Based on the study by Dargaville et al. we estimated that NIV failure would occur in 22% of infants at risk of RDS (9 (link)). A sample size of 159 subjects provided an estimate of incidence with a 95% confidence interval (95%CI) with ±7% precision, accounting for 15% invalid data.
Descriptive analysis was performed by calculating frequencies and percentages for categorical variables. The central tendency (mean and median) and dispersion [standard deviation and interquartile range (IQR)] were calculated for quantitative variables. The independent sample t-test was used to compare continuous variables, and the χ2 test or Fisher's exact test was used to compare categorical variables. All analyses are presented for the entire cohort and gestational age.
Multiple logistic regression was used to identify potential predictors of NIV success or failure by calculating odds ratios (OR) with 95% confidence intervals (CI). The variables selected for the multivariate analysis were those corresponding to p-values less than 0.1 in the univariate analysis. Statistical significance was set at p < 0.05; analyses were performed using the available data without imputation of the missing data. Statistical analyses were performed using the SAS software (version 9.3, SAS Institute Inc., Cary, NC, United States).
Descriptive analysis was performed by calculating frequencies and percentages for categorical variables. The central tendency (mean and median) and dispersion [standard deviation and interquartile range (IQR)] were calculated for quantitative variables. The independent sample t-test was used to compare continuous variables, and the χ2 test or Fisher's exact test was used to compare categorical variables. All analyses are presented for the entire cohort and gestational age.
Multiple logistic regression was used to identify potential predictors of NIV success or failure by calculating odds ratios (OR) with 95% confidence intervals (CI). The variables selected for the multivariate analysis were those corresponding to p-values less than 0.1 in the univariate analysis. Statistical significance was set at p < 0.05; analyses were performed using the available data without imputation of the missing data. Statistical analyses were performed using the SAS software (version 9.3, SAS Institute Inc., Cary, NC, United States).
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