OUTCOME: Console time ANALYSIS: primary_all_designs STUDIES: 10 TREATMENTS: Conventional, Retzius, Ultra Original data: treat1 treat2 TE seTE Beyatli_2025 Retzius Ultra 19.6000 2.4142 Kowalczyk_Georgetown_series Conventional Ultra 3.3330 2.8598 Lim_2014 Conventional Retzius 24.0000 0.9055 Lin_2025 Conventional Ultra 77.4500 14.7542 Oshima_2023 Conventional Retzius 8.8000 5.4154 Puliatti_2019 Conventional Ultra 7.0000 4.1622 Qian_2024 Conventional Retzius -13.2450 2.8576 Sayyid_2017 Conventional Retzius 21.8880 4.8621 Shimura_2025 Conventional Retzius 17.0000 10.5317 Yilmaz_2023 Conventional Retzius 1.2600 12.1693 Number of treatment arms (by study): narms Beyatli_2025 2 Kowalczyk_Georgetown_series 2 Lim_2014 2 Lin_2025 2 Oshima_2023 2 Puliatti_2019 2 Qian_2024 2 Sayyid_2017 2 Shimura_2025 2 Yilmaz_2023 2 Results (random effects model): treat1 treat2 MD 95%-CI Beyatli_2025 Retzius Ultra 15.4752 [-8.1635; 39.1139] Kowalczyk_Georgetown_series Conventional Ultra 24.7923 [ 3.6642; 45.9205] Lim_2014 Conventional Retzius 9.3171 [-6.5256; 25.1599] Lin_2025 Conventional Ultra 24.7923 [ 3.6642; 45.9205] Oshima_2023 Conventional Retzius 9.3171 [-6.5256; 25.1599] Puliatti_2019 Conventional Ultra 24.7923 [ 3.6642; 45.9205] Qian_2024 Conventional Retzius 9.3171 [-6.5256; 25.1599] Sayyid_2017 Conventional Retzius 9.3171 [-6.5256; 25.1599] Shimura_2025 Conventional Retzius 9.3171 [-6.5256; 25.1599] Yilmaz_2023 Conventional Retzius 9.3171 [-6.5256; 25.1599] Number of studies: k = 10 Number of pairwise comparisons: m = 10 Number of observations: o = 1910 Number of treatments: n = 3 Number of designs: d = 3 Random effects model Treatment estimate (sm = 'MD', comparison: other treatments vs 'Conventional'): MD 95%-CI z p-value Conventional . . . . Retzius -9.3171 [-25.1599; 6.5256] -1.15 0.2491 Ultra -24.7923 [-45.9205; -3.6642] -2.30 0.0215 Quantifying heterogeneity / inconsistency: tau^2 = 397.0035; tau = 19.9249; I^2 = 97.1% [95.9%; 98.0%] Tests of heterogeneity (within designs) and inconsistency (between designs): Q d.f. p-value Total 280.09 8 < 0.0001 Within designs 186.01 7 < 0.0001 Between designs 94.08 1 < 0.0001 Details of network meta-analysis methods: - Frequentist graph-theoretical approach - Restricted maximum-likelihood estimator for tau^2 - Calculation of I^2 based on Q --- P-SCORE RANKING --- P-score Ultra 0.9448 Retzius 0.4876 Conventional 0.0676 --- SUCRA RANKING --- SUCRA Ultra 0.9446 Retzius 0.4902 Conventional 0.0652 - based on 20000 simulations --- GLOBAL INCONSISTENCY: DESIGN-BY-TREATMENT --- Q statistics to assess homogeneity / consistency Q df p-value Total 280.09 8 < 0.0001 Within designs 186.01 7 < 0.0001 Between designs 94.08 1 < 0.0001 Design-specific decomposition of within-designs Q statistic Design Q df p-value Conventional:Retzius 161.65 5 < 0.0001 Conventional:Ultra 24.36 2 < 0.0001 Between-designs Q statistic after detaching of single designs (influential designs have p-value markedly different from < 0.0001) Detached design Q df p-value Conventional:Retzius 0.00 0 -- Conventional:Ultra 0.00 0 -- Retzius:Ultra 0.00 0 -- Q statistic to assess consistency under the assumption of a full design-by-treatment interaction random effects model Q df p-value tau.within tau2.within Between designs 0.07 1 0.7873 19.5168 380.9067 --- LOCAL INCONSISTENCY: NODE SPLITTING/SIDE --- Separate indirect from direct evidence (SIDE) using back-calculation method Random effects model: comparison k prop nma direct indir. Diff z p-value Retzius:Conventional 6 0.88 -9.3171 -10.0751 -3.6190 -6.4561 -0.26 0.7971 Ultra:Conventional 3 0.76 -24.7923 -23.2190 -29.6751 6.4561 0.26 0.7971 Retzius:Ultra 1 0.36 15.4752 19.6000 13.1439 6.4561 0.26 0.7971 Legend: comparison - Treatment comparison k - Number of studies providing direct evidence prop - Direct evidence proportion nma - Estimated treatment effect (MD) in network meta-analysis direct - Estimated treatment effect (MD) derived from direct evidence indir. - Estimated treatment effect (MD) derived from indirect evidence Diff - Difference between direct and indirect treatment estimates z - z-value of test for disagreement (direct versus indirect) p-value - p-value of test for disagreement (direct versus indirect)