Abstract
Introduction: The aim of this study was to compare the patterns of visual field (VF) defects in primary angle-closure glaucoma (PACG) to control groups of eyes with high-tension glaucoma (HTG) and normal-tension glaucoma (NTG). Methods: Forty-eight eyes with PACG were enrolled, and control eyes with HTG and NTG matched for age, sex, and mean deviation of VF defect were selected. VF tests were performed using the 24-2 program of the Humphrey field analyzer. VF defects were classified into six patterns with the Ocular Hypertension Treatment Study classification system and were categorized into three stages (early, moderate, and advanced). Each hemifield was divided into five regions according to the Glaucoma Hemifield Test (GHT). The mean total deviation (TD) of each GHT region was calculated. Results: Compared with HTG and NTG groups, the partial arcuate VF defects were more common in the PACG group. In the PACG group, the nasal GHT region in the inferior hemifield had the worst mean TD (−8.48 ± 8.62 dB), followed by the arcuate 1 (−7.81 ± 7.91 dB), arcuate 2 (−7.46 ± 7.43 dB), paracentral (−7.19 ± 7.98 dB), and central (−5.14 ± 6.24 dB) regions; the mean TD of the central region was significantly better than those for all other regions (all p < 0.05). A similar trend was observed in the superior hemifield in the PACG group but not the VF hemifields of the HTG and NTG groups. Conclusion: Patterns of VF defect in PACG patients differ from those with HTG and NTG. This discrepancy might be due to the differences in the pathogenic mechanisms of glaucomatous optic neuropathy.
Introduction
Glaucoma, the leading cause of global blindness, is a progressive optic neuropathy with characteristic structural changes and corresponding visual field (VF) defects [1]. Primary angle-closure glaucoma (PACG) is the main type of glaucoma in Asia, estimated to affect 20 million people, accounting for 26% of all glaucoma in the world [2, 3]. Although primary open-angle glaucoma (POAG) is more prevalent, PACG has a four to ten times higher rate of blindness than POAG, and therefore, nearly half the cases of glaucoma are blind due to PACG globally [4‒6]. VF defect from glaucoma is associated with lower vision-related quality of life [7, 8], and different VF defects may result in different functional disabilities [9].
Several reports suggest that different types of glaucoma show significant differences in structural damage of the optic disc and spatial patterns of VF defect, indicating different pathogenic mechanisms [10, 11]. High-tension glaucoma (HTG), POAG with elevated intraocular pressure (IOP), is considered to have a mixture of pressure-dependent and pressure-independent etiologies [12]. In addition to elevated IOP, other factors like ocular blood flow, vessel autoregulation, and cerebrospinal fluid pressure also contribute to glaucomatous damage in POAG [13‒15]. Compared with HTG, pressure-independent risk factors are considered more important in the pathophysiology of normal-tension glaucoma (NTG) [15‒17]. Previous studies revealed that VF defects in NTG are more central, more localized, and steeper than the VF defects in HTG [18‒20]. Furthermore, HTG eyes tend to have more diffused VF defects than eyes with NTG [21].
PACG is characterized by elevated IOP secondary to the mechanical obstruction of the aqueous outflow by an anatomically closed angle [22]. Contrary to POAG, PACG is thought to be a more pressure-dependent form of glaucoma [23]. The glaucomatous functional damage reflected the different pathogenic mechanisms of glaucoma subtypes. Therefore, the pattern of VF defects in PACG may differ from POAG, especially NTG. Comparing the characteristics and spatial distribution of VF defects in these three glaucoma subtypes may provide a better understanding of the pattern of VF defects in PACG. Several studies compare the VF damages of PACG and HTG, suggesting that the patterns of VF defects in PACG and POAG may differ [10, 11, 24, 25]. However, there is a paucity of published data directly comparing spatial characteristics of VF defects between PACG, HTG, and NTG and only a few studies comparing VF progression rates or interocular asymmetry of the VF defects in different glaucoma subtypes [26‒28]. Huang et al. [28] compared the interocular asymmetry of VF loss in glaucoma and found that PACG had more significant interocular asymmetry than NTG and POAG. Our previous study compared the intraocular asymmetry of VF and found that the superior hemifield was affected more severely than the inferior hemifield in all three subtypes of primary glaucoma. This tendency was more pronounced in NTG compared to HTG and PACG [29]. In the present study, we aimed to explore the patterns of VF defects in PACG eyes and to compare the findings to control groups of eyes with HTG and NTG.
