montecinos, S Dias, L F Damiani, R Gutierrez-Arias, B Lobo-Valbuena, and F Gordo-Vidal.
• Escuela de Kinesiología, Facultad de Medicina, Universidad de los Andes, Santiago, Chile; Division of Critical Care Medicine, Hospital Clinico de la Universidad de Chile, Santiago, Chile. Electronic address: iramirez@miuandes.cl.
• Med Intensiva. 2021 Apr 1; 45 (3): 138-146.

ObjectiveTo describe the main factors associated with proper recognition and management of patient-ventilator asynchrony (PVA).DesignAn analytical cross-sectional study was carried out.SettingAn international study conducted in 20 countries through an online survey.ParticipantsPhysicians, respiratory therapists, nurses and physiotherapists currently working in the Intensive Care Unit (ICU).Main Variables Of InterestUnivariate and multivariate logistic regression models were used to establish associations between all variables (profession, training in mechanical ventilation, type of training program, years of experience and ICU characteristics) and the ability of HCPs to correctly identify and manage 6 PVA.ResultsA total of 431 healthcare professionals answered a validated survey. The main factors associated to proper recognition of PVA were: specific training program in mechanical ventilation (MV) (OR 2.27; 95%CI 1.14-4.52; p=0.019), courses with more than 100h completed (OR 2.28; 95%CI 1.29-4.03; p=0.005), and the number of ICU beds (OR 1.037; 95%CI 1.01-1.06; p=0.005). The main factor influencing the management of PVA was the correct recognition of 6 PVAs (OR 118.98; 95%CI 35.25-401.58; p<0.001).ConclusionIdentifying and managing PVA using ventilator waveform analysis is influenced by many factors, including specific training programs in MV, the number of ICU beds, and the number of recognized PVAs.Copyright © 2019 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

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