📜 Journal Club: Consensus on identifying and ranking ventilator asynchronies in invasively ventilated ICU patients: a modified Delphi study (SYNAPsE)
By: BETINA SANTOS TOMAZ, FISIOTERAPEUTA - 05/22/2026 13:27
📊 International consensus on patient–ventilator asynchronies: what changes in practice?
The identification and management of patient–ventilator asynchronies (PVA) remain among the greatest bedside challenges in invasive mechanical ventilation. Despite decades of research, important gaps still existed: which asynchronies truly matter? Which can we reliably detect in clinical practice? And which should be prioritized?
A recent study published in Intensive Care Medicine brought an important step forward by proposing an international consensus based on the Delphi method (SYNAPsE), bringing together experts to address these questions in a structured way.
Source: Molenaar MA, Nasa P, Damiani LF, Ferreira JC, et al. Intensive Care Med. 2026 Mar;52(3):423–433.
🧠 Which asynchronies are considered clinically relevant?
The consensus identified 7 main types of clinically relevant asynchronies:
- Ineffective triggering
- Reverse triggering
- Double triggering
- Auto-triggering
- Insufficient inspiratory flow
- Premature cycling
- Delayed cycling
👉 An important point: not everything we see on ventilator waveforms is necessarily an “asynchrony.” For example, excess inspiratory flow was not considered a PVA itself, but rather a ventilatory setting issue that may lead to asynchrony.
👀 What can we reliably identify using ventilator waveforms alone?
In real-world practice, esophageal pressure monitoring is rarely available. Therefore, the consensus focused on what is feasible at the bedside.
✔️ Detectable with good reliability:
- Double triggering
- Ineffective triggering
- Reverse triggering
- Insufficient inspiratory flow
- Premature cycling
❌ More difficult to identify using waveforms alone:
- Auto-triggering
- Delayed cycling
👉 This reinforces what we experience in daily practice: waveform interpretation is not trivial—it requires training and continuous attention.
⚠️ Which asynchronies have the greatest impact on outcomes?
There was strong agreement among experts:
🔴 Most clinically relevant:
- Double triggering
- Ineffective triggering
These were associated with:
- Longer duration of mechanical ventilation
- Higher mortality (particularly in ARDS)
💡 Pathophysiologically, this makes sense:
- Double triggering → breath stacking → increased risk of VILI
- Ineffective triggering → wasted effort → increased work of breathing and diaphragmatic dysfunction
🫁 What about patients with ARDS?
The consensus was even more direct:
📌 Severity ranking (when unrecognized and untreated):
- Double triggering
- Ineffective triggering
- Reverse triggering
👉 In other words, not all asynchronies carry the same clinical weight—and this directly influences bedside priorities.
🔄 What about other clinical scenarios?
For patients without ARDS or in the postoperative cardiac surgery setting, no rigid ranking consensus was reached.
👉 A more pragmatic approach was proposed:
Classify asynchronies as “severe” vs “mild” based on:
- Impact on duration of mechanical ventilation
- Patient discomfort
- Hemodynamic instability
🚨 Why does this matter?
Although frequent, asynchronies are:
- Underdiagnosed
- Dependent on continuous waveform interpretation
- Often merely “markers” of a broader problem (e.g., high respiratory drive, pain, acidosis, etc.)
👉 Detecting the asynchrony is only the first step.
👉 The real challenge is understanding why it is happening.
🔮 The future: where are we heading?
The study also highlights clear directions:
- Development of automated detection systems
- Integration with artificial intelligence
- Continuous real-time monitoring
- Personalized ventilator adjustment strategies
💬 Take-home message
✔️ Not all asynchronies have the same clinical impact
✔️ Double triggering and ineffective triggering should be prioritized
✔️ Not everything can be detected from waveforms alone
✔️ Clinical context is essential
✔️ We need to evolve toward continuous monitoring
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