Alternate gas washout indices: Assessment of ventilation inhomogeneity in mild to moderate pediatric cystic fibrosis lung disease.

INTRODUCTION: Normalized phase III slope (SnIII ) indices from multiple breath washout (MBW) estimate ventilation inhomogeneity. Alternate (*) protocols for SnIII indices exist, however the utility of these outcomes in children with mild-to-moderate cystic fibrosis (CF) is unknown. METHODS: We measured nitrogen MBW and spirometry in 135 children (43 controls) aged 4-18 years. We assessed validity, practicability, and reliability of SnIII protocols. Outcomes included the ability to detect abnormal lung function, test agreement, measurement duration, intra-test repeatability, and quality. RESULTS: Lung clearance index (LCI) was abnormal in 80 (87%), Scond in 55 (60%), Scond* in 17 (19%), Sacin in 10 (11%), Sacin* in 11 (12%), and FEV1 in 28 (30%). Alternate protocols reduced measurement duration. Agreement of indices to detect abnormal lung function was poor. The quality of analysis and repeatability deteriorated with the alternate technique compared to standard. CONCLUSION: In children with mild-to-moderate CF lung disease, alternate protocols seem practical but clinimetric properties of standard SnIII protocols are preferable.

Feasibility of automated slope III and Scond analysis in children.

BACKGROUND: Multiple breath washout (MBW) derived Scond is an established index of ventilation inhomogeneity. Time-consuming post hoc calculations of the expirogram's slope of alveolar phase III (SIII) and the lack of available software hampered widespread application of Scond. METHODS: Seventy-two school-aged children (45 with cystic fibrosis; CF) performed 3 nitrogen MBW. We tested a new automated algorithm for Scond analysis (Scondauto ) which comprised breath selection for SIII detection, calculation and reporting of test quality. We compared Scondauto to (i) standard Scond analysis (Scondmanual ) with manual breath selection and to (ii) pragmatic Scond analysis including all breaths (Scondall ). Primary outcomes were success rate and agreement between different Scond protocols, and Scond fitting quality (linear regression R(2) ). RESULTS: Average Scondauto (0.06 for CF and 0.01 for controls) was not different from Scondmanual (0.06 for CF and 0.01 for controls) and showed comparable fitting quality (R(2) 0.53 for CF and 0.13 for controls vs. R(2) 0.54 for CF and 0.13 for controls). Scondall was similar in CF and controls but with inferior fitting quality compared to Scondauto and Scondmanual . CONCLUSIONS: Automated Scond calculation is feasible and produces robust results comparable to the standard manual way of Scond calculation. This algorithm provides a valid, fast and objective tool for regular use, even in children.