Computational and Mathematical Methods in Medicine

Research Article

[Retracted] Serum Adiponectin Level in Different Stages of Type 2 Diabetic Kidney Disease: A Meta-Analysis

Table 2

Sensitivity analysis.
Excluded studyNormoalbuminuria vs. controlMicroalbuminuria vs. normoalbuminuriaMacroalbuminuria vs. microalbuminuria
Mean difference (95% CI)Mean difference (95% CI)Mean difference (95% CI)
Sun [18]98.5%0.001-0.37 (-1.22, 0.47)97.3%0.0012.50 (1.87, 3.12)97.9%0.0012.50 (1.73, 3.27)
Bai [19]98.5%0.001-0.46 (-1.30, 0.39)97.9%0.0012.38 (1.68, 3.08)98.0%0.0012.32 (1.54, 3.11)
Cheng [20]98.5%0.001-0.46 (-1.30, 0.37)97.9%0.0012.40 (1.71, 3.09)98.1%0.0012.40 (1.60, 3.20)
Xu [21]98.5%0.001-0.38 (-1.22, 0.46)97.9%0.0012.37 (1.68, 3.06)98.1%0.0012.41 (1.61, 3.22)
Tian [22]98.5%0.001-0.36 (-1.19, 0.47)97.8%0.0012.21 (1.55, 2.88)98.0%0.0012.26 (1.48, 3.04)
Bi [23]98.4%0.001-0.35 (-1.20, 0.49)97.5%0.0012.25 (1.61, 2.89)97.8%0.0012.26 (1.51, 3.01)
Zhou [24]98.4%0.001-0.33 (-1.15, 0.50)97.9%0.0012.39 (1.70, 3.09)98.1%0.0012.40 (1.60, 3.21)
Lu [25]98.5%0.001-0.40 (-1.26, 0.46)97.5%0.0012.47 (1.81, 3.12)97.8%0.0012.48 (1.70, 3.25)
Nie [26]98.5%0.001-0.36 (-1.20, 0.47)97.8%0.0012.31 (1.63, 2.99)98.1%0.0012.42 (1.61, 3.23)
Lin [27]98.3%0.001-0.59 (-1.38, 0.21)97.8%0.0012.33 (1.65, 3.01)98.0%0.0012.35 (1.55, 3.15)
Tang [28]98.5%0.001-0.36 (-1.20, 0.47)97.8%0.0012.23 (1.57, 2.90)98.0%0.0012.28 (1.50, 3.06)
Zhou [29]98.4%0.001-0.27 (-1.09, 0.55)97.9%0.0012.40 (1.71, 3.09)98.1%0.0012.35 (1.55, 3.14)
Hu [30]98.5%0.001-0.37 (-1.21, 0.46)97.9%0.0012.36 (1.67, 3.04)98.1%0.0012.40 (1.60, 3.20)
Wan [31]98.5%0.001-0.38 (-1.21, 0.46)97.9%0.0012.37 (1.68, 3.06)98.1%0.0012.43 (1.62, 3.23)
Xie [32]98.5%0.001-0.46 (-1.30, 0.38)97.8%0.0012.27 (1.60, 2.94)98.1%0.0012.35 (1.56, 3.15)
Li [33]98.3%0.001-0.62 (-1.40, 0.17)97.8%0.0012.34 (1.65, 3.02)98.0%0.0012.36 (1.56, 3.15)
Zhou [34]98.5%0.001-0.34 (-1.17, 0.49)97.9%0.0012.39 (1.70, 3.09)98.1%0.0012.41 (1.60, 3.21)
Zhong [35]98.5%0.001-0.45 (-1.29, 0.40)97.9%0.0012.39 (1.70, 3.08)98.1%0.0012.42 (1.62, 3.23)
Yang [36]98.4%0.001-0.52 (-1.34, 0.29)97.8%0.0012.34 (1.65, 3.02)97.9%0.0012.55 (1.78, 3.31)
Wan [37]98.5%0.001-0.32 (-1.15, 0.50)97.8%0.0012.31 (1.63, 2.99)98.1%0.0012.41 (1.60, 3.22)
Lin [38]98.5%0.001-0.37 (-1.20, 0.47)97.9%0.0012.36 (1.68, 3.05)98.1%0.0012.41 (1.60, 3.21)
Wu [39]98.4%0.001-0.55 (-1.35, 0.26)97.9%0.0012.39 (1.70, 3.09)98.1%0.0012.34 (1.55, 3.13)
Cheng [40]98.4%0.001-0.69 (-1.49, 0.12)97.8%0.0012.17 (1.50, 2.83)98.0%0.0012.19 (1.42, 2.96)
Yang [41]98.4%0.001-0.19 (-1.00, 0.62)97.8%0.0012.29 (1.61, 2.97)98.1%0.0012.32 (1.53, 3.11)
Liu [42]98.4%0.001-0.69 (-1.49, 0.12)97.8%0.0012.20 (1.54, 2.87)98.0%0.0012.12 (1.35, 2.89)
Yang [43]98.5%0.001-0.47 (-1.30, 0.36)97.9%0.0012.42 (1.73, 3.11)98.1%0.0012.36 (1.57, 3.16)
Zhu [44]98.5%0.001-0.39 (-1.24, 0.46)97.9%0.0012.42 (1.72, 3.12)97.8%0.0011.91 (1.17, 2.65)
Xiao [45]98.4%0.001-0.25 (-1.06, 0.56)97.9%0.0012.32 (1.64, 3.00)98.1%0.0012.37 (1.58, 3.17)
Kato [46]98.4%0.001-0.49 (-1.32, 0.33)97.9%0.0012.33 (1.65, 3.02)98.1%0.0012.33 (1.54, 3.12)
Yilmaz [47]N/AN/AN/A97.9%0.0012.47 (1.81, 3.14)98.0%0.0012.47 (1.68, 3.26)
Saito [48]98.4%0.001-0.33 (-1.15, 0.50)97.9%0.0012.40 (1.68, 3.11)97.9%0.0012.48 (1.70, 3.26)
Fujita [49]98.5%0.001-0.39 (-1.22, 0.45)97.9%0.0012.42 (1.73, 3.11)98.1%0.0012.42 (1.62, 3.22)
Komaba [50]N/AN/AN/A97.9%0.0012.41 (1.71, 3.12)98.1%0.0012.43 (1.62, 3.24)
Koshimura [51]N/AN/AN/A97.9%0.0012.41 (1.72, 3.09)98.1%0.0012.42 (1.62, 3.21)
Random-effect model used; N/A: not applicable.