Statistics
Data were examined for calculation and distribution for statistical analysis SAS v9.4 (SAS institute, Cary, NC). A power analysis performed prior to the study showed that with a sample size of 44, an alpha level of 0.05 and power ≥ 0.80, we could detect a significant association between the clinical variables with iPFT z-scores when the correlation was as low as 0.41. Statistical significance was defined as p ≤ 0.05. For categorical variables, frequency and percentage analysis were performed. For continuous iPFT variables, mean and 95% confidence intervals were calculated. Chi-square analysis was used to evaluate the proportion of infants in each group with abnormal FRC vs. forced expiratory volume in 0.5 seconds (FEV0.5) parameters. To determine the association between WFA/WFL z-score and lung function, Pearson correlation coefficients were calculated. Associations between lung function and categorical clinical risk factors were calculated using Student’s t-test or Mann-Whitney U test as appropriate. Correlation between FRC and respiratory rate (RR) was determined using Spearman rank-sum correlation coefficients. We conducted additional analyses stratifying infants into normal versus obstruction or hyperinflation. For these analyses, we defined obstruction as an FEV0.5 z-score < -2 and hyperinflation as FRC z-score > 2. To identify the respiratory rate cutoff that yielded the best combination of sensitivity and specificity in predicting hyperinflation, we used logistic regression with Youden’s Index.