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Incorporating pulse wave velocity into model-based pulse contour analysis method for estimation of cardiac stroke volume.
Smith, Rachel; Balmer, Joel; Pretty, Christopher G; Mehta-Wilson, Tashana; Desaive, Thomas; Shaw, Geoffrey M; Chase, J Geoffrey.
Afiliação
  • Smith R; Department of Mechanical Engineering, University of Canterbury, New Zealand. Electronic address: rachel.smith@pg.canterbury.ac.nz.
  • Balmer J; Department of Mechanical Engineering, University of Canterbury, New Zealand.
  • Pretty CG; Department of Mechanical Engineering, University of Canterbury, New Zealand.
  • Mehta-Wilson T; Department of Mechanical Engineering, University of Canterbury, New Zealand.
  • Desaive T; IGA Cardiovascular Science, University of Liége, Liége, Belgium.
  • Shaw GM; Christchurch Hospital Intensive Care Unit New Zealand.
  • Chase JG; Department of Mechanical Engineering, University of Canterbury, New Zealand.
Comput Methods Programs Biomed ; 195: 105553, 2020 Oct.
Article em En | MEDLINE | ID: mdl-32497771
BACKGROUND AND OBJECTIVES: Stroke volume (SV) and cardiac output (CO) are important metrics for hemodynamic management of critically ill patients. Clinically available devices to continuously monitor these metrics are invasive, and less invasive methods perform poorly during hemodynamic instability. Pulse wave velocity (PWV) could potentially improve estimation of SV and CO by providing information on changing vascular tone. This study investigates whether using PWV for parameter identification of a model-based pulse contour analysis method improves SV estimation accuracy. METHODS: Three implementations of a 3-element windkessel pulse contour analysis model are compared: constant-Z, water hammer, and Bramwell-Hill methods. Each implementation identifies the characteristic impedance parameter (Z) differently. The first method identifies Z statically and does not use PWV, and the latter two methods use PWV to dynamically update Z. Accuracy of SV estimation is tested in an animal trial, where interventions induce severe hemodynamic changes in 5 pigs. Model-predicted SV is compared to SV measured using an aortic flow probe. RESULTS: SV percentage error had median bias and [(IQR); (2.5th, 97.5th percentiles)] of -0.5% [(-6.1%, 4.7%); (-50.3%, +24.1%)] for the constant-Z method, 0.6% [(-4.9%, 6.2%); (-43.4%, +29.3%)] for the water hammer method, and 0.8% [(-6.5, 8.6); (-37.1%, +47.6%)] for the Bramwell-Hill method. CONCLUSION: Incorporating PWV for dynamic Z parameter identification through either the Bramwell-Hill equation or the water hammer equation does not appreciably improve the 3-element windkessel pulse contour analysis model's prediction of SV during hemodynamic changes compared to the constant-Z method.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Onda de Pulso / Hemodinâmica Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Onda de Pulso / Hemodinâmica Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article