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Patient-ventilator interaction using autoencoder derived magnitude of asynchrony breathing

Loo, Nien Loong and Chiew, Yeong Shiong and Shuen Ang, Christopher Yew and Tan, Chee Pin and Mat Nor, Mohd Basri (2023) Patient-ventilator interaction using autoencoder derived magnitude of asynchrony breathing. IFAC-PapersOnLine, 56 (2). pp. 2067-2072. ISSN 2405-8971 E-ISSN 2405-8963

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Abstract

The occurrence of asynchronous breathing (AB) is prevalent during mechanical ventilation (MV) treatment. Despite studies being carried out to elucidate the impact of AB on MV patients, the asynchrony index, a metric to describe the patient-ventilator interaction, may not be sufficient to quantify the severity of each AB fully in MV patients. This research investigates the feasibility of using a machine learning-derived metric, the ventilator interaction index, to describe a patient’s interaction with a mechanical ventilator. VI is derived using the magnitude of a breath’s asynchrony to measure how well patient is interacting with the ventilator. 1,188 hours of hourly and for 13 MV patients were computed using a convolution neural network and an autoencoder. Pearson’s correlation analysis between patients’ and versus their levels of partial pressure oxygen (PaO2) and partial pressure of carbon dioxide (PaCO2) was carried out. In this patient cohort, the patients’ median is 38.4% [Interquartile range (IQR): 25.9-48.8], and the median is 86.0% [IQR: 76.5-91.7]. Results show that high AI does not necessarily predispose to low. This difference suggests that every AB poses a different magnitude of asynchrony that may affect patient’s PaO2 and PaCO2. Quantifying hourly along with during MV could be beneficial in explicating the aetiology of AB.

Item Type: Article (other)
Additional Information: 5608/110341
Uncontrolled Keywords: Asynchronous breathing, Magnitude of asynchrony, Asynchrony index
Subjects: R Medicine > RC Internal medicine > RC82 Medical Emergencies, Critical Care, Intensive Care, First Aid
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: 22 Jan 2024 09:18
Last Modified: 22 Jan 2024 09:18
URI: http://irep.iium.edu.my/id/eprint/110341

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