Methods
Participants
This cross-sectional study was conducted at a tertiary referral center in China. Approval for the study was granted by the Ethics Committee of the Eye Hospital of Wenzhou Medical University. The study was conducted in accordance with the tenets of the Declaration of Helsinki, and written informed consent was obtained from all participants. Participants diagnosed with PACG or HTG by a glaucoma specialist (Y.B.L.) in the Glaucoma Clinic of the Wenzhou Medical University Eye Hospital were recruited during the period from January 2017 to December 2019. Patients with NTG were recruited from the Wenzhou Glaucoma Progression Study (WGPS), a longitudinal community-based study providing free glaucoma screenings in the Wenzhou area [29‒31].
Glaucoma diagnoses required the presence of glaucomatous optic neuropathy (optic disc hemorrhage, retinal nerve fiber layer defect, vertical cup-to-disc ratio >0.7 and/or cup-to-disc ratio asymmetry >0.2, or neuroretinal rim width <0.1) with correlating VF defects [32]. PACG was diagnosed in the presence of angle closure (posterior trabecular meshwork was not visible in ≥180° on gonioscopy). POAG is defined as the presence of an open anterior chamber angle as assessed by gonioscopy, evidence of glaucomatous optic neuropathy, and a corresponding VF defect. POAG patients with six untreated IOP measurements consistently <21 mm Hg with no single measurement >24 mm Hg and no more than one reading equal to 23 or 24 mm Hg were classified as NTG and others as HTG [29, 33]. Additional inclusion criteria were as follows: age 18 years or older, spherical equivalent refractive error between −6.0 and +3.0 diopter (D), and presenting visual acuity ≥6/18. Subjects with secondary glaucoma, previous laser or incisional surgery of the retina, and/or other conditions potentially affecting the VF were excluded.
All subjects underwent an ophthalmologic examination, including visual acuity testing, IOP measurement, slit-lamp examination, VF testing (Humphrey Field Analyzer II; Carl Zeiss Meditec Inc, Dublin, CA, USA), and fundus photography (VISUCAM 200; Carl Zeiss Meditec Inc, Dublin, CA, USA). IOPs were measured between 8:00 a.m. and 5:00 p.m. on 1 day, and the median of the two readings was used. All examinations were performed by certified technicians.
Visual Fields
VF testing was performed using program 24-2 with the Swedish Interactive Threshold Algorithm (SITA) program. A minimum of 2 VF tests were conducted using the 24-2 programs. The test completed with fixation loss rates <20% and false-positive and false-negative error rates <15% were considered reliable and eligible for the analysis; the first VF test for each participant was excluded from analysis.
According to the mean deviation (MD), VF severity was categorized into three stages: early glaucoma (≥−6 dB), moderate glaucoma (<−6 dB and >−12 dB), advanced glaucoma (≤−12 dB) [34]. Furthermore, the VF defects were classified into six patterns in each of the superior and inferior hemifields: altitudinal, arcuate, nasal step, paracentral, partial arcuate, and temporal wedge, according to the Ocular Hypertension Treatment (OHT) Study classification system [35]. Meanwhile, the total deviation (TD) probability plot was divided into five subfield regions in each of the superior and inferior hemifields: central, paracentral, nasal, and two peripheral (arcuate 1 and arcuate 2), according to the Glaucoma Hemifield Test (GHT) sectors [10]. The distribution of defect patterns and deviation of the test points within these regions were calculated.
