Spss statistical software version 22 for windows

Measurement data were expressed as means and standard deviations ( $\overline{x}\pm s$ ). The differences between groups were compared using a t-test if the data satisfied the normal distribution and homogeneity test of variance requirements. Wilcoxon rank sum test was utilized if the data did not satisfy the normal distribution or homogeneity test of variance requirements. Count data were expressed using frequency (percentage), and the differences between the groups were compared by the Pearson’s χ² test. Spearman’s rank analysis was carried out to identify the association between Pg and systemic inflammatory factors. The differences in inflammatory parameters of different infection forms of Pg in AMI patients were compared with a one-way analysis of variance. Multivariate logistic regression analysis was performed to evaluate the relationship among the different infection forms of Pg, AMI, and severity of coronary artery lesions. SPSS statistical software for Windows, version 22.0 (SPSS, Chicago, IL, USA) was employed to sort and analyze the data. All statistical tests were bilateral, with p < 0.05 considered to indicate statistical significance.

All experiments were repeated at least three times, and the results are expressed as the mean ± SD using SPSS statistical software for Windows, version 22.0 (SPSS, Chicago, IL, USA). Comparisons of two independent groups were determined using the chi-square test and two-tailed Student’s t-test. The statistical significance among three or more groups was evaluated by one-way analysis of variance. Pearson’s correlation analysis was used to detect the correlation between the two groups. Kaplan-Meier analysis and the log-rank test were conducted to analyze the survival rates of each group. Two-tailed P values < 0.05 were considered significant.

Statistical analyses were performed using SPSS statistical software for Windows version 22.0 (SPSS Inc.). Here, survival was defined as overall survival time from the time of diagnosis. Survival curves related to TP53 and ATRX expression were generated using the Kaplan–Meier method, and median survival times with 95% confidence intervals were given. Comparison of survival curves between normal and aberrant expression was performed using the log-rank test. P-value <0.05 was considered statistically significant. Association between TP53 and ATRX expression statuses was evaluated using cross tabulation and Fisher’s exact test.

The Kolmogorov-Smirnov test was used to test the normality of continuous variables. The variables with normality are shown as the mean ± SD; whereas the skewed distributed variables are presented as the median and interquartile ranges. The data with non-normality were log-transformed into a normal distribution. Differences of values among multiple groups were analyzed using chi-square tests for categorical variables, Student’s t tests, and one-way analysis of variance for continuous variables. Bonferroni corrections were performed to correct for multiple comparisons. Pearson’s correlations and partial correlations were conducted to examine the relationship between variables. A multiple stepwise linear regression analysis was performed with the BDNF as the dependent variable. Variables with a significant association with BDNF were imputed as independent. Based on a recent meta-analysis of peripheral BDNF in BD, the duration of illness, symptom severity (CGI-BP-S scores), and age were added as adjustment variables (3 (link)). All the data were analyzed using SPSS statistical software for Windows, version 22.0 (SPSS, Chicago, IL, USA). Two-side tests and adjusted p < 0.05 were considered significant.

All statistical analyses were performed using SPSS statistical software for Windows version 22.0 (SPSS, Chicago, IL, USA). For statistical analyses, BCVA values were transformed into the logarithm of the minimum angle of resolution (LogMAR) values. The independent t-test and chi-square test were used to compare clinical factors, and compare ocular parameters between fellow eyes of RVO patients and normal controls.
Linear mixed models were used to calculate and compare the reduction rates of pRNFL thicknesses over time between fellow eyes of RVO patients and normal controls. The pRNFL thickness was fitted with linear mixed models using age, sex, BCVA, IOP, AL, SE, baseline average pRNFL thickness, HTN, DM, and the interactions between the group and follow-up durations as fixed effects. A random intercept was included at eye levels. Univariate and multivariate generalized linear mixed models were used to determine the factors associated with longitudinal changes in pRNFL thicknesses.

The data were analyzed by using SPSS statistical software for Windows, version 22.0 (SPSS, Chicago, IL, USA). The results are presented with mean (standard deviation) unless otherwise mentioned. The comparisons between the two groups were performed with Mann-Whitney U-test and with Fisher's exact test. Adult or near adult heights were compared with PAHs at the beginning of the study (1 (link)) and at the post-treatment visit (9 (link), 15 (link)) and with target heights by using Wilcoxon signed-rank test. Spearman rank correlations were calculated. Number needed to harm (NNH) with Lz-treatment was calculated for the risk of vertebral deformity. Statistically significant level was set to p < 0.05.

All statistical analyses were performed using SPSS statistical software for Windows, version 22.0 (SPSS, Chicago, IL, USA). For statistical analyses, BCVA values were transformed to the logarithm of the minimum angle of resolution (log MAR) values. One-way analysis of variance with Bonferroni correction and the chi-squared test were used to compare clinical factors, OCT parameters, and OCTA parameters among groups. Ordered differences among groups were analyzed by the Jonckheere–Terpstra (J-T) test for trends. Pearson’s correlation was used to investigate the associations between clinical, peripapillary OCTA parameters and pRNFL thicknesses. Univariate and multivariate regression analyses were also performed to identify factors significantly related to peripapillary VD and PD in SCP. A value of p < 0.05 was considered statistically significant.