A Rapid, Handheld Device to Assess Respiratory Resistance: Clinical and Normative Evidence.

INTRODUCTION

Following reports of respiratory symptoms among service members returning from deployment to South West Asia (SWA), an expert panel recommended pre-deployment spirometry be used to assess disease burden. Unfortunately, testing with spirometry is high cost and time-consuming. The airflow perturbation device (APD) is a handheld monitor that rapidly measures respiratory resistance (APD-Rr) and has promising but limited clinical data. Its speed and portability make it ideally suited for large volume pre-deployment screening. We conducted a pilot study to assess APD performance characteristics and develop normative values.

MATERIALS AND METHODS

We prospectively enrolled subjects and derived reference equations for the APD from those without respiratory symptoms, pulmonary disease, or tobacco exposure. APD testing was conducted by medical technicians who received a 10-min in-service on its use. A subset of subjects performed spirometry and impulse oscillometry (iOS), administered by trained respiratory therapists. APD measures were compared with spirometry and iOS.

RESULTS

The total study population included 199 subjects (55.8% males, body mass index 27.7 ± 6.0 kg/m2, age 49.9 ± 18.7 yr). Across the three APD trials, mean inspiratory (APD-Ri), expiratory (APD-Re), and average (APD-Ravg) resistances were 3.30 ± 1.0, 3.69 ± 1.2, and 3.50 ± 1.1 cm H2O/L/s. Reference equations were derived from 142 clinically normal volunteers. Height, weight, and body mass index were independently associated with APD-Ri, APD-Re, and APD-Ravg and were combined with age and gender in linear regression models. APD-Ri, APD-Re, and APD-Ravg were significantly inversely correlated with FEV1 (r = -0.39 to -0.42), FVC (r = -0.37 to -0.40), and FEF25-75 (r = -0.31 to -0.35) and positively correlated with R5 (r = 0.61-0.62), R20 (r = 0.50-0.52), X5 (r = -0.57 to -0.59), and FRES (r = 0.42-0.43). Bland-Altman plots showed that the APD-Rr closely approximates iOS when resistance is normal.

CONCLUSION

Rapid testing was achieved with minimal training required, and reference equations were constructed. APD-Rr correlated moderately with iOS and weakly with spirometry. More testing is required to determine whether the APD has value for pre- and post-deployment respiratory assessment.