In:
Computational and Mathematical Methods in Medicine, Hindawi Limited, Vol. 2014 ( 2014), p. 1-10
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.
Type of Medium:
Online Resource
ISSN:
1748-670X
,
1748-6718
Language:
English
Publisher:
Hindawi Limited
Publication Date:
2014
detail.hit.zdb_id:
2256917-0
