OUTCOME: Urinary continence at 1 month ANALYSIS: primary_all_designs STUDIES: 17 TREATMENTS: Conventional, Retzius, Ultra Original data: treat1 treat2 TE seTE Asimakopoulos_2019 Conventional Retzius -1.6199 0.5238 Beyatli_2025 Retzius Ultra 0.3254 0.3972 Dalela_Detroit_RCT_2015_2016 Conventional Retzius -0.9163 0.4416 Feng_2025 Conventional Retzius -1.6094 0.3598 Ficarra_2022 Conventional Retzius -1.7707 0.4225 Golubtsova_2021 Conventional Retzius -0.3930 0.5725 Kwon_2014 Conventional Ultra -0.9386 0.3614 Lim_2014 Conventional Retzius -1.3964 0.6129 Lin_2025 Conventional Ultra -0.0000 0.7906 Maruyama_2020 Conventional Retzius -0.8752 1.5210 Nagoya_RS_anatomy_OAB Conventional Retzius -2.5390 0.6851 Puliatti_2019 Conventional Ultra -0.2820 0.4570 Qian_2024 Conventional Retzius -0.9653 0.2638 Tahra_2021 Conventional Retzius -1.7185 0.5685 Wang_2021 Conventional Retzius -2.5867 0.5980 Yilmaz_2023 Conventional Retzius -1.3231 0.4002 Zeng_2026 Conventional Retzius -2.3308 0.5021 Number of treatment arms (by study): narms Asimakopoulos_2019 2 Beyatli_2025 2 Dalela_Detroit_RCT_2015_2016 2 Feng_2025 2 Ficarra_2022 2 Golubtsova_2021 2 Kwon_2014 2 Lim_2014 2 Lin_2025 2 Maruyama_2020 2 Nagoya_RS_anatomy_OAB 2 Puliatti_2019 2 Qian_2024 2 Tahra_2021 2 Wang_2021 2 Yilmaz_2023 2 Zeng_2026 2 Results (random effects model): treat1 treat2 OR 95%-CI Asimakopoulos_2019 Conventional Retzius 0.2331 [0.1717; 0.3163] Beyatli_2025 Retzius Ultra 2.0642 [1.1528; 3.6964] Dalela_Detroit_RCT_2015_2016 Conventional Retzius 0.2331 [0.1717; 0.3163] Feng_2025 Conventional Retzius 0.2331 [0.1717; 0.3163] Ficarra_2022 Conventional Retzius 0.2331 [0.1717; 0.3163] Golubtsova_2021 Conventional Retzius 0.2331 [0.1717; 0.3163] Kwon_2014 Conventional Ultra 0.4811 [0.2775; 0.8339] Lim_2014 Conventional Retzius 0.2331 [0.1717; 0.3163] Lin_2025 Conventional Ultra 0.4811 [0.2775; 0.8339] Maruyama_2020 Conventional Retzius 0.2331 [0.1717; 0.3163] Nagoya_RS_anatomy_OAB Conventional Retzius 0.2331 [0.1717; 0.3163] Puliatti_2019 Conventional Ultra 0.4811 [0.2775; 0.8339] Qian_2024 Conventional Retzius 0.2331 [0.1717; 0.3163] Tahra_2021 Conventional Retzius 0.2331 [0.1717; 0.3163] Wang_2021 Conventional Retzius 0.2331 [0.1717; 0.3163] Yilmaz_2023 Conventional Retzius 0.2331 [0.1717; 0.3163] Zeng_2026 Conventional Retzius 0.2331 [0.1717; 0.3163] Number of studies: k = 17 Number of pairwise comparisons: m = 17 Number of observations: o = 2208 Number of treatments: n = 3 Number of designs: d = 3 Random effects model Treatment estimate (sm = 'OR', comparison: other treatments vs 'Conventional'): OR 95%-CI z p-value Conventional . . . . Retzius 4.2909 [3.1614; 5.8239] 9.35 < 0.0001 Ultra 2.0787 [1.1992; 3.6032] 2.61 0.0091 Quantifying heterogeneity / inconsistency: tau^2 = 0.0951; tau = 0.3084; I^2 = 31.2% [0.0%; 62.3%] Tests of heterogeneity (within designs) and inconsistency (between designs): Q d.f. p-value Total 21.79 15 0.1135 Within designs 20.74 14 0.1084 Between designs 1.04 1 0.3068 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 Retzius 0.9963 Ultra 0.5014 Conventional 0.0023 --- SUCRA RANKING --- SUCRA Retzius 0.9963 Ultra 0.5014 Conventional 0.0024 - based on 20000 simulations --- GLOBAL INCONSISTENCY: DESIGN-BY-TREATMENT --- Q statistics to assess homogeneity / consistency Q df p-value Total 21.79 15 0.1135 Within designs 20.74 14 0.1084 Between designs 1.04 1 0.3068 Design-specific decomposition of within-designs Q statistic Design Q df p-value Conventional:Retzius 18.81 12 0.0933 Conventional:Ultra 1.94 2 0.3796 Between-designs Q statistic after detaching of single designs (influential designs have p-value markedly different from 0.3068) 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 0.95 1 0.3302 0.3302 0.1091 --- LOCAL INCONSISTENCY: NODE SPLITTING/SIDE --- Separate indirect from direct evidence (SIDE) using back-calculation method Random effects model: comparison k prop nma direct indir. RoR z p-value Retzius:Conventional 13 0.93 4.2909 4.4710 2.4200 1.8475 0.98 0.3248 Ultra:Conventional 3 0.72 2.0787 1.7478 3.2290 0.5413 -0.98 0.3248 Retzius:Ultra 1 0.35 2.0642 1.3846 2.5580 0.5413 -0.98 0.3248 Legend: comparison - Treatment comparison k - Number of studies providing direct evidence prop - Direct evidence proportion nma - Estimated treatment effect (OR) in network meta-analysis direct - Estimated treatment effect (OR) derived from direct evidence indir. - Estimated treatment effect (OR) derived from indirect evidence RoR - Ratio of Ratios (direct versus indirect) z - z-value of test for disagreement (direct versus indirect) p-value - p-value of test for disagreement (direct versus indirect)