Airway pressure release ventilation (APRV) is inverse ratio, pressure controlled, intermittent mandatory ventilation with unrestricted spontaneous breathing. It is based on the principle of open lung approach. It has many purported advantages over conventional ventilation, including alveolar recruitment, improved oxygenation, preservation of spontaneous breathing, improved hemodynamics, and potential lung-protective effects. It has many claimed disadvantages related to risks of volutrauma, increased work of breathing, and increased energy expenditure related to spontaneous breathing. APRV is used mainly as a rescue therapy for the difficult to oxygenate patients with acute respiratory distress syndrome (ARDS). There is confusion regarding this mode of ventilation, due to the different terminology used in the literature. APRV settings include the "P high," "T high," "P low," and "T low". Physicians and respiratory therapists should be aware of the different ways and the rationales for setting these variables on the ventilators. Also, they should be familiar with the differences between APRV, biphasic positive airway pressure (BIPAP), and other conventional and nonconventional modes of ventilation. There is no solid proof that APRV improves mortality; however, there are ongoing studies that may reveal further information about this mode of ventilation. This paper reviews the different methods proposed for APRV settings, and summarizes the different studies comparing APRV and BIPAP, and the potential benefits and pitfalls for APRV.

Airway pressure release ventilation was introduced to clinical practice about two decades ago as an alternative mode for mechanical ventilation; however, it had not gained popularity until recently as an effective safe alternative for difficult-to-oxygenate patients with acute lung injury/ acute respiratory distress syndrome This review will cover the definition and mechanism of airway pressure release ventilation, its advantages, indications, and guidance.

BACKGROUND: New-generation ventilators display dynamic measures of respiratory mechanics, such as compliance, resistance, and auto-PEEP. Knowledge of the respiratory mechanics is paramount to clinicians at the bedside. These calculations are obtained automatically by using the least squares fitting method of the equation of motion. The accuracy of these calculations in static and dynamic conditions have not been fully validated or examined in different clinical conditions or various ventilator modes. METHODS: A bench study was performed by using a lung simulator to compare the ventilator automated calculations during passive and active conditions. Three clinical scenarios (normal, COPD, and ARDS) were simulated with known compliances and resistance set per respective condition: normal (compliance 50 mL/cm H 2 O, resistance 10 cm H 2 O/L/s), COPD (compliance 60 mL/cm H 2 O, resistance 22 cm H 2 O/L/s), and ARDS (compliance 30 mL/cm H 2 O, and resistance 13 cm H 2 O/L/s). Each scenario was subjected to 4 different muscle pressures (P mus): 0, ؊5, ؊10, and ؊15 cm H 2 O. All the experiments were done using adaptive support ventilation. The resulting automated dynamic calculations of compliance and resistance were then compared based on the clinical scenarios. RESULTS: There was a small bias (average error) and level of agreement in the passive conditions in all the experiments; however, these errors and levels of agreement got progressively higher proportional to the increased P mus. There was a strong positive correlation between P mus and compliance measured as well as a strong negative correlation between P mus and resistance measured. CONCLUSIONS: Automated displayed calculations of respiratory mechanics were not dependable or accurate in active breathing conditions. The calculations were clinically more reliable in passive conditions. We propose different methods of calculating P mus , which, if incorporated into the calculations, would improve the accuracy of respiratory mechanics made via the least squares fitting method in actively breathing conditions.

Most clinicians pay attention to tidal volume and airway pressures and their curves during mechanical ventilation. On the other hand, inspiratory-expiratory flow curves also provide a plethora of information, but much less attention is paid to them. Flow curves chronologically show the velocity and direction of inspiration and expiration and are influenced by the respiratory mechanics, the patient's effort, and the mode of ventilation and its settings. When the ventilator setting does not synchronize with the patient's respiratory pattern, the patient can easily have worsening breathing effort, patient-ventilator asynchrony, which can lead to prolonged ventilator support or lung injury. The information provided by the flow curves during mechanical ventilation, such as respiratory mechanics, the patient's effort, and patient-ventilator interactions, are very helpful when adjusting the ventilator setting. If clinicians can monitor and assess the flow curves information appropriately, it can be a useful diagnostic and therapeutic tool at the bedside. There may be association between inspiratory effort and flow, and this may further guide us, especially in the weaning process and when patients are not synchronizing with the ventilator. In this review, we try to gather information about "flow" that is scattered around in the literature and textbooks in one place. We will summarize the different flow waveforms utilized in commonly used ventilator modes with their advantages and disadvantages, information gained by the flow curves (i.e., flow-time, flow-volume, and flow-pressure), how to detect and manage asynchronies, and some ideas for future uses. Flow waveforms shapes and patterns are very beneficial for the management of patients undergoing mechanical ventilatory support. Attention to those waveforms can potentially improve patient outcomes. Clinicians should be familiar with this information and how to act upon them.

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