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A patient-specific airway branching model for mechanically ventilated patients.
Damanhuri, Nor Salwa; Docherty, Paul D; Chiew, Yeong Shiong; van Drunen, Erwin J; Desaive, Thomas; Chase, J Geoffrey.
Afiliação
  • Damanhuri NS; University of Canterbury, Christchurch 8041, New Zealand.
  • Docherty PD; University of Canterbury, Christchurch 8041, New Zealand.
  • Chiew YS; University of Canterbury, Christchurch 8041, New Zealand.
  • van Drunen EJ; University of Canterbury, Christchurch 8041, New Zealand.
  • Desaive T; University of Liège, 4000 Liège, Belgium.
  • Chase JG; University of Canterbury, Christchurch 8041, New Zealand.
Comput Math Methods Med ; 2014: 645732, 2014.
Article em En | MEDLINE | ID: mdl-25214888
ABSTRACT

BACKGROUND:

Respiratory mechanics models have the potential to guide mechanical ventilation. Airway branching models (ABMs) were developed from classical fluid mechanics models but do not provide accurate models of in vivo behaviour. Hence, the ABM was improved to include patient-specific parameters and better model observed behaviour (ABMps).

METHODS:

The airway pressure drop of the ABMps was compared with the well-accepted dynostatic algorithm (DSA) in patients diagnosed with acute respiratory distress syndrome (ARDS). A scaling factor (α) was used to equate the area under the pressure curve (AUC) from the ABMps to the AUC of the DSA and was linked to patient state.

RESULTS:

The ABMps recorded a median α value of 0.58 (IQR 0.54-0.63; range 0.45-0.66) for these ARDS patients. Significantly lower α values were found for individuals with chronic obstructive pulmonary disease (P < 0.001).

CONCLUSION:

The ABMps model allows the estimation of airway pressure drop at each bronchial generation with patient-specific physiological measurements and can be generated from data measured at the bedside. The distribution of patient-specific α values indicates that the overall ABM can be readily improved to better match observed data and capture patient condition.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Respiração Artificial / Síndrome do Desconforto Respiratório / Modelos Teóricos Tipo de estudo: Observational_studies / Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País como assunto: Oceania Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Respiração Artificial / Síndrome do Desconforto Respiratório / Modelos Teóricos Tipo de estudo: Observational_studies / Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País como assunto: Oceania Idioma: En Ano de publicação: 2014 Tipo de documento: Article