Expiratory flow limitation during mechanical ventilation: real-time detection and physiological subtypes
Issued Date
2024-12-01
Resource Type
ISSN
13648535
eISSN
1466609X
Scopus ID
2-s2.0-85193633873
Journal Title
Critical Care
Volume
28
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Critical Care Vol.28 No.1 (2024)
Suggested Citation
Junhasavasdikul D., Kasemchaiyanun A., Tassaneyasin T., Petnak T., Bezerra F.S., Mellado‐Artigas R., Chen L., Sutherasan Y., Theerawit P., Brochard L. Expiratory flow limitation during mechanical ventilation: real-time detection and physiological subtypes. Critical Care Vol.28 No.1 (2024). doi:10.1186/s13054-024-04953-9 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/98508
Title
Expiratory flow limitation during mechanical ventilation: real-time detection and physiological subtypes
Corresponding Author(s)
Other Contributor(s)
Abstract
Background: Tidal expiratory flow limitation (EFLT) complicates the delivery of mechanical ventilation but is only diagnosed by performing specific manoeuvres. Instantaneous analysis of expiratory resistance (Rex) can be an alternative way to detect EFLT without changing ventilatory settings. This study aimed to determine the agreement of EFLT detection by Rex analysis and the PEEP reduction manoeuvre using contingency table and agreement coefficient. The patterns of Rex were explored. Methods: Medical patients ≥ 15-year-old receiving mechanical ventilation underwent a PEEP reduction manoeuvre from 5 cmH2O to zero for EFLT detection. Waveforms were recorded and analyzed off-line. The instantaneous Rex was calculated and was plotted against the volume axis, overlapped by the flow-volume loop for inspection. Lung mechanics, characteristics of the patients, and clinical outcomes were collected. The result of the Rex method was validated using a separate independent dataset. Results: 339 patients initially enrolled and underwent a PEEP reduction. The prevalence of EFLT was 16.5%. EFLT patients had higher adjusted hospital mortality than non-EFLT cases. The Rex method showed 20% prevalence of EFLT and the result was 90.3% in agreement with PEEP reduction manoeuvre. In the validation dataset, the Rex method had resulted in 91.4% agreement. Three patterns of Rex were identified: no EFLT, early EFLT, associated with airway disease, and late EFLT, associated with non-airway diseases, including obesity. In early EFLT, external PEEP was less likely to eliminate EFLT. Conclusions: The Rex method shows an excellent agreement with the PEEP reduction manoeuvre and allows real-time detection of EFLT. Two subtypes of EFLT are identified by Rex analysis. Trial registration: Clinical trial registered with www.thaiclinicaltrials.org (TCTR20190318003). The registration date was on 18 March 2019, and the first subject enrollment was performed on 26 March 2019.