Expiratory flow limitation during mechanical ventilation: real-time detection and physiological subtypes

Junhasavasdikul, D., Kasemchaiyanun, A., Tassaneyasin, T. et al. Expiratory flow limitation during mechanical ventilation: real-time detection and physiological subtypes. Crit Care 28, 171 (2024). https://doi.org/10.1186/s13054-024-04953-9

Abstract

Tidal expiratory flow limitation (EFLT) complicates mechanical ventilation, traditionally diagnosed through specific manoeuvres. This study explores using instantaneous analysis of expiratory resistance (Rex) for real-time EFLT detection without altering ventilator settings. The study aimed to determine the agreement between Rex analysis and the PEEP reduction manoeuvre for EFLT detection and to explore Rex patterns.

Introduction

Expiratory flow limitation (EFL) occurs when expiratory flow cannot increase despite higher driving pressure, commonly seen in patients with airway diseases during mechanical ventilation. EFLT leads to air-trapping and intrinsic PEEP, contributing to adverse outcomes like dyspnea, asynchronies, and extubation failure. The current EFLT detection methods involve changes in expiratory driving pressure or flow interruptions, which are cumbersome. This study hypothesizes that real-time analysis of Rex could detect EFLT without additional manoeuvres.

Methods

The study was conducted at Ramathibodi Hospital in Bangkok, Thailand, involving 339 patients undergoing mechanical ventilation. Patients aged 15 and older with stable ventilatory settings were included. A PEEP reduction manoeuvre from 5 cmH2O to zero was performed, and waveforms were recorded for offline Rex analysis. Lung mechanics and clinical outcomes were collected. The Rex method was validated with an independent dataset.

Results

The prevalence of EFLT was 16.5% using the PEEP reduction manoeuvre and 20% using the Rex method, with a 90.3% agreement between methods. In the validation dataset, the agreement was 91.4%. Patients with EFLT had higher hospital mortality. Three Rex patterns were identified: no EFLT, early EFLT (associated with airway diseases), and late EFLT (associated with non-airway diseases like obesity). Early EFLT patients were less responsive to external PEEP.

Discussion

EFLT is prevalent in mechanically ventilated patients, with varying rates based on detection methods. The Rex method demonstrated excellent agreement with the PEEP reduction manoeuvre, allowing real-time EFLT detection and classification into early and late subtypes. Early EFLT, associated with airway diseases, showed a continuous rise in Rex from the start of expiration, while late EFLT, linked to non-airway conditions, exhibited a rise in Rex later in expiration. These subtypes suggest different underlying mechanisms and responses to PEEP.

Conclusion

The Rex method provides a reliable, real-time approach to detecting and classifying EFLT, with excellent agreement with traditional methods. Identifying EFLT subtypes can guide better clinical management, particularly regarding PEEP application.

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Discussion Questions:

1. How could the real-time detection of EFLT using the Rex method influence the management of mechanically ventilated patients?
2. What are the clinical implications of distinguishing between early and late EFLT subtypes in terms of treatment strategies?
3. How might the Rex method be integrated into routine clinical practice to improve patient outcomes and streamline EFLT detection?

Javier Amador-Casta?eda, BHS, RRT, FCCM, PNAP

Interprofessional Critical Care Network (ICCN)

ceo@iccn2023.net

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