Introduction
Methods
Data source and search strategy
Study selection: inclusion and exclusion criteria
Data collection and quality assessment
Statistical analysis
Results
Literature search
Author, Year | Study | Country | Ethnicity | Gender | Age(controls/patients) | Normal sample size(eye) | Experimental sample size(eye) | The type of glaucoma | Whether patients were treated for glaucoma | Machine | IOPGAT(mmHg) |
---|---|---|---|---|---|---|---|---|---|---|---|
Morales, 2021 [8] | Observational, cross-sectional, study | Spain | - | M/F | (21.45 ± 9.94)/(18.60 ± 11.65) | 40 | 50 | PCG | - | ORA | 18.18 ± 3.94 |
Sullivan, 2008 [9] | Observational, cross-sectional study | The United States | Whites, Hispanics, blacks, native Americans | - | (64.5 ± 12.9)/(71.9 ± 10.0) | 71 | 99 | GLC | - | ORA | - |
Hocaoglu, 2020 [10] | Observational, cross-sectional study | Turkey | - | M/F | (55.43 ± 8.65)/(62.96 ± 8.15) | 133 | 68 | POAG | Yes | ORA | 16.65 ± 5.42 |
Fujishiro, 2020 [11] | Observational, cross-sectional study | Japan | - | M/F | (31.5 ± 5.1)/(62.9 ± 10.3) | 35 | 104 | POAG | - | Corvis ST, ORA | - |
Aoki, 2021 [12] | Retrospective, cross-sectional study | Japan | - | - | (69.4 ± 13.9)/(69.1 ± 13.4) | 68 | 68 | POAG | Yes | Corvis ST, ORA | 12.9 ± 3.2 |
Park, 2018 [13] | Retrospective, cross-sectional study | Korea | - | M/F | (56.35 ± 10.46)/NTG early: (53.92 ± 12.03)/advanced: (62.38 ± 11.96) | 93 | 95 | NTG | No | ORA | NTG early: 15.10 ± 3.18/ advanced: 15.17 ± 2.99 |
Cankaya, 2012 [14] | Observational, cross-sectional study | Turkey | - | M/F | (68.4 ± 5.7)/(70.2 ± 7.3) | 102 | 78 | EXG | - | ORA | 16.3 ± 4.1 |
Yazgan, 2015 [15] | Observational, cross-sectional study | Turkey | - | M/F | (67.83 ± 6.75)/(73.50 ± 5.36) | 45 | 30 | PEXG | - | ORA | 15.7 ± 4.02 |
Detry, 2011 [16] | Observational, cross-sectional study | Belgium | - | M/F | (58.0 ± 14.0)/(70.0 ± 11.0) | 24 | 108 | POAG | - | ORA | 17.0 ± 4.3 |
Perucho, 2016 [17] | Observational, cross-sectional study | Spain | Caucasian | - | (18.07 ± 11.34)/(19.18 ± 11.45) | 103 | 118 | PCG | - | ORA | 18.32 ± 5.13 |
Perucho, 2017 [18] | Observational, cross-sectional study | Spain | - | M/F | (5.20 ± 3.25)/(5.64 ± 2.85) | 66 | 94 | PCG | - | ORA | - |
Gatzioufas, 2013 [19] | Prospective, observational study | German | - | M/F | (14.2 ± 3.6)/(13.6 ± 4.8) | 40 | 40 | PCG | - | ORA | |
Morita, 2012 [20] | Observational, cross-sectional study | Japan | - | M/F | (57.7 ± 12.1)/(59.1 ± 12.3) | 83 | 83 | NTG | - | ORA | 14.0 ± 2.2 |
Costin, 2014 [21] | Prospective, observational study | Finland | - | - | (56.5 ± 5.7)/(63.6 ± 12.1) | 15 | 13 | POAG | - | ORA | 14.5 ± 3.6 |
