Protocol conception for safe selection of mechanical ventilation settings for respiratory failure Patients

被引:7
作者
Lee, Jay Wing Wai [1 ]
Chiew, Yeong Shiong [1 ]
Wang, Xin [1 ]
Tan, Chee Pin [1 ]
Nor, Mohd Basri Mat [2 ]
Cove, Matthew E. [3 ]
Damanhuri, Nor Salwa [4 ]
Chase, J. Geoffrey [5 ]
机构
[1] Monash Univ Malaysia, Sch Engn, Subang Jaya, Selangor, Malaysia
[2] Int Islamic Univ Malaysia, Kulliyah Med, Pahang, Malaysia
[3] Natl Univ Hlth Syst, Dept Med, Div Resp & Crit Care Med, Singapore, Singapore
[4] Univ Teknol MARA, Fac Elect Engn, Cawangan Pulau Pinang, George Town, Malaysia
[5] Univ Canterbury, Ctr Bioengn, Christchurch, New Zealand
关键词
Respiratory failure; Mechanical ventilation; Respiratory mechanics; and decision making; END-EXPIRATORY PRESSURE; ACUTE LUNG INJURY; DISTRESS-SYNDROME; CARE; MODEL; ARDS; BEDSIDE; SYSTEM; VOLUME;
D O I
10.1016/j.cmpb.2021.106577
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Background and Objective: Mechanical ventilation is the primary form of care provided to respiratory failure patients. Limited guidelines and conflicting results from major clinical trials means selection of mechanical ventilation settings relies heavily on clinician experience and intuition. Determining optimal mechanical ventilation settings is therefore difficult, where non-optimal mechanical ventilation can be deleterious. To overcome these difficulties, this research proposes a model-based method to manage the wide range of possible mechanical ventilation settings, while also considering patient-specific conditions and responses. Methods: This study shows the design and development of the "VENT" protocol, which integrates the single compartment linear lung model with clinical recommendations from landmark studies, to aid clinical decision-making in selecting mechanical ventilation settings. Using retrospective breath data from a cohort of 24 patients, 3,566 and 2,447 clinically implemented VC and PC settings were extracted respectively. Using this data, a VENT protocol application case study and clinical comparison is performed, and the prediction accuracy of the VENT protocol is validated against actual measured outcomes of pressure and volume. Results: The study shows the VENT protocols' potential use in narrowing an overwhelming number of possible mechanical ventilation setting combinations by up to 99.9%. The comparison with retrospective clinical data showed that only 33% and 45% of clinician settings were approved by the VENT protocol. The unapproved settings were mainly due to exceeding clinical recommended settings. When utilising the single compartment model in the VENT protocol for forecasting peak pressures and tidal volumes, median [IQR] prediction error values of 0.75 [0.31 - 1.83] cmH(2)O and 0.55 [0.19 - 1.20] mL/kg were obtained. Conclusions: Comparing the proposed protocol with retrospective clinically implemented settings shows the protocol can prevent harmful mechanical ventilation setting combinations for which clinicians would be otherwise unaware. The VENT protocol warrants a more detailed clinical study to validate its potential usefulness in a clinical setting. (C) 2021 Elsevier B.V. All rights reserved.
引用
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页数:17
相关论文
共 79 条
  • [51] Volume-dependent compliance in ARDS: proposal of a new diagnostic concept
    Mols, G
    Brandes, I
    Kessler, V
    Lichtwarck-Aschoff, M
    Loop, T
    Geiger, K
    Guttmann, J
    [J]. INTENSIVE CARE MEDICINE, 1999, 25 (10) : 1084 - 1091
  • [52] A virtual patient model for mechanical ventilation
    Morton, S. E.
    Dickson, J.
    Chase, J. G.
    Docherty, P.
    Desaive, T.
    Howe, S. L.
    Shaw, G. M.
    Tawhai, M.
    [J]. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2018, 165 : 77 - 87
  • [53] Prediction of lung mechanics throughout recruitment maneuvers in pressure-controlled ventilation
    Morton, Sophie E.
    Knopp, Jennifer L.
    Tawhai, Merryn H.
    Docherty, Paul
    Heines, Serge J.
    Bergmans, Dennis C.
    Moeller, Knut
    Chase, J. Geoffrey
    [J]. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2020, 197
  • [54] Optimising mechanical ventilation through model-based methods and automation
    Morton, Sophie E.
    Knopp, Jennifer L.
    Chase, J. Geoffrey
    Docherty, Paul
    Howe, Sarah L.
    Moeller, Knut
    Shaw, Geoffrey M.
    Tawhai, Merryn
    [J]. ANNUAL REVIEWS IN CONTROL, 2019, 48 : 369 - 382
  • [55] Predictive Virtual Patient Modelling of Mechanical Ventilation: Impact of Recruitment Function
    Morton, Sophie E.
    Knopp, Jennifer L.
    Chase, J. Geoffrey
    Moeller, Knut
    Docherty, Paul
    Shaw, Geoffrey M.
    Tawhai, Merryn
    [J]. ANNALS OF BIOMEDICAL ENGINEERING, 2019, 47 (07) : 1626 - 1641
  • [56] Network Data Acquisition and Monitoring System for Intensive Care Mechanical Ventilation Treatment
    Ng, Qing Arn
    Chiew, Yeong Shiong
    Wang, Xin
    Tan, Chee Pin
    Nor, Mohd Basri Mat
    Damanhuri, Nor Salwa
    Chase, J. Geoffrey
    [J]. IEEE ACCESS, 2021, 9 (09): : 91859 - 91873
  • [57] MECHANICS OF BREATHING IN MAN
    OTIS, AB
    FENN, WO
    RAHN, H
    [J]. JOURNAL OF APPLIED PHYSIOLOGY, 1950, 2 (11) : 592 - 607
  • [58] Personalized mechanical ventilation in acute respiratory distress syndrome
    Pelosi, Paolo
    Ball, Lorenzo
    Barbas, Carmen S. V.
    Bellomo, Rinaldo
    Burns, Karen E. A.
    Einav, Sharon
    Gattinoni, Luciano
    Laffey, John G.
    Marini, John J.
    Myatra, Sheila N.
    Schultz, Marcus J.
    Teboul, Jean Louis
    Rocco, Patricia R. M.
    [J]. CRITICAL CARE, 2021, 25 (01)
  • [59] Individualized PEEP Setting in Subjects With ARDS: A Randomized Controlled Pilot Study
    Pintado, Maria-Consuelo
    de Pablo, Raul
    Trascasa, Maria
    Milicua, Jose-Maria
    Rogero, Santiago
    Daguerre, Martin
    Cambronero, Jose-Andres
    Arribas, Ignacio
    Sanchez-Garcia, Miguel
    [J]. RESPIRATORY CARE, 2013, 58 (09) : 1416 - 1423
  • [60] Poor Hooman., 2018, Basics of Mechanical Ventilation