Use of the forced-oscillation technique to estimate spirometry values.

ABSTRACT

PURPOSE: Spirometry is sometimes difficult to perform in elderly patients and in those with severe respiratory distress. The forced-oscillation technique (FOT) is a simple and noninvasive method of measuring respiratory impedance. The aim of this study was to determine if FOT data reflect spirometric indices. PATIENTS AND METHODS: Patients underwent both FOT and spirometry procedures prior to inclusion in development (n=1,089) and validation (n=552) studies. Multivariate linear regression analysis was performed to identify FOT parameters predictive of vital capacity (VC), forced VC (FVC), and forced expiratory volume in 1 second (FEV1). A regression equation was used to calculate estimated VC, FVC, and FEV1. We then determined whether the estimated data reflected spirometric indices. Agreement between actual and estimated spirometry data was assessed by Bland-Altman analysis. RESULTS: Significant correlations were observed between actual and estimated VC, FVC, and FEV1 values (all r>0.8 and P<0.001). These results were deemed robust by a separate validation study (all r>0.8 and P<0.001). Bias between the actual data and estimated data for VC, FVC, and FEV1 in the development study was 0.007 L (95% limits of agreement [LOA] 0.907 and -0.893 L), -0.064 L (95% LOA 0.843 and -0.971 L), and -0.039 L (95% LOA 0.735 and -0.814 L), respectively. On the other hand, bias between the actual data and estimated data for VC, FVC, and FEV1 in the validation study was -0.201 L (95% LOA 0.62 and -1.022 L), -0.262 L (95% LOA 0.582 and -1.106 L), and -0.174 L (95% LOA 0.576 and -0.923 L), respectively, suggesting that the estimated data in the validation study did not have high accuracy. CONCLUSION: Further studies are needed to generate more accurate regression equations for spirometric indices based on FOT measurements.