Statistical Analysis
To compare the three glaucoma subtypes, this study equalized the baseline characteristics of the groups using propensity score matching. The propensity score was calculated using multivariable logistic regression analysis based on several demographic and clinical covariates, namely, age, sex, MD, and VF severity level. The caliper for the propensity match was set at 0.5. Using predicted probabilities and the nearest-neighbor-matching technique, 48 PACG eyes could be matched with either NTG or HTG eyes simultaneously, and these 48 triplets were selected for comparison. Generalized estimating equation (GEE) models were used to compare the demographic characteristics and parameters between groups as we used data from both eyes. For the point-wise analysis, the mean TD value of each VF test point in the superior hemifield was compared with its corresponding point in the inferior hemifield for the three groups using the GEE model, accounting for mean TD. For the region-wise analysis, the mean TDs of the 5 GHT regions in the superior hemifield were compared with their counterparts in the inferior hemifield for the three groups using the GEE model, adjusted for mean TD and sex. The relationship between the TD and pattern standard deviation (PSD) was compared in the three groups using GEE models. Statistical significance was set at p < 0.05, and all analyses were performed using “R” software (R version 4.0.2; The Foundation for Statistical Computing, Vienna, Austria, http://www.r-project. org).
Results
In total, 114 patients with PACG (162 eyes), 74 HTG patients with (111 eyes), and 102 patients with NTG (148 eyes) were included in the study. After propensity score matching, 144 eyes were eligible at a 1:1:1 ratio, resulting in 48 eyes included in each glaucoma subtype. Table 1 compares the demographic and ocular characteristics of participants. There was no significant difference in age, sex, MD, or degree of VF loss between the PACG, HTG, and NTG groups (p = 0.154, 0.310, 0.272, 0.644, respectively). The mean TD, PSD, and visual field index were similar across the groups. The mean spherical equivalent refraction was most hyperopic in the PACG group (p = 0.003), and the mean IOP at presentation was highest in the HTG group (p = 0.007).
Demographic and ocular characteristics of the matched subjects
Characteristics . | PACG . | HTG . | NTG . | p value . |
---|---|---|---|---|
Eyes, n | 48 | 48 | 48 | |
Age, years | 61.2 (7.98) | 56.1 (17.3) | 58.8 (15.9) | 0.154 |
Male sex, n (%) | 16 (38.1) | 25 (61.0) | 20 (46.5) | 0.310 |
VA, logMAR | 0.12 (0.15) | 0.17 (0.16) | 0.21 (0.16) | 0.049 |
SE, D | 0.18 (2.08) | −1.30 (2.64) | −1.61 (3.00) | 0.003 |
IOP at test, mm Hg | 14.8 (5.03) | 17.7 (5.81) | 14.7 (3.42) | 0.007 |
TD, dB | −7.79 (6.05) | −9.74 (5.81) | −8.15 (7.11) | 0.398 |
MD, dB | −7.40 (5.99) | −9.76 (8.74) | −8.04 (7.26) | 0.272 |
PSD, dB | 5.74 (3.74) | 6.65 (4.16) | 7.40 (4.48) | 0.142 |
VFI, % | 83.3 (17.6) | 73.8 (28.0) | 77.5 (21.3) | 0.095 |
VF defect severity, n (%) | 0.644 | |||
Early stage | 24 (50.0) | 21 (43.8) | 24 (50.0) | |
Moderate stage | 15 (31.2) | 14 (29.2) | 12 (25.0) | |
Advanced stage | 9 (18.8) | 13 (27.0) | 12 (25.0) |
Characteristics . | PACG . | HTG . | NTG . | p value . |
---|---|---|---|---|
Eyes, n | 48 | 48 | 48 | |
Age, years | 61.2 (7.98) | 56.1 (17.3) | 58.8 (15.9) | 0.154 |
Male sex, n (%) | 16 (38.1) | 25 (61.0) | 20 (46.5) | 0.310 |
VA, logMAR | 0.12 (0.15) | 0.17 (0.16) | 0.21 (0.16) | 0.049 |
SE, D | 0.18 (2.08) | −1.30 (2.64) | −1.61 (3.00) | 0.003 |
IOP at test, mm Hg | 14.8 (5.03) | 17.7 (5.81) | 14.7 (3.42) | 0.007 |
TD, dB | −7.79 (6.05) | −9.74 (5.81) | −8.15 (7.11) | 0.398 |
MD, dB | −7.40 (5.99) | −9.76 (8.74) | −8.04 (7.26) | 0.272 |
PSD, dB | 5.74 (3.74) | 6.65 (4.16) | 7.40 (4.48) | 0.142 |
VFI, % | 83.3 (17.6) | 73.8 (28.0) | 77.5 (21.3) | 0.095 |
VF defect severity, n (%) | 0.644 | |||
Early stage | 24 (50.0) | 21 (43.8) | 24 (50.0) | |
Moderate stage | 15 (31.2) | 14 (29.2) | 12 (25.0) | |
Advanced stage | 9 (18.8) | 13 (27.0) | 12 (25.0) |
Data are mean±standard deviation unless otherwise indicated.
