Model-based prediction of expiratory resistance index in patients with asthma.
OBJECTIVE
Develop a sensitive algorithm and index for detection of asthma patients using forced expiratory flow curves.


METHODS
A lumped-parameter model of forced expiration was developed. The model can predict the flow-volume curve during forced expiratory maneuver. The flow-volume curves generated by the model depend on values of resistance parameters (FER). Use of flow-volume curves recorded from normal subjects and from patients with asthma before and after ventolin inhalation as inputs for the inverse model, yielded the resistance parameters for each case. These parameters are based on the entire information presented in the flow-volume curve and on the reduction in flow at all lung volumes.


RESULTS
Forced Expiratory Resistance (FER(N)) indices were estimated at different percent of lung volumes using the inverse model. The index was significantly affected by inhalation of ventolin in asthmatic patients and was insensitive to ventolin inhalation in normal patients. In asthmatic patients, the FER index at five lung volumes (out of eight), was two--five times greater than in normal subjects with p < 0.05 (three of them with p < 0.01).


CONCLUSIONS
The estimated parameters were sensitive indicators of the degree of lung function impairment and were able to accurately distinguish between healthy and asthmatic patients.
Barnea
Ofer
O
Biomedical Engineering Department, Faculty of Engineering, Tel Aviv University, Israel. barneao@eng.tau.ac.il
Abboud
Shimon
S
Guber
Alexander
A
Bruderman
Israel
I
D000465:Algorithms; D001249:Asthma / Q000175:diagnosis*; D005540:Forced Expiratory Flow Rates; D005544:Forecasting; D006801:Humans; D008962:Models, Theoretical