Beyazyıldız, 2014 [22] | Observational cross-sectional study | Turkey | - | M/F | Control: (51.2 ± 11.6)/EXG: (68.6 ± 8.5)/POAG: (58.9 ± 10.7) | 50 | 46/66 | EXG/POAG | - | ORA | EXG: (16.5 ± 4.1)/POAG: (16.4 ± 4.2) |
Mangouritsas, 2009 [23] | Prospective, observational study | Greece | - | M/F | (59.2 ± 14.2)/(62.4 ± 9.8) | 74 | 108 | POAG | - | ORA | 16.38 ± 2.73 |
Narayanaswamy, 2011 [24] | Prospective observational study | Singapore | - | M/F | Control: (54.7 ± 8.5)/PACG: (67.1 ± 9.8)/POAG: (64.6 ± 10.5) | 150 | 131/162 | PACG/POAG | - | ORA | (16.4 ± 0.8)/(14.4 ± 0.5) |
Kaushik, 2012 [25] | Prospective observational study | India | - | M/F | Unclear(> 18 years of age) | 71 | 59/36 | PACG/POAG | - | ORA | PACG(16.2 ± 3.9)/POAG: (23.6 ± 12.4) |
Shin, 2015 [26] | Prospective, cross-sectional study | Korea | - | M/F | (49.0 ± 16.07)/(52.24 ± 14.48) | 89 | 97 | NTG | - | ORA | GAT: (14.94 ± 3.27)/ICare: (14.71 ± 3.19) |
Ayala, 2011 [27] | Retrospective, cross-sectional study | Sweden | - | M/F | Control: (67 ± 9)/POAG: (62 ± 13)/PXSG: (71 ± 9) | 30 | 30/30 | POAG/PXSG | - | ORA | POAG: (16.4 ± 4.6)/PXSG: (17.5 ± 5.6) |
Detry, 2012 [28] | Observational cross-sectional study | Belgium | African, Caucasian | M/F | African: (43.9 ± 11.4)/(53.8 ± 12.7) Caucasian: (58.4 ± 14.7)/(70.6 ± 9.2) | 55 | 59 | POAG | - | ORA | African: (18.0 ± 5.0) Caucasian: (16.4 ± 3.7) |
Grise, 2012 [29] | Retrospective, cross-sectional study | France | - | - | Control: (57.5 ± 5.9)/NTG: (56.1 ± 5.1)/POAG: (59.9 ± 4.9) | 44 | 28/75 | NTG/POAG | - | ORA | NTG: (13.0 ± 2.63)/POAG: (18.0 ± 4.42) |
Morales, 2022 [33] | Observational cross-sectional study | Spain | - | M/F | Unclear(> 18 years of age) | 40 | 40 | PCG | - | ORA | - |
Jung, 2020 [31] | Retrospective cross-sectional study | Korea | - | M/F | Control: (56.19 ± 12.45)/POAG: (55.13 ± 15.65)/EXG: (57.77 ± 13.00) | 61 | 46/54 | POAG/NTG | 32/38a | Corvis ST | - |
Miki, 2020 [30] | Retrospective cross-sectional study | Japan | - | - | (56.4 ± 13.2)/(52.7 ± 14.6) | 35 | 35 | NTG | - | Corvis ST | 15.6 ± 2.8 |
Hussnain, 2015 [32] | Retrospective, cross-sectional study | The United States | - | - | (61.59 ± 16.56)/(70.73 ± 11.33) | 1418 | 322 | POAG | - | ORA | - |
Reznicek, 2013 [34] | Prospective observational study | German | - | - | Control: (55.4 ± 15.5)/ OAG: (63.1 ± 13.9) | 36 | 142/106/14/22 | OAG/POAG/NTG/PEXG | - | Corvis ST | OAG: (15.4 ± 6.1)/POAG: (16.5 ± 7.2)/NTG: (11.1 ± 1.5)/PEXG: (13.9 ± 3.5) |
Study characteristics
Comparison analysis
