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Ventilator waveform interpretation in mechanically ventilated small animals
Author(s) -
Corona Terry M.,
Aumann Marcel
Publication year - 2011
Publication title -
journal of veterinary emergency and critical care
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.886
H-Index - 47
eISSN - 1476-4431
pISSN - 1479-3261
DOI - 10.1111/j.1476-4431.2011.00673.x
Subject(s) - medicine , mechanical ventilator , ventilation (architecture) , mechanical ventilation , waveform , respiratory physiology , airway , intensive care medicine , anesthesia , respiratory system , computer science , mechanical engineering , telecommunications , radar , engineering
Objective To review the topic of ventilator waveforms analysis with emphasis on interpretation of ventilator waveforms and their use in the management and monitoring of mechanically ventilated small animal patients. Data sources Human clinical studies, scientific reviews, and textbooks, as well as veterinary textbooks and clinical examples of ventilator waveforms in mechanically ventilated dogs. Summary Ventilator waveforms are graphic representations of data collected from the ventilator and reflect patient‐ventilator interactions. The 4 parameters pressure, volume, flow, and time are most descriptive of mechanical ventilation. Typically, 3 different graphs, also referred to as scalars, consisting of pressure versus time, volume versus time, and flow versus time, with time always plotted on the x ‐axis, are used. Changes in the ventilator settings as well as in the characteristics of the lungs such as airway resistance ( R aw ) and respiratory system compliance ( C rs ) can be recognized from specific variations in the waveforms. Flow‐volume and pressure‐volume loops provide additional information about changes in lung function. Patient‐ventilator dyssynchrony is a common problem during mechanical ventilation and can lead to patient discomfort and an increased work of breathing. Ventilator waveforms are helpful to identify dyssynchrony, which can be divided into trigger, flow, cycle, and expiratory dyssynchrony. Ventilator waveforms allow the clinician to assess changes in respiratory mechanics, and can be useful in monitoring the progression of disease pathology and response to therapy. Adjustments in ventilator settings based on proper analysis and interpretation of these waveforms can help the clinician to optimize ventilation therapy. Conclusions Ventilator waveforms are graphic representations of patient‐ventilator interactions. Proper interpretation of ventilator waveforms affords the critical care clinician a better understanding of the patient's respiratory function, response to therapy, and causes for patient‐ventilator dyssynchrony. Ventilator waveform interpretation is an important tool in the assessment and management of mechanically ventilated small animal patients.