Spss software 25

Data are presented as median values and interquartile ranges (IQRs) for continuous variables and frequencies and percentages for categorical variables. Continuous-variable comparisons between the groups were performed using the Mann-Whitney U test. Categorical variables were compared using the Fisher exact test. Pearson correlation coefficients were examined to assess whether the prevalence of COVID-19 was associated with the prevalence of M. pneumoniae. Statistical significance was determined as a 2-sided P value of <0.05. Statistical analyses were performed using SPSS software 25.0 (IBM SPSS Statistics, Armonk, NY, USA).

The chi‒square test or Fisher’s exact test was used in the comparisons of categorical variables. The Shapiro‒Wilk test was used to test the data distribution. Normally distributed continuous variables are described by the mean ± standard deviation (SD), and nonnormally distributed continuous variables are described by the median (interquartile range, IQR). Student’s t test or Mann‒Whitney U test was used in the comparisons of continuous variables between 2 groups, whereas the one-way analysis of variance test or Kruskal‒Wallis test was used in the comparisons of continuous variables among 3 groups, if appropriate.
After the univariable analysis, age, sex and clinical factors with a p value < 0.1 were included in the multivariable modified Poisson regression analysis^{30 (link)} to determine the relationships of craniocervical AS number and poststroke inflammatory markers with 90-day poor functional outcome. Subsequently, all participants were categorized into 3 groups based on the tertiles of the craniocervical AS number. Multivariable ordinal logistic regression analysis was used to determine the relationship of the poststroke inflammatory markers with the craniocervical AS number. All statistical analyses were performed by using SPSS software 25.0 (IBM, Armonk, NY, United States). All tests were two-sided, and a p value < 0.05 was considered statistically significant.

Statistical analyses were conducted using IBM SPSS software 25.0 and R software 4.0.2. We turned all continuous variables into classified variables according to the optimal cut-off value of the Receiver Operating Curve (ROC). Using the Chi-square test or Fish’s exact test, the difference between the classified data was evaluated. OS and PFS were plotted using the Kaplan–Meier curves and compared using the log-rank test. The univariate and multivariate Cox analyses were performed to evaluate the association between pre-treatment nutrition-related indicators and prognosis in older patients with locally advanced ESCC. In univariate analyses, all variables with a p value < 0.10 were incorporated into multivariate analyses. Using the time-dependent ROC (time-ROC) and C-index, the predictive ability of each independently nutrition-related prognostic indicator was evaluated. In addition, the relationship between nutrition-related indicators and survival outcomes was assessed using the Restricted Cubic Splines (RCS). To understand the application of the same prognostic indicators in different subgroups, we performed a subgroup analysis of age, sex, radiation dose, chemotherapy, tumor location, tumor length, T stage, N stage, tumor stage, and PNI. Statistically, a p value < 0.05 was considered significant.