Validation of an automated patient-ventilator asynchrony detection algorithm

Abstract

Background: Patient-ventilator asynchrony (PVA) is common in ventilated patients and associated with poor outcomes. However, it is underrecognized due to challenging identification. Automated algorithms aid, but are limited to few PVA types, lack validation, or operate offline [Rietveld et al, ICMx 2025, PMID:40119215]. Aim: To validate an AI-based algorithm (Deep Breath) that detects multiple PVAs in real-time (ineffective effort, reverse/double/delayed trigger and premature/delayed cycling). Methods: Ventilator and esophageal pressure (Pes) waveforms from 24 ventilated patients were collected. 5169 Breaths were labeled for PVA by 3 clinicians, out of a pool of 12, via dedicated software (Figure 1). Ground truth was set by majority voting or consensus. The same breaths were classified by the algorithm, using only ventilator waveforms (no Pes). We evaluated performance using recall, specificity and F1-score. Validation required ≥0.95 normal breath specificity and ≥0.8 recall per PVA type. Results: The algorithm accurately detects PVA, with a macro recall, specificity and F1-score of 0.83, 0.96 and 0.81, respectively. Minimum PVA recall (0.8, delayed trigger) and normal breath specificity (0.97) were above set validation criteria (Table 1). Conclusion: This novel algorithm is capable of real-time, accurate detection of multiple PVA types using only standard ventilator waveforms, offering a versatile solution for accurate PVA monitoring. erjor;12/suppl_17/44/F1 F1 F1

Authors 13

1. Thijs P. Rietveld

   Erasmus MC

   Affiliation as printed

   1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands

2. Petra J. Rietveld Aachen 2Adult Intensive Care

   Leiden University Medical Center

   Affiliation as printed

   2Adult Intensive Care, Leiden University Medical Center, Leiden, Netherlands

3. Björn J. P. van der Ster

   Erasmus MC

   Affiliation as printed

   1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands

4. Diederik A M P J Gommers

   Erasmus MC

   Affiliation as printed

   1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands

5. L. Felipe Damiani

   Pontificia Universidad Católica de Chile

   Affiliation as printed

   4Departamento de Ciencias de la Salud, Pontificia Universidad Católica de Chile, Santiago, Chile

6. Franciska van der Velde-Quist Aachen 2Adult Intensive Care

   Leiden University Medical Center

   Affiliation as printed

   2Adult Intensive Care, Leiden University Medical Center, Leiden, Netherlands

7. Henrik Endeman

   OLVG

   Affiliation as printed

   5Adult Intensive Care, Erasmus Medical Center & Intensive Care, OLVG, Rotterdam, Amsterdam, Netherlands

8. Jacob W. M. Snoep Aachen 2Adult Intensive Care

   Leiden University Medical Center

   Affiliation as printed

   2Adult Intensive Care, Leiden University Medical Center, Leiden, Netherlands

9. Julien P. van Oosten

   Erasmus MC

   Affiliation as printed

   1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands

10. Juliette Francovich

    Erasmus MC

    Affiliation as printed

    1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands

11. Nico G. Goedendorp

    Erasmus MC

    Affiliation as printed

    1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands

12. Abraham Schoe Aachen 2Adult Intensive Care

    Leiden University Medical Center

    Affiliation as printed

    2Adult Intensive Care, Leiden University Medical Center, Leiden, Netherlands

13. Annemijn H. Jonkman

    Erasmus MC

    Affiliation as printed

    1Adult Intensive Care, Erasmus Medical Center, Rotterdam, Netherlands