Repeatability of lung clearance index in infants with cystic fibrosis and recurrent wheeze

Abstract

Objectives: To describe the short-and medium-term repeatability of lung clearance index at 2.5% (LCI 2.5 ) in infants and calculate the number of patients needed to enroll in a study (N) using LCI 2.5 as a primary outcome.Methods: An 8-month follow-up observational study was employed for assessing short-term [coefficient of repeatability (CR) and intraclass correlation (ICC)] and medium-term repeatability (Bland-Altman method) of LCI 2.5 in infants with cystic fibrosis (CF) or recurrent wheeze (RW) measured by the nitrogen multiple-breath washout test (N 2 -MBW). Using these variability data, the N to reach 90% test power at the level of statistical significance (0.05) was calculated.Results: Forty infants with CF and 21 with RW were enrolled. Initial N 2 -MBW testing was successful in 33 and 17 patients, respectively. Follow-up data were available for 23 and 11 infants, respectively. Short-term repeatability of LCI 2.5 was high (CR = 1.10 and 1.04 in CF and RW patients, respectively; ICC = 0.88 and 0.83 in CF and RW patients, respectively). The between-subject standard deviation was <13% of the actual LCI 2.5 value. In clinically stable patients, LCI 2.5 did not significantly change during the 8-month follow-up. Mean LCI 2.5 change was −0.08 (1% of baseline) in CF and −0.05 (0.6%) in RW, with 95% limits of agreement being 1.40) in RW patients. N = 23 infants if both intragroup differences of LCI 2.5 and minimal difference to be detected would be 2.0. Conclusion:N 2 -MBW may be a reproducible tool with reasonable test power to detect differences in infant studies.

Pediatric pulmonology year in review 2021 and 2022: Physiology

“…To be able to utilize N 2 ‐MBW as a tool to monitor lung disease, data on the variability of this measurement are needed. Koucky et al 9 performed serial N 2 ‐MBW in a cohort of infants with CF and recurrent wheezing and established short‐term and medium‐term variability of in LCI. These data will be helpful in planning future studies.…”