VA, visual acuity; SE, spherical equivalent; IOP, intraocular pressure; TD, total deviation; MD, mean deviation; PSD, pattern standard deviation; VFI, visual field index; VF, visual field.
In terms of VF defect patterns, the partial arcuate defect was the most common defect pattern in the PACG group, being noted in 41.7% of eyes in the superior hemifield and 39.5% of eyes in the inferior hemifield (Table 2). In the HTG group, altitudinal and arcuate (29.2% and 25.0%, respectively) were the dominant patterns in the superior hemifield, whereas partial arcuate dominated the inferior hemifield (32.4%). In the NTG group, arcuate (37.5%) was the dominant pattern in the superior hemifield, and partial arcuate dominated the inferior hemifield (35.3%).
Distribution of VF defect patterns of the matched subjects
Types of VF defects, n (%) . | PACG (n = 48) . | HTG (n = 48) . | NTG (n = 48) . |
---|---|---|---|
Superior hemifield | |||
No defect | 7 (14.6) | 3 (6.3) | 5 (10.4) |
Temporal wedge | 1 (2.1) | 0 (0) | 0 (0) |
Altitudinal | 2 (4.2) | 14 (29.2) | 5 (10.4) |
Paracentral | 3 (6.2) | 3 (6.3) | 5 (10.4) |
Nasal step | 4 (8.3) | 6 (12.5) | 1 (2.1) |
Arcuate | 11 (22.9) | 12 (25.0) | 18 (37.5) |
Partial arcuate | 20 (41.7) | 10 (20.7) | 14 (29.2) |
Inferior hemifield | |||
No defect | 9 (18.8) | 11 (22.9) | 9 (18.8) |
Temporal wedge | 1 (2.1) | 0 (0) | 0 (0) |
Altitudinal | 2 (4.2) | 10 (20.7) | 3 (6.3) |
Paracentral | 6 (12.5) | 2 (4.2) | 7 (14.6) |
Nasal step | 3 (6.3) | 4 (8.3) | 6 (12.5) |
Arcuate | 8 (16.6) | 6 (12.5) | 6 (12.5) |
Partial arcuate | 19 (39.5) | 15 (32.4) | 17 (35.3) |
Types of VF defects, n (%) . | PACG (n = 48) . | HTG (n = 48) . | NTG (n = 48) . |
---|---|---|---|
Superior hemifield | |||
No defect | 7 (14.6) | 3 (6.3) | 5 (10.4) |
Temporal wedge | 1 (2.1) | 0 (0) | 0 (0) |
Altitudinal | 2 (4.2) | 14 (29.2) | 5 (10.4) |
Paracentral | 3 (6.2) | 3 (6.3) | 5 (10.4) |
Nasal step | 4 (8.3) | 6 (12.5) | 1 (2.1) |
Arcuate | 11 (22.9) | 12 (25.0) | 18 (37.5) |
Partial arcuate | 20 (41.7) | 10 (20.7) | 14 (29.2) |
Inferior hemifield | |||
No defect | 9 (18.8) | 11 (22.9) | 9 (18.8) |
Temporal wedge | 1 (2.1) | 0 (0) | 0 (0) |
Altitudinal | 2 (4.2) | 10 (20.7) | 3 (6.3) |
Paracentral | 6 (12.5) | 2 (4.2) | 7 (14.6) |
Nasal step | 3 (6.3) | 4 (8.3) | 6 (12.5) |
Arcuate | 8 (16.6) | 6 (12.5) | 6 (12.5) |
Partial arcuate | 19 (39.5) | 15 (32.4) | 17 (35.3) |
Data are mean±standard deviation unless otherwise indicated.
VFI, visual field index.
