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.