Jennifer L. Knopp , Yeong Shiong Chiew , Dimitrios Georgopoulos , Geoffrey M. Shaw , J. Geoffrey Chase
{"title":"Ubiquity of models describing inspiratory effort dynamics in patients on pressure support ventilation","authors":"Jennifer L. Knopp , Yeong Shiong Chiew , Dimitrios Georgopoulos , Geoffrey M. Shaw , J. Geoffrey Chase","doi":"10.1016/j.ifacsc.2024.100250","DOIUrl":null,"url":null,"abstract":"<div><p>Mechanical Ventilation (MV) is an important therapy in the intensive care unit (ICU). Assisted spontaneous breathing (ASB) MV modes are a key and growing part of MV care, as they require less sedation and help avoid muscle atrophy. Equally, a lack of standardised approaches to MV care has led to the rise of model-based methods, which typically cannot estimate spontaneous breathing (SB) efforts, and are thus not able to be used for ASB MV. To address this issue, several models of SB effort have been created, though they require specialised added sensors and/or maneuvers. ►This research utilises a unique observational clinical dataset, which includes esophageal and gastric pressure measurements not typically taken in the ICU for N=6 patients. These measurements enable more direct model-based estimation of muscular pressure effort in SB MV patients. The data is analysed for all 6 patients for 3 models which include dynamics common to the current models. Models are assessed based on model fit. ►The results show all 3 models are unable to capture dynamics in 2 patients due to added muscular dynamics in their breathing, violating assumptions in the model dynamics or constraints. These results indicate the need for more flexible models and associated identification methods to better capture these dynamics.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"27 ","pages":"Article 100250"},"PeriodicalIF":1.8000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC Journal of Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468601824000117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Mechanical Ventilation (MV) is an important therapy in the intensive care unit (ICU). Assisted spontaneous breathing (ASB) MV modes are a key and growing part of MV care, as they require less sedation and help avoid muscle atrophy. Equally, a lack of standardised approaches to MV care has led to the rise of model-based methods, which typically cannot estimate spontaneous breathing (SB) efforts, and are thus not able to be used for ASB MV. To address this issue, several models of SB effort have been created, though they require specialised added sensors and/or maneuvers. ►This research utilises a unique observational clinical dataset, which includes esophageal and gastric pressure measurements not typically taken in the ICU for N=6 patients. These measurements enable more direct model-based estimation of muscular pressure effort in SB MV patients. The data is analysed for all 6 patients for 3 models which include dynamics common to the current models. Models are assessed based on model fit. ►The results show all 3 models are unable to capture dynamics in 2 patients due to added muscular dynamics in their breathing, violating assumptions in the model dynamics or constraints. These results indicate the need for more flexible models and associated identification methods to better capture these dynamics.