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Stochastic modelling of respiratory system elastance for mechanically ventilated respiratory failure patients

Wai Lee, Jay Wing and Chiew, Yeong Shiong and Wang, Xin and Tan, Chee Pin and Mat Nor, Mohd Basri and Damanhuri, Nor Salwa and Chase, Geoffrey and UNSPECIFIED and UNSPECIFIED (2021) Stochastic modelling of respiratory system elastance for mechanically ventilated respiratory failure patients. Annals of Biomedical Engineering. pp. 1-16. ISSN 00906964 E-ISSN 15216047

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While lung protective mechanical ventilation (MV) guidelines have been developed to avoid ventilator induced lung injury (VILI), a one-size-fits-all approach cannot benefit every individual patient. Hence, there is significant need for the ability to provide patient-specific MV settings to ensure safety, and optimise patient care. Model based approaches enable patient-specific care by identifying time-varying patient-specific parameters, such as respiratory elastance, Ers, to capture inter- and intra-patient variability. However, patient-specific parameters evolve with time, as a function of disease progression and patient condition, making predicting their future values crucial for recommending patient-specific MV settings. This study employs stochastic modelling to predict future Ers values using retrospective patient data to develop and validate a model indicating future intra-patient variability of Ers. Cross validation results show stochastic modelling can predict future elastance ranges with 92.59 and 68.56% of predicted values within the 5–95% and the 25–75% range, respectively. This range can be used to ensure patients receive adequate minute ventilation should elastance rise and minimise the risk of VILI should elastance fall. The results show the potential for model-based protocols using stochastic model prediction of future Ers values to provide safe and patient-specific MV. These results warrant further investigation to validate its clinical utility.

Item Type: Article (Journal)
Additional Information: 5608/92724
Uncontrolled Keywords: Mechanical ventilation, Stochastic modelling, Respiratory mechanics, Patient-specific ventilation, Elastance, Critical care.
Subjects: R Medicine > RC Internal medicine > RC731 Specialties of Internal Medicine-Diseases of The Respiratory System
R Medicine > RC Internal medicine > RC82 Medical Emergencies, Critical Care, Intensive Care, First Aid
T Technology > TJ Mechanical engineering and machinery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Medicine > Department of Anaesthesiology & Intensive Care
Kulliyyah of Medicine
Depositing User: Dr. Mohd Basri Mat Nor
Date Deposited: 28 Oct 2021 11:36
Last Modified: 28 Oct 2021 11:36
URI: http://irep.iium.edu.my/id/eprint/92724

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