Resp Care
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Monitoring of patient-ventilator interactions at the bedside involves evaluation of patient breathing pattern on ventilator settings. One goal of mechanical ventilation is to have ventilator-assisted breathing coincide with patient breathing. ⋯ The types of asynchronies discussed are trigger asynchrony (ie, breath initiation that may manifest as ineffective triggering, double-triggering, or auto-triggering); flow asynchrony (ie, breath-delivery asynchrony, which may manifest as assisted-breath delivery being faster or slower than what patient desires); and cycling asynchronies (ie, termination of assisted inspiration does not coincide with patient breath termination, which may manifest as delayed cycling or premature cycling). Various waveforms are displayed and graphically demonstrate asynchronies; basic principles of waveform interpretation are discussed.
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With current ventilator triggering design, in initiating ventilator breaths patient effort is only a small fraction of the total effort expended to overcome the inspiratory load. Similarly, advances in ventilator pressure or flow delivery and inspiratory flow termination improve patient effort or inspiratory muscle work during mechanical ventilation. Yet refinements in ventilator design do not necessarily allow optimal patient-ventilator interactions, as the clinician is key in managing patient factors and selecting appropriate ventilator factors to maintain patient-ventilator synchrony. ⋯ Wasted efforts can be aggravated by respiratory muscle weakness or other conditions that reduce respiratory drive. In the post-triggering phase, ventilator factors play an important role in patient-ventilator interaction; this role includes the assistance level, set inspiratory flow rate, T(I), pressurization rate, and cycling-off threshold, and to some extent, applied PEEP. This paper proposes an algorithm that clinicians can use to adjust ventilator settings with the goal to eliminate or reduce patients' wasted efforts.
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Patient-ventilator synchrony is a complex issue affected by ventilator performance, patient characteristics, and the patient-ventilator interface. The history of patient-ventilator interaction includes avoidance of pharmacalogic paralysis, the development of spontaneous breathing systems, microprocessor technology to maximize interaction, and closed-loop control. While most clinicians agree that patient-ventilator synchrony is desirable, there remain no cause-and-effect data that asynchrony is associated with poor outcome.
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Mechanical ventilation can be life-saving for patients with acute respiratory failure. In between the 2 extremes of complete and no ventilatory support, both patient and machine contribute to ventilatory work. Ideally, ventilator gas delivery would perfectly match patient demand. ⋯ Its prevalence depends on numerous factors, including timing and duration of observation, technique used for detection, patient population, type of asynchrony, ventilation mode and settings (eg, trigger, flow, and cycle criteria), and confounding factors (eg, state of wakefulness, sedation). Patient-ventilator asynchrony is associated with adverse effects, including higher/wasted work of breathing, patient discomfort, increased need for sedation, confusion during the weaning process, prolonged mechanical ventilation, longer stay, and possibly higher mortality. Whether asynchrony is a marker of poor prognosis or causes these adverse outcomes remains to be determined.
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Assisted (interactive) breathing is generally preferred to controlled breaths in patients on mechanical ventilators. Assisted breaths allow the patient's respiratory muscles to be used, and ventilatory muscle atrophy can be prevented. Moreover, the respiratory drive of the patient does not have to be aggressively blunted. ⋯ Current ventilation modes have a number of features that can monitor and enhance synchrony, including adjustment of the trigger variable, the use of pressure-targeted versus fixed-flow-targeted breaths, and manipulations of the cycle variable. Clinicians need to know how to use these ventilation mode and monitor them properly, especially understanding the airway pressure and flow graphics. The clinical challenge is synchronizing ventilator gas delivery with patient effort.