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    Subject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: Animal experiments and proof of concept (2011)

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    12627810_septic_shock_RV_measurements-REVISED FINAL 2.0.pdf (172.4Kb)
    Type of Content
    Journal Article
    UC Permalink
    http://hdl.handle.net/10092/5136
    
    Publisher's DOI/URI
    https://doi.org/10.1088/0967-3334/32/1/005
    
    Publisher
    University of Canterbury. Electrical and Computer Engineering
    University of Canterbury. Mechanical Engineering
    ISSN
    0967-3334
    Collections
    • Engineering: Journal Articles [1535]
    Authors
    Chase, Geoff cc
    Lambermont, B.
    Starfinger, C.
    Hann, C.E.
    Shaw, Geoff cc
    Ghuysen, A.
    Kolh, P.
    Dauby, P.C.
    Desaive, T.
    show all
    Abstract

    A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models of pulmonary embolism, hypovolemia with PEEP titrations, and induced endotoxic shock. However, these studies required both left and right heart catheters to collect the data required for subject-specific monitoring and diagnosis – a maximally invasive data set in a critical care setting although it does occur in practice. Hence, use of this model-based diagnostic would require significant additional invasive sensors for some subjects, which is unacceptable in some, if not all, cases. The main goal of this study is to prove the concept of using only measurements from one side of the heart (right) in a “minimal” data set to identify an effective patient-specific model that can capture key clinical trends in endotoxic shock. This research extends existing methods to a reduced and minimal data set requiring only a single catheter and reducing the risk of infection and other complications – a very common, typical situation in critical care patients, particularly after cardiac surgery. The extended methods and assumptions that found it are developed and presented in a case study for the patient-specific parameter identification of pig-specific parameters in an animal model of induced endotoxic shock. This case study is used to define the impact of this minimal data set on the quality and accuracy of the model-application for monitoring, detecting and diagnosing septic shock. Six anesthetized healthy pigs weighing 20-30 kg received a 0.5- mg/kg endotoxin infusion over a period of 30 mins from T0 to T30. For this research, only right heart measurements were obtained. Errors for the identified model are within 8% when the model is identified from data, re-simulated and then compared to the experimentally measured data, including measurements not used in the identification process for validation. Importantly, all identified parameter trends match physiologically and clinically and experimentally expected changes, indicating that no diagnostic power is lost. This work represents a further with human subjects validation for this model-based approach to cardiovascular diagnosis and therapy guidance in monitoring endotoxic disease states. The results and methods obtained can be readily extended from this case study to the other animal model results presented previously. Overall, these results provide further support for prospective, proof of concept clinical testing with humans.

    Citation
    Chase, J.G., Lambermont, B., Starfinger, C., Hann, C.E., Shaw, G.M., Ghuysen, A., Kolh, P., Dauby, P.C., Desaive, T. (2011) Subject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: Animal experiments and proof of concept. Physiological Measurement, 32(1), pp. 65-82.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    cardiovascular system; cardiac model; parameter identification; integral method; endotoxin; septic shock
    ANZSRC Fields of Research
    32 - Biomedical and clinical sciences::3201 - Cardiovascular medicine and haematology::320101 - Cardiology (incl. cardiovascular diseases)
    09 - Engineering::0903 - Biomedical Engineering
    32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive care
    Rights
    https://hdl.handle.net/10092/17651

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