OUTCOME: Urinary continence at 2 weeks 
ANALYSIS: primary_all_designs 
STUDIES: 4 
TREATMENTS: Conventional, Retzius, Ultra 

Original data:

                    treat1  treat2      TE   seTE
Kwon_2014     Conventional   Ultra -0.1409 0.3756
Lambert_2023  Conventional Retzius -2.4120 0.3469
Maruyama_2020 Conventional Retzius -0.8913 1.5214
Yee_2021      Conventional Retzius  1.0544 0.6079

Number of treatment arms (by study):
              narms
Kwon_2014         2
Lambert_2023      2
Maruyama_2020     2
Yee_2021          2

Results (random effects model):

                    treat1  treat2     OR            95%-CI
Kwon_2014     Conventional   Ultra 0.8686 [0.0235; 32.1219]
Lambert_2023  Conventional Retzius 0.4600 [0.0480;  4.4072]
Maruyama_2020 Conventional Retzius 0.4600 [0.0480;  4.4072]
Yee_2021      Conventional Retzius 0.4600 [0.0480;  4.4072]

Number of studies: k = 4
Number of pairwise comparisons: m = 4
Number of observations: o = 568
Number of treatments: n = 3
Number of designs: d = 2

Random effects model

Treatment estimate (sm = 'OR', comparison: other treatments vs 'Conventional'):
                 OR            95%-CI    z p-value
Conventional      .                 .    .       .
Retzius      2.1740 [0.2269; 20.8287] 0.67  0.5006
Ultra        1.1513 [0.0311; 42.5785] 0.08  0.9390

Quantifying heterogeneity / inconsistency:
tau^2 = 3.2522; tau = 1.8034; I^2 = 91.9% [79.5%; 96.8%]

Tests of heterogeneity (within designs) and inconsistency (between designs):
                    Q d.f.  p-value
Total           24.71    2 < 0.0001
Within designs  24.71    2 < 0.0001
Between designs  0.00    0       --

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       0.6824
Ultra         0.4577
Conventional  0.3599

--- SUCRA RANKING ---
              SUCRA
Retzius      0.6815
Ultra        0.4580
Conventional 0.3604

- based on 20000 simulations

--- GLOBAL INCONSISTENCY: DESIGN-BY-TREATMENT ---
Q statistics to assess homogeneity / consistency

                    Q df  p-value
Total           24.71  2 < 0.0001
Within designs  24.71  2 < 0.0001
Between designs  0.00  0       --

Design-specific decomposition of within-designs Q statistic

               Design     Q df  p-value
 Conventional:Retzius 24.71  2 < 0.0001

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 0.00  0      --     2.1845      4.7718

--- 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 3 1.00 2.1740 2.1740      .   . .       .
   Ultra:Conventional 1 1.00 1.1513 1.1513      .   . .       .
        Retzius:Ultra 0    0 1.8882      . 1.8882   . .       .

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)