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. 2024 Mar 18;17(3):408–419. doi: 10.18240/ijo.2024.03.02

Table 2. Subgroup analyses and Meta-regression results.

Variables No. of models Sensitivity
Specificity
PLR
NLR
DOR
AUC Meta regressionP
Pooled (95%CI) I² Pooled (95%CI) I² Pooled (95%CI) I² Pooled (95%CI) I² Pooled (95%CI) I²
Region 0.00
 Asian 28 0.94 (0.92, 0.96) 92.62% 0.91 (0.87, 0.94) 94.06% 10.39 (7.38, 14.63) 93.74% 0.06 (0.04, 0.09) 93.52% 168.82 (90.82, 313.80) 100% 0.97
 Western 23 0.82 (0.70, 0.89) 93.54% 0.88 (0.85, 0.91) 75.45% 6.84 (4.81, 9.70) 76.38% 0.21 (0.12, 0.36) 92.69% 33.08 (13.85, 79.05) 100% 0.92
Method 0.00
 ML 27 0.84 (0.76, 0.90) 94.23% 0.87 (0.84, 0.90) 88.56% 6.67 (5.05, 8.79) 87.11% 0.18 (0.11, 0.29) 94.54% 36.98 (19.30, 70.86) 100% 0.92
 DL 24 0.95 (0.91, 0.97) 94.71% 0.92 (0.89, 0.94) 92.60% 11.94 (8.23, 17.32) 92.05% 0.06 (0.03, 0.10) 95.12% 209.55 (91.56, 4779.59) 100% 0.98
Outcome 0.06
 OAG 39 0.91 (0.86, 0.95) 95.38% 0.91 (0.89, 0.93) 85.87% 10.23 (7.73, 13.55) 86.58% 0.10 (0.06, 0.16) 95.89% 107.50 (52.10, 221.80) 100% 0.96
 Glaucoma 12 0.88 (0.83, 0.92) 88.39% 0.84 (0.79, 0.89) 88.18% 5.62 (4.09, 7.74) 85.38% 0.14 (0.09, 0.21) 89.44% 40.55 (21.54, 76.32) 100% 0.93
Device
 Topcon 3D OCT 7 0.92 (0.85, 0.96) 89.58% 0.90 (0.87, 0.93) 71.39% 9.59 (6.89, 13.36) 50.19% 0.09 (0.05, 0.17) 89.10% 108.97 (52.58, 225.86) 100% 0.95 0.58
 Heidelberg Spectralis OCT 10 0.94 (0.91, 0.96) 93.56% 0.94 (0.89, 0.97) 96.22% 15.72 (8.66, 28.53) 95.81% 0.06 (0.04, 0.10) 95.06% 243.19 (91.31, 647.67) 100% 0.98 0.02
 Cirrus ZEISS OCT 30 0.85 (0.77, 0.90) 93.78% 0.87 (0.83, 0.90) 86.96% 6.38 (4.78, 8.52) 83.98% 0.17 (0.11, 0.27) 93.84% 36.70 (19.21, 70.13) 100% 0.92 0.00

DL: Deep learning; ML: Machine learning; OAG: Open angle glaucoma; PLR: Positive likelihood ratio; NLR: Negative likelihood ratio; DOR: Diagnostic odds ratio; AUC: Area under curve.