Table 3 presents the distributions of the mean TDs of the GHT regions in the matched subjects. In PACG eyes, the nasal region in the inferior hemifield had the worst mean TD, followed by the arcuate 1, arcuate 2, paracentral and central regions; the mean TD of the central region was significantly better than those for all other regions (all p < 0.05, Table 4). A similar trend was observed in the superior hemifield in PACG eyes. In HTG eyes, the mean TD was worst in the superior nasal region and the inferior paracentral regions, whereas the mean TD was best in the superior arcuate 2 and inferior central regions. In the NTG group, the nasal region had the worst mean TD, and the arcuate 2 region had the best mean TD in both hemifields.
Within-hemifield comparisons of the GHT regions in the matched subjects (dB)
. | Central . | Paracentral . | Nasal . | Peripheral, arcuate 1 . | Peripheral, arcuate 2 . | p value . |
---|---|---|---|---|---|---|
Superior hemifield | ||||||
PACG | −6.24±7.78 | −8.49±9.44 | −10.37±8.54 | −8.71±7.25 | −8.27±7.89 | <0.001 |
HTG | −10.03±10.9 | −11.02±11.8 | −12.74±11.2 | −9.92±10.9 | −9.55±10.8 | 0.012 |
NTG | −9.53±10.4 | −10.59±11.1 | −12.61±11.2 | −10.21±9.90 | −9.45±9.71 | 0.009 |
Inferior hemifield | ||||||
PACG | −5.14±6.24 | −7.19±7.98 | −8.48±8.62 | −7.81±7.91 | −7.46±7.43 | <0.001 |
HTG | −7.65±9.76 | −10.25±10.7 | −10.18±10.6 | −9.32±10.1 | −8.64±9.01 | 0.036 |
NTG | −6.32±9.54 | −7.11±10.1 | −8.11±10.2 | −6.12±8.63 | −4.82±8.12 | <0.001 |
. | Central . | Paracentral . | Nasal . | Peripheral, arcuate 1 . | Peripheral, arcuate 2 . | p value . |
---|---|---|---|---|---|---|
Superior hemifield | ||||||
PACG | −6.24±7.78 | −8.49±9.44 | −10.37±8.54 | −8.71±7.25 | −8.27±7.89 | <0.001 |
HTG | −10.03±10.9 | −11.02±11.8 | −12.74±11.2 | −9.92±10.9 | −9.55±10.8 | 0.012 |
NTG | −9.53±10.4 | −10.59±11.1 | −12.61±11.2 | −10.21±9.90 | −9.45±9.71 | 0.009 |
Inferior hemifield | ||||||
PACG | −5.14±6.24 | −7.19±7.98 | −8.48±8.62 | −7.81±7.91 | −7.46±7.43 | <0.001 |
HTG | −7.65±9.76 | −10.25±10.7 | −10.18±10.6 | −9.32±10.1 | −8.64±9.01 | 0.036 |
NTG | −6.32±9.54 | −7.11±10.1 | −8.11±10.2 | −6.12±8.63 | −4.82±8.12 | <0.001 |
Data are mean ± standard deviation.
