A Rapid, Handheld Device to Assess Respiratory Resistance: Clinical and Normative Evidence. Issue 9 (7th February 2018)

• Record Type: Journal Article
• Authors: Holley, Aaron B; Boose, Wesley D; Perkins, Michael; Sheikh, Karen L; Solomon, Nancy P; Dietsch, Angela M; Vossoughi, Jafar; Johnson, Arthur T; Collen, Jacob F
• Is Part Of: Military medicine. Volume 183:Issue 9/10(2018)
• Page Start: e370
• Page End: e377
• Publication Date: 2018-02-07
• Subjects: spirometry -- respiratory resistance -- asthma -- dyspnea -- impulse oscillometry -- occupational lung disease; Surgery, Military -- Societies, etc; Medicine, Military -- Societies, etc; Medicine, Military -- Periodicals; Surgery, Military -- Periodicals; Medicine, Military; Surgery, Military; Military Medicine -- Periodicals; Periodicals; Electronic journals; 616.98023
• DOI: 10.1093/milmed/usx224
• Languages: English
• ISSNs: 0026-4075

Abstract

Abstract: 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/m 2, 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 H2 O/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.