Comparison of AL values between glaucoma patients and normal subjects
Comparison of CCT between glaucoma patients and normal subjects
Comparison of CH between glaucoma patients and normal subjects
Comparison of CRF between glaucoma patients and normal subjects
Comparison of IOPcc and IOPg between glaucoma patients and normal subjects
Subgroup analysis
Heterogeneity | |||||||||
---|---|---|---|---|---|---|---|---|---|
No | MD(95%CI) | Q | I2 | PQ | χ2 | P | |||
a. Subgroup analysis of CCT | |||||||||
Age | ≥ 18 years old < 18 years old | 4328 240 | -6.89(-9.61, -4.17) -28.44(-64.71, 7.83) | 52.20 17.55 | 37% 94% | 0.02 0.000 | 4.964 1.54 | 0.000 0.12 | |
Whether patients were treated for glaucoma | Used medicine Not used medicine Not mentioned | 559 376 3633 | -3.94(-9.51, 1.64) -2.86(-9.35, 3.64) -9.60(-13.71, -5.49) | 0.50 1.12 83.43 | 0% 11% 65% | 0.92 0.29 0.000 | 1.38 0.86 4.58 | 0.17 0.39 0.000 | |
OAG | 178 | -20.00(-37.32, -2.68) | - | - | - | 2.26 | 0.02 | ||
POAG NTG | 1895 1035 | -6.59(-10.86,-2.32) -5.97(-10.00, -1.94) | 22.56 7.85 | 38% 11% | 0.07 0.35 | 3.03 2.90 | 0.002 0.004 | ||
The type of glaucoma | PCG GLC | 410 170 | -18.11(-40.65, 4.43) -5.00(-16.14, 6.14) | 25.99 - | 88% - | 0.000 - | 1.57 0.88 | 0.12 0.38 | |
EXG PACG PXSG | 409 411 60 | -9.48 (-28.43,9.47) -7.68(-14.72, -0.64) -3.00(-13.63, 7.63) | 17.46 0.14 - | 83% 0% - | 0.000 0.71 - | 0.98 2.14 0.55 | 0.33 0.03 0.58 | ||
The type of machine | ORA Corvis ST ORA and Corvis ST | 3573 720 275 | -7.48(-11.42,-3.55) -11.34(-19.87, -2.80) -11.85(-25.18, 1.47) | 76.00 10.90 2.34 | 66% 45% 57% | 0.000 0.09 0.13 | 3.73 2.60 1.74 | 0.000 0.009 0.08 | |
b. Subgroup analysis of CH | |||||||||
Age | ≥ 18 years old < 18 years old Not clearly defined | 4564 240 221 | -1.39(-1.72, -1.06) -2.48(-2.90, -2.06) -2.86(-3.37, -2.35) | 196.47 0.61 - | 88% 0% - | 0.000 0.43 - | 8.30 11.46 10.93 | 0.000 0.000 0.000 | |
Whether patients were treated for glaucoma | Used medicine Not used medicine Not mentioned | 337 376 4312 | -1.07(-1.37, -0.77) -0.66(-1.42, 0.11) -1.68(-2.07, -1.28) | 0.21 6.01 238.11 | 0% 83% 91% | 0.65 0.01 0.000 | 6.95 1.69 8.27 | 0.000 0.09 0.000 | |
POAG NTG | 2955 728 | -1.14(-1.49,-0.79) -0.91(-1.49, -0.33) | 53.11 21.04 | 79% 86% | 0.000 0.000 | 6.40 3.06 | 0.000 0.002 | ||
The type of glaucoma | PCG GLC | 631 170 | -2.71(-3.01, -2.41) -1.60(-2.06, -1.14) | 3.00 - | 0% - | 0.56 - | 17.88 6.86 | 0.000 0.000 | |
EXG PACG PXSG | 351 130 60 | -2.66 (-3.45, -1.88) -0.20(-0.70, 0.30) -1.80(-2.58, -1.02) | 7.98 - - | 75% - - | 0.02 - - | 6.64 0.78 4.50 | 0.000 0.44 0.000 | ||
