International study conducted in 20 countries through an online survey. Participants: Physicians, respiratory therapists, nurses and physiotherapists that are currently working at the Intensive Care Unit (ICU). Main variables of interest: Univariate 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) with the ability of HCPs to correctly identify and manage 6 PVA. Results: A total of 431 HCPs answered a validated survey. The main factors associated with the proper recognition of PVA were: specific training program in mechanicalventilation (MV) (OR 2.27; 95% CI 1.14-4.52; p = 0.019), courses with more than 100 hours completed (OR 2.28; 95% CI 1.29-4.03; p = 0.005) and the number of intensive care unit (ICU) beds (OR 1.037; 95% CI 1.01-1.06; p = 0.005). The main factor that influenced PVA management was recognizing 6 PVA correctly (OR 118.98;; p < 0.001).
Conclusion:Identifying and managing PVA using ventilator waveform analysis is influenced by many factors including specific training programs in MV, number of ICU beds and the recognized number of PVA.
International study conducted in 20 countries through an online survey. Participants: Physicians, respiratory therapists, nurses and physiotherapists that are currently working at the Intensive Care Unit (ICU). Main variables of interest: Univariate 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) with the ability of HCPs to correctly identify and manage 6 PVA. Results: A total of 431 HCPs answered a validated survey. The main factors associated with the proper recognition of PVA were: specific training program in mechanicalventilation (MV) (OR 2.27; 95% CI 1.14-4.52; p = 0.019), courses with more than 100 hours completed (OR 2.28; 95% CI 1.29-4.03; p = 0.005) and the number of intensive care unit (ICU) beds (OR 1.037; 95% CI 1.01-1.06; p = 0.005). The main factor that influenced PVA management was recognizing 6 PVA correctly (OR 118.98;; p < 0.001).
Conclusion:Identifying and managing PVA using ventilator waveform analysis is influenced by many factors including specific training programs in MV, number of ICU beds and the recognized number of PVA.
Brazil that aim to understand the effects, applicability and mechanisms of isometric handgrip exercise. For this, we will analyze the effects of isometric handgrip training on different populations (hypertensive, peripheral artery disease patients and obstructive sleep apnea patients) and contexts (ie clinical, unsupervised and laboratory). Thus, the aim of this study was to describe the rationale and design behind the ISOPRESS network, presenting the methods employed. Methods Rationale The ISOPRESS network was developed to analyze the effects of isometric handgrip training on cardiovascular variables in
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