Statistical analysis
Pain
Continuous data are expressed as means ± standard deviations (SD). Two-tailed independent t-tests were performed to compare variables between groups when a normality assumption held according to a Kolmogorov-Smirnov test. Net effect sizes were evaluated using Cohen’s d method, defined as the improvement from baseline after pharmaceutical intervention, subtracted from the improvement after HBOT, divided by the pooled standard deviation of the composite score. Categorical data were expressed in numbers and percentages, compared by chi-square/Fisher’s exact tests. To evaluate HBOT’s effect, a repeated-measure ANOVA mixed-model was used to compare post-treatment and pre-treatment data. The model included time, group and the group-by-time interaction. In questionnaire analysis, a Bonferroni correction was used for multiple comparisons. In SPECT analysis, FDR correction was used for multiple comparisons. A value of p<0.05 was considered significant. Pearson’s correlations were performed between Pain test scores or SPECT activation changes and the change in questionnaire scores before and after treatment. Data analysis was performed using MATLAB R2021b (MathWorks, Natick, MA) Statistics and Machine Learning Toolbox.