Paper Info
Title
A Patient-Specific Airway Branching Model for Mechanically Ventilated Patients.
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 (alpha) 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.. value of 0.58 (IQR: 0.54-0.63; range: 0.45-0.66) for these ARDS patients. Significantly lower.. 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.. values indicates that the overall ABM can be readily improved to better match observed data and capture patient condition.
Year
DOI
Venue
2014
10.1155/2014/645732
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Field
DocType
Volume
Mechanical ventilation,Artificial intelligence,Surgery,Airway,Medicine,Patient state,Branching (version control),ARDS,Internal medicine,Cardiology,Pressure drop,Acute respiratory distress,Respiratory physiology,Machine learning
Journal
2014
ISSN
Citations 
PageRank 
1748-670X
1
0.37
References 
Authors
1
6
Name
Order
Citations
PageRank
Nor Salwa Damanhuri110.71
Paul Docherty23210.28
Yeong Shiong Chiew3126.19
Erwin J. van Drunen410.37
Thomas Desaive53414.02
J. Geoffrey Chase637591.29