The type of machine | ORA Corvis ST ORA and Corvis ST | 4750 - 275 | -1.59(-1.96,-1.21) - -1.08(-1.37, -0.80) | 265.29 - 0.26 | 91% - 0% | 0.000 - 0.61 | 8.24 - 7.42 | 0.000 - 0.000 | |
c. Subgroup analysis of CRF | |||||||||
Age | ≥ 18 years old < 18 years old Not clearly defined | 2358 240 221 | -0.71(-1.10, -0.31) -1.68(-3.32, -0.03) -1.17(-1.81, -0.53) | 109.33 12.40 - | 84% 92% - | 0.000 0.000 - | 3.49 2.00 3.57 | 0.000 0.05 0.000 | |
Whether patients were treated for glaucoma | Used medicine Not used medicine Not mentioned | 201 376 2242 | -0.61(-1.16, -0.06) -0.77(-1.25, -0.29) -0.84(-1.31, -0.38) | - 1.84 138.37 | - 46% 88% | - 0.18 0.000 | 2.16 3.16 3.55 | 0.03 0.002 0.000 | |
POAG NTG | 819 728 | -0.31(-1.11, 0.48) -1.02(-1.54, -0.51) | 46.62 12.99 | 87% 77% | 0.000 0.005 | 0.78 3.91 | 0.44 0.000 | ||
The type of glaucoma | PCG GLC | 631 170 | -1.47(-2.12, -0.81) -0.90(-1.44, -0.36) | 15.94 - | 75% - | 0.003 - | 4.40 3.24 | 0.000 0.001 | |
EXG PACG PXSG | 351 130 - | -1.14 (-2.34, 0.05) 0.70(-0.00, 1.40) - | 15.27 - - | 87% - - | 0.000 - - | 1.87 1.95 - | 0.06 0.05 - | ||
The type of machine | ORA Corvis ST ORA and Corvis ST | 2680 - 139 | -0.80(-1.20,-0.40) - -1.34(-1.95, -0.73) | 139.97 - - | 86% - - | 0.000 - - | 3.89 - 4.31 | 0.000 - 0.000 |
Sensitivity analysis
Publication bias
The P value of Egger’s Test | |
---|---|
CCT | 0.459 |
CH | 0.023 |
CRF | 0.319 |
Quality assessment
Study | Patient selection | Comparability | Outcome assessments | Sum of score |
---|---|---|---|---|
Morales, 2021 [8] | **** | * | ** | 7 |
Sullivan, 2008 [9] | **** | * | ** | 7 |
Hocaoglu, 2020 [10] | **** | ** | ** | 8 |
Fujishiro, 2020 [11] | **** | * | ** | 7 |
Aoki, 2021 [12] | **** | ** | ** | 8 |
Park, 2018 [13] | **** | ** | ** | 8 |
Cankaya, 2012 [14] | **** | * | ** | 7 |
Yazgan, 2015 [15] | **** | * | ** | 7 |
Detry, 2011 [16] | **** | * | ** | 7 |
Perucho, 2016 [17] | **** | * | ** | 7 |
Perucho, 2017 [18] | **** | * | ** | 7 |
Gatzioufas, 2013 [19] | **** | * | ** | 7 |
Morita, 2012 [20] | **** | * | ** | 7 |
Costin, 2014 [21] | **** | * | ** | 7 |
Beyazyıldız, 2014 [22] | **** | * | ** | 7 |
Mangouritsas, 2009 [23] | **** | * | ** | 7 |
Narayanaswamy, 2011 [24] | **** | * | ** | 7 |
Kaushik, 2012 [25] | **** | * | ** | 7 |
Shin, 2015 [26] | **** | * | ** | 7 |
Ayala, 2011 [27] | **** | * | ** | 7 |
Detry, 2012 [28] | **** | * | ** | 7 |
Grise, 2012 [29] | **** | * | ** | 7 |
Morales, 2022 [33] | **** | * | ** | 7 |
Jung, 2020 [31] | **** | * | ** | 7 |
Miki, 2020 [30] | **** | * | ** | 7 |
Hussnain, 2015 [32] | **** | * | ** | 7 |
Reznicek, 2013 [34] | **** | * | ** | 7 |