BACKGROUND: The digital Auto-Trak™ system is a technology capable of automatically adjusting the triggering and cycling mechanisms during pressure support ventilation (PSV). OBJECTIVE: To compare Auto-Trak with conventional settings in terms of patient-ventilator synchrony and discomfort. METHODS:Twelve healthy volunteers underwentPSV via the mouth by breathing through an endotracheal tube. In the conventional setting, a pressure support of 8 cm H2O with flow cycling (25% peak inspiratory flow) and a sensitivity of 1 cm H2O was adjusted. In Auto-Trak the triggering and cycling were automatically set. Discomfort, effort of breathing, and the asynchrony index (AI) were assessed. In a complementary bench study, the inspiratory and expiratory time delays were quantified for both settings in three mechanical models: 'normal', obstructive (COPD), and restrictive (ARDS), using the ASL 5000 simulator. RESULTS: In the volunteer study the AI and the discomfort scores did not differ statistically between the two settings. In the bench investigation the use of Auto-Trak was associated with a greater triggering delay in the COPD model and earlier expiratory cycling in the ARDS model but with no asynchronic events. CONCLUSIONS: Use of the Auto-Trak system during PSV showed similar results in comparison to the conventional adjustments with respect to patient-ventilator synchrony and discomfort in simulated conditions of invasive mechanical ventilation.
RCT Entities:
BACKGROUND: The digital Auto-Trak™ system is a technology capable of automatically adjusting the triggering and cycling mechanisms during pressure support ventilation (PSV). OBJECTIVE: To compare Auto-Trak with conventional settings in terms of patient-ventilator synchrony and discomfort. METHODS: Twelve healthy volunteers underwent PSV via the mouth by breathing through an endotracheal tube. In the conventional setting, a pressure support of 8 cm H2O with flow cycling (25% peak inspiratory flow) and a sensitivity of 1 cm H2O was adjusted. In Auto-Trak the triggering and cycling were automatically set. Discomfort, effort of breathing, and the asynchrony index (AI) were assessed. In a complementary bench study, the inspiratory and expiratory time delays were quantified for both settings in three mechanical models: 'normal', obstructive (COPD), and restrictive (ARDS), using the ASL 5000 simulator. RESULTS: In the volunteer study the AI and the discomfort scores did not differ statistically between the two settings. In the bench investigation the use of Auto-Trak was associated with a greater triggering delay in the COPD model and earlier expiratory cycling in the ARDS model but with no asynchronic events. CONCLUSIONS: Use of the Auto-Trak system during PSV showed similar results in comparison to the conventional adjustments with respect to patient-ventilator synchrony and discomfort in simulated conditions of invasive mechanical ventilation.