Additional file 1 of Prevention of cytomegalovirus infection after solid organ transplantation: a Bayesian network analysis
Creators: name: Zhang, Yu
name: Zhou, Tao
name: Huang, Mingzhu
name: Gu, Guangxiang
name: Xia, Qiang
Publisher: name: figshare
Year: 2020
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences

description: Additional file 1: Figure S1. Network plot of different outcome and subgroup analysis. Different nodes represent different treatments and the size of the nodes corresponds to the number of patients. The line represents a direct comparison between the two treatments and the thickness of the line is consistent with the number of direct comparisons of the two treatments. Figure S2. The results of Bayesian network meta-analysis. We should read result from right to left. Each result is a comparison between the column-defining treatment and the row-defining treatment. We highlight the data with significant statistical difference (p &lt; 0.05) by *. (Abbreviations: CI, confidence interval; CMV, Cytomegalovirus.). Figure S3. Direct pairwise comparisons of CMV infection. There are five direct pairwise comparisons of antiviral drugs among the included studies. The heterogeneity was assessed by I2 statistic (low-degree:25-49%; moderate-degree:50–75%; highdegree: &gt; 75%). There is a high-degree heterogeneity between the comparison between valganciclovir and valacyclovir. Figure S4. Direct pairwise comparisons of CMV disease. There are five direct pairwise comparisons of antiviral drugs among the included studies. The heterogeneity was assessed by I2 statistic (low-degree:25-49%; moderate-degree:50–75%; highdegree: &gt; 75%). There is only a moderate-degree heterogeneity between the comparison between acyclovir and ganciclovir. Figure S5. Direct pairwise comparisons of acute rejection and leukopenia. There are two direct pairwise comparisons respectively among acute rejection and leukopenia. The heterogeneity was assessed by I2 statistic (low-degree:25-49%; moderate-degree:50–75%; high-degree: &gt; 75%). About acute rejection, There is a low-degree heterogeneity between the comparison between ganciclovir and valacyclovir and a high-degree heterogeneity between the comparison between valganciclovir and valacyclovir. As for leukopenia, There is only a low-degree heterogeneity between the comparison between acyclovir and ganciclovir. Figure S6. Inconsistency analysis of different outcome and subgroup analysis in the network. The ROR value of all result is close to one, indicating that the inconsistency is weak. (Abbreviations: AV, acyclovir; GV, ganciclovir; VAV, valacyclovir; VGV, valganciclovir; CN, control.) Figure S7. Node-splitting analyses of different outcome and subgroup analysis in the network. All of the results compared direct and indirect evidence between different antiviral drugs did not show significant statistical differences (significant difference with p-values &lt; 0.05). Figure S8. Rank possibility of different outcome and subgroup analysis. The figure shows the probability of each Intervention being best, second best, third best, and so on. Rank 5 is the best because the less likely the occurrence of CMV infection and disease with the corresponding interventions. Figure S9. Comparison-adjusted funnel plot of different outcome and subgroup analysis in the network. The red line suggests the null hypothesis that the study-specifc effect sizes do not differ from the respective comparison-specifc pooled effect estimates. The blue line is the regression line. Different colors represent different comparisons. The funnel plot should be symmetrical near the zero line if there is no publication bias (Abbreviations: AV, acyclovir; GV, ganciclovir; VAV, valacyclovir; VGV, valganciclovir; CN, control.).