Spss statistics for windows macintosh version 25

The G*power software (G*power 3.1, University of Düsseldorf, Düsseldorf, Germany) was used for sample size calculation. The conditions were as follows; Wilcoxon signed-rank test (one sample case), effect size d = 0.5; α error prob = 0.05; Power (1-β error probability) = 0.90. Data were analyzed using IBM SPSS Statistics for Windows/Macintosh, version 25.0 (IBM Corp., Armonk, NY, USA), and continuous variables were recorded as mean and standard deviation. As a result of performing the normality test with Kolmogorov–Smirnov and Shapiro–Wilk, the main analysis variables did not show a normal distribution; therefore, a nonparametric analysis was performed. The Wilcoxon method was used to perform intra-group of pre- and post-comparison. For comparison between groups, the Mann–Whitney method was used. The significance level was set at p < 0.05.

The sample size was calculated on the basis of the findings of a previous study by Aho et al. [11 (link)] The mean difference (standard deviation [SD]) in serum norepinephrine levels between the baseline and the highest level during surgery between patients who received intramuscular dexmedetomidine and those who received 0.9% saline was 2.2 (1.5) mcg/dL. We expected that, compared to the controls, patients receiving intravenous dexmedetomidine would show a reduction in serum norepinephrine level by at least 50% [12 (link)]. We calculated that 21 patients per group were required to detect this degree of difference with a power of 80% and an α = 0.05. Considering a 10% dropout rate, we decided to enroll 46 patients in total.
After determining the normality of data distribution by using the Shapiro-Wilk test, continuous variables were analyzed using the t test or Mann-Whitney U test as appropriate. Parametric and non-parametric data were reported as mean ± SDs and median [interquartile ranges], respectively. Categorical variables were analyzed using the chi-square test or Fisher’s exact test. Bonferroni correction was used for multiple comparisons. Data analysis was conducted using IBM SPSS Statistics for Windows/Macintosh, Version 25.0 (IBM Corp., Armonk, NY, USA). For all analyses, a P-value < 0.05 was considered significant, and two-sided tests were used.

Results are presented as medians with interquartile ranges (IQRs) or numbers with percentages wherever appropriate. The Mann–Whitney U test was used to compare non-normally distributed continuous variables. The Pearson χ² test or Fisher’s exact test was used to compare categorical variables. Variables exhibiting significant differences between groups were entered into univariate and multivariate logistic regression analyses to determine factors independently predicting nosocomial bacterial pneumonia. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression models. We used multivariate logistic regression models to evaluate ORs, and the forward selection method was employed to assess the associated factors with a p value of <0.1 from univariate analyses. A p value of <0.05 was considered statistically significant. ICU admission proportion, MV dependence, and the duration of SARS-CoV-2 shedding were evaluated using a Kaplan–Meier curve and the log-rank test. Two-sided tests were used and considered statistically significant for p values less than 0.05. All statistical analyses were performed using IBM SPSS Statistics for Windows/Macintosh, Version 25.0 (IBM Corp., Armonk, NY, USA).