Abstract
Mechanical ventilation (MV) parameters and other physiological parameters determined from mechanically ventilated respiratory failure patients can be used to estimate patient-centred outcomes. However, there is a lack of analysis of these ventilation parameters continuously to provide useful clinical insight into patients' disease state, progression as well as evaluation of MV treatment management. This paper presents a model-based analysis on patient-specific respiratory mechanics and MV breath parameters for a clinical observational trial. This study includes 15 patients, with 24 hours of MV data analysed per patient. A total of 385,438 breaths were analysed for this patient cohort. Model-based identification of patient-specific respiratory mechanics yielded a median [interquartile range, IQR] Ers and Rrs of 28.66 cmH2 O/L [24.81-35.92] and 8.86 cmH2 O/L/s [6.11-12.78]. Out of 15 patients, 10 patients have less than 10% of MV parameters (VT, PPlat, PIP, driving pressure, PEEP and MP) falling into the safe ranges described by lung protective strategies and in literature. Analysis of patient arterial blood gas values (ABG) yielded a median PaCO2, PaO2 and pH of 38.0 mmHg [31.7-43.0], 90.2 mmHg [73.9-119.0], and 7.38 [7.32-7.42] respectively. Respiratory mechanics, parameters and haemodynamics are patient-specific and time-varying. Model-based methods enable continuous, concurrent, and real-time monitoring of breath parameters, aiding clinicians in titrating and providing an optimal balance between various ventilator settings while preventing patient harm.Clinical Relevance-Simultaneous and real-time analysis of patient-specific respiratory mechanics and parameters in this clinical observational trial show low compliance rates with respect to lung protective strategies in mechanical ventilation treatment.
Original language | English |
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Title of host publication | 7th IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2022 - Proceedings |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 100-105 |
Number of pages | 6 |
ISBN (Electronic) | 9781665494694 |
DOIs | |
Publication status | Published - 2022 |
Event | IEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2022 - Online, Malaysia Duration: 7 Dec 2022 → 9 Dec 2022 Conference number: 7th https://ieeexplore.ieee.org/xpl/conhome/10079231/proceeding (Proceedings) https://www.iecbes.org/ (Website) |
Conference
Conference | IEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2022 |
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Abbreviated title | IECBES 2022 |
Country/Territory | Malaysia |
Period | 7/12/22 → 9/12/22 |
Internet address |
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