Spss program version 13

Statistical Product and Service Solutions (SPSS) program Version 13.0 was used for statistical analysis (SPSS Inc., Chicago, IL, USA). The Kolmogorov–Smirnov test was used to determine the normality of the data distribution. Continuous variables were reported as mean, standard deviation (SD), or median with IQR based on the data distribution. For comparisons between two distinct groups or between two or more groups, normally distributed data were compared using Student’s t-test or one-way analysis of variance (ANOVA). Otherwise, the Kruskal–Wallis H test or Mann–Whitney U test was used.
The chi-square test was used to determine whether the genotype distribution of healthy controls supported the Hardy–Weinberg equilibrium (HWE). The genotype distribution and frequency of mutant alleles in patients and healthy controls were compared using chi-square or Fisher’s exact test. To examine the potential relationship between genetic polymorphisms and the risk of developing PTOM according to four genetic models (dominant, recessive, homozygous, and heterozygous models), binomial logistic regression analysis with sex, age, and genotype distribution as covariates was used (CI). All reported p-values were two-sided, and statistical significance was set at p < 0.05.

Pain will be the primary outcome and will be determined using a VAS and algometer. EMG will be the secondary outcome. The independent variables will be the different light sources used for phototherapy. The dependent variables will be derived from the pre-treatment and post-treatment evaluations. Intra-group comparisons will be performed using repeated-measures analysis of variance (ANOVA or Friedman’s test), followed by either the Student’s t-test or Wilcoxon’s test. Inter-group comparisons will be performed using either one-way ANOVA or the Kruskal-Wallis test. The choice of tests will be determined by the distribution (normal or non-normal) of the data. The level of significance will be set to 5% (P <0.05). All comparisons and statistical analyses will be performed using the SPSS program, version 13.0 (Chicago, IL, USA). Cohen’s d will be employed to determine the clinical effect size of the proposed therapies, with the interpretation of the coefficients based on the classification established by Cohen [23 ]: 0.2 = small effect; ≥0.5 = moderate effect; ≥0.8 = large effect.

The data were analyzed using a Student’s t-test and one-way analysis of variance (ANOVA), followed by a Tukey post hoc comparison test (SPSS program version 13.0; SPSS Inc., Chicago, IL, USA). Differences of at least p ≤ 0.05 were considered significant. Iron concentration underwent statistical analysis in R computational language. In each group, data were considered as probable outliers when they exceeded by 1.5 times the 0.25–0.75 percentile range. Metabolomics data were analyzed in R, with sparse principal component analysis (sPCA) performed using a mixOmics package, applying the sparsity principle as detailed by Shen and Huang [35 (link)].