Dear Editor,

Patient-ventilator asynchrony (PVA) is a prevalent and frequently underrecognized issue among patients receiving mechanical ventilation.^(1-5) High rates of asynchrony have been associated with prolonged mechanical ventilation, increased intensive care unit length of stay, and may contribute to ventilator-induced lung injury.^(1,3,6,7) Despite clinicians’ efforts to optimize ventilation by adjusting ventilator settings, asynchrony often persists because of the inherent limitations of conventional triggering and cycling algorithms. ^(3,8) Recently, an international Delphi consensus study highlighted that several clinically relevant PVAs are difficult to detect reliably using standard ventilator waveforms alone, underscoring the persistent gap between their clinical importance and bedside recognition.⁽⁵⁾

Traditional triggering mechanisms, such as pressure- and flow-based triggering, are particularly susceptible to the effects of intrinsic positive end-expiratory pressure (auto-PEEP), in which delayed or missed triggering events frequently occur.^(1,3,4,8) Likewise, conventional fixed flow-cycling criteria, which preset the termination of inspiration at 25% of peak inspiratory flow, may fail to account for variations in patient effort, respiratory mechanics, or disease state.^(1,8,9) These limitations can lead to premature or delayed cycling during pressure support ventilation, ultimately impairing patient-ventilator synchrony and reducing patient comfort.^(1,3-5)

To address these limitations, advanced adaptive algorithms have been developed to enhance the precision and responsiveness of ventilator triggering and cycling.^(3,4,8) AdaptiveSync is a feature implemented in the latest generation of mechanical ventilators and is available for both adult and pediatric patients weighing ≥10.0kg. It consists of two complementary components: (i) AdaptiveTrigger (A_TRIG) for inspiratory triggering and (ii) Adaptive Cycle (A_CYCLE) for expiratory cycling. A_TRIG employs a multiparameter algorithm that integrates pressure, flow, and the rate of flow change estimated proximally to the patient's endotracheal tube. This approach enables a dynamic, individualized trigger response that continuously adapts to variations in patient effort and respiratory mechanics.^(4,8) A_CYCLE, in turn, determines the optimal end of inspiration by analyzing the patient's expiratory time constant, inspiratory pressure above the plateau level, respiratory rate, and level of support. Together, these algorithms provide real-time adaptive optimization of both trigger sensitivity and cycling criteria.

Adaptive Sync dynamically adjusts ventilator performance across a broad spectrum of respiratory mechanics. In obstructive pathophysiology, such as chronic obstructive pulmonary disease (COPD), in which auto-PEEP is frequently present, the system supports high-sensitivity triggering. In restrictive conditions, such as acute respiratory distress syndrome (ARDS), it provides greater robustness against auto-triggering.^(1,6,8) A_TRIG has three operational settings: (i) High sensitivity - which enables triggering during auto-PEEP or when inspiratory flow remains negative and is suitable for patients with severe obstructive conditions; (ii) Standard sensitivity - which is appropriate for most clinical scenarios in the absence of significant alterations in lung mechanics; and (iii) Low sensitivity - which provides greater stability when cardiac oscillations interfere with pressure or flow signals.^(1,4,8)

A_CYCLE can be applied independently or in conjunction with A_TRIG, as expiratory cycling directly influences inspiratory triggering dynamics.^(1,8) Improved synchrony has been demonstrated when A_TRIG and A_CYCLE are activated simultaneously (Figure 1). By continuously adapting to the patient's respiratory effort and mechanics, Adaptive Sync streamlines ventilator management and promotes individualized patient-ventilator interaction. This technology offers a promising strategy for addressing asynchrony-related complications and improving clinical outcomes in patients receiving assisted or spontaneous modes during invasive or noninvasive mechanical ventilation.^(1,3,8)