Analysis of forced expired volume signals using multi-exponential functions
- 85 Downloads
- 4 Citations
Abstract
Patients with pulmonary disease are often unable to complete forced expiration manœuvres. The aim of the study is to evaluate whether forced vital capacity (FVC), the volume exhaled at the end of completed forced expiration, can be estimated by extrapolating volume-time curves obtained from uncompleted manœuvres. The suitability of mono-, bi-, and tri-exponential functions to characterise complete volume-time curves from 50 subjects is investigated. Mono-exponential modelling is insufficient, whereas bi-exponential fitting yields an adequate description for 47 data sets. Tri-exponential models lead to overfitting in all but three cases (normalised sum of least squares: 50.2±34.5 for mono-2.76±4.11 for bi-, 2.74±4.19 for tri-exponential modelling; condition number of the correlation matrix: 1.0025±0.0004 for mono-, 1.08±0.08 for bi-, 34.7±100.1 for tri-exponential fitting (mean±SD)). Thus, FVC is estimated by the extrapolation of 27 uncompleted spirograms using bi- or tri-exponential models, depending on their accordance with measured data and on the identifiability of their parameters. This algorithm yields unbiased estimates (difference from measured inspiratory vital capacity: 0.01±0.21 L). This method can be used for investigation of the lung function of subjects who cannot complete the forced expiration manœuvre.
Keywords
Lung function measurement Spirometry Forced expiration manœuvre Model selection Prediction of forced vital capacityPreview
Unable to display preview. Download preview PDF.
References
- American Thoracic Society (1995): ‘Standardization of spirometry’,Am. J. Respir. Crit. Care Med.,152, pp. 1107–1136Google Scholar
- Chelucci, G. L., Brunet, F., Dall'Ava-Santucci, J., Dhainaut, J. F., Paccaly, D., Armaganidis, A., Milic-Emili, J., andLockhart, A. (1991): ‘A single-compartment model cannot describe passive expiration in intubated, paralysed humans’,Eur. Respir. J.,4, pp. 458–464Google Scholar
- Chelucci, G. L., Dall'Ava-Santucci, J., Dhainaut, J. F., Chelucci, A., Allegra, A., Paccaly, D., Brunet, F., Milic-Emili, J., andLockhart, A. (1993): ‘Mocelling of passive expiration in patients with adult respiratory distress syndrome’,Eur. Respir. J.,6, pp. 785–790.Google Scholar
- Chhabra, S. K. (1998): ‘Forced vital capacity, slow vital capacity, or inspiratory vital capacity: which is the best measure of vital capacity?’,J. Asthma.,35, pp. 361–365Google Scholar
- Guttmann, J., Eberhard, L., Fabry, B., Bertschmann, W., Zeravik, J., Adolph, M., Eckart, J., andWolff, G. (1995): ‘Time constant/volume relationship of passive expiration in mechanically ventilated ARDS patients’,Eur. Respir. J.,8, pp. 114–120CrossRefGoogle Scholar
- Hedman, J., Kaprio, J., Poussa, T., andNieminen, M. M. (1999): ‘Prevalence of asthma, aspirin intolerance, nasal polyposis and chronic obstructive pulmonary disease in a population-based study’,Int. J. Epidemiol.,28, pp. 717–722.CrossRefGoogle Scholar
- Permutt, S., andMenkes, H. A. (1979): ‘Spirometry: analysis of the forced expiration within the time domain’ inMacklem, P., andPermutt, S. (Eds): ‘The lung in transition from health to disease’, Vol. 12, Lung biology in health and disease (Marcel Dekker, New York), pp. 113–152.Google Scholar
- Pimmel, R. L., Miller III, T. K., Fouke, J. M., and Eyles, J. G. (1981): ‘Time-constant histograms from the forced expired volume signal’,J. Appl. Physiol.,51, pp. 1581–1593Google Scholar
- Press, W. H., Teukolsky, S. A., Vetterling, W. T., andFlannery, B. P. (1992); ‘Numerical recipes in C’ (Cambridge University Press, Cambridge)Google Scholar
- Revelly, J. P., Feihl, F., Liebling, T., andPerret, C. (1989): ‘Time constant histograms from the forced expired volume signal: a clinical evaluation’,Eur. Respir. J.,2, pp. 536–542Google Scholar
- Rotger, M., Navajas, D., andFarré, R. (1989): ‘A least squares algorithm to determine the mechanical time constant distribution of the lung during forced expiration’,Int. J. Biomed. Comput.,24, pp. 29–40CrossRefGoogle Scholar