Comparisons of the GHT regions within the hemifields of the matched subjects
Variable . | Central versus paracentral . | Central versus nasal . | Central versus arcuate 1 . | Central versus arcuate 2 . | Nasal versus paracentral . | Nasal versus arcuate 1 . | Nasal versus arcuate 2 . | Paracentral versus arcuate 1 . | Paracentral versus arcuate 2 . | Arcuate 1 versus arcuate 2 . |
---|---|---|---|---|---|---|---|---|---|---|
Superior hemifield | ||||||||||
PACG | 0.001 | <0.001 | 0.004 | 0.116 | 0.013 | 0.067 | 0.049 | 0.696 | 0.882 | 0.377 |
HTG | 0.236 | <0.001 | 0.724 | 0.960 | 0.031 | 0.001 | 0.002 | 0.235 | 0.217 | 0.533 |
NTG | 0.190 | 0.001 | 0.348 | 0.829 | 0.037 | 0.016 | 0.014 | 0.844 | 0.360 | 0.245 |
Inferior hemifield | ||||||||||
PACG | 0.003 | <0.001 | 0.008 | 0.006 | 0.015 | 0.414 | 0.141 | 0.173 | 0.660 | 0.478 |
HTG | <0.001 | <0.001 | 0.001 | 0.135 | 0.963 | 0.235 | 0.198 | 0.239 | 0.132 | 0.352 |
NTG | 0.133 | 0.035 | 0.925 | 0.385 | 0.333 | 0.049 | 0.041 | 0.213 | 0.094 | 0.168 |
Variable . | Central versus paracentral . | Central versus nasal . | Central versus arcuate 1 . | Central versus arcuate 2 . | Nasal versus paracentral . | Nasal versus arcuate 1 . | Nasal versus arcuate 2 . | Paracentral versus arcuate 1 . | Paracentral versus arcuate 2 . | Arcuate 1 versus arcuate 2 . |
---|---|---|---|---|---|---|---|---|---|---|
Superior hemifield | ||||||||||
PACG | 0.001 | <0.001 | 0.004 | 0.116 | 0.013 | 0.067 | 0.049 | 0.696 | 0.882 | 0.377 |
HTG | 0.236 | <0.001 | 0.724 | 0.960 | 0.031 | 0.001 | 0.002 | 0.235 | 0.217 | 0.533 |
NTG | 0.190 | 0.001 | 0.348 | 0.829 | 0.037 | 0.016 | 0.014 | 0.844 | 0.360 | 0.245 |
Inferior hemifield | ||||||||||
PACG | 0.003 | <0.001 | 0.008 | 0.006 | 0.015 | 0.414 | 0.141 | 0.173 | 0.660 | 0.478 |
HTG | <0.001 | <0.001 | 0.001 | 0.135 | 0.963 | 0.235 | 0.198 | 0.239 | 0.132 | 0.352 |
NTG | 0.133 | 0.035 | 0.925 | 0.385 | 0.333 | 0.049 | 0.041 | 0.213 | 0.094 | 0.168 |
Data are mean ± standard deviation.
Figure 1 shows the region-wise and point-wise comparisons of the matched glaucoma-subtype pairs. The mean TDs of the GHT regions were better in both hemifields of the PACG eyes than in HTG eyes; however, the differences were not statistically significant (all p > 0.05, Fig. 1a). In HTG eyes, the mean TD of the inferior arcuate 2 region was significantly worse than that in NTG eyes (p = 0.035, Fig. 1b). The inferior arcuate 1 and arcuate 2 regions in PACG eyes had significantly worse mean TDs than those in NTG eyes (p = 0.046 and p = 0.007, respectively, Fig. 1c). In the comparison of VF test locations, in HTG eyes, 1 point in the region adjacent to the blind spot had significantly worse TD than the corresponding point in PACG eyes (p = 0.038, Fig. 1d), and 1 point in the inferior arcuate 2 region had significantly worse TD than that in NTG eyes (p = 0.012, Fig. 1d). In NTG eyes, 2 points in the superior arcuate 1 region had significantly worse TDs than the corresponding points in HTG eyes (p = 0.023 and p = 0.020, respectively, Fig. 1e), and 1 point in the superior arcuate 1 region and 1 point in the region adjacent to the blind spot had significantly worse TDs than that in PACG eyes (p = 0.040 and p = 0.029, respectively, Fig. 1e). In PACG eyes, 2 points in the superior arcuate 1 region, 3 points in the superior arcuate 2 region, and 3 points in the region adjacent to the blind spot had significantly worse TDs than those in NTG eyes (ps < 0.05, Fig. 1f).
Region-wise and point-wise comparisons of matched glaucoma subtype pairs. a–c show the comparison of regions. d–f show the comparison of point-wise locations. a and d represent the differences between PACG and HTG; b and e represent the differences between HTG and NTG; and c and f represent the differences between NTG and PACG. The dark shadows with “A,” “H,” and “N” represent significantly worse VF damage in PACG, HTG, and NTG, respectively (p < 0.05).
Region-wise and point-wise comparisons of matched glaucoma subtype pairs. a–c show the comparison of regions. d–f show the comparison of point-wise locations. a and d represent the differences between PACG and HTG; b and e represent the differences between HTG and NTG; and c and f represent the differences between NTG and PACG. The dark shadows with “A,” “H,” and “N” represent significantly worse VF damage in PACG, HTG, and NTG, respectively (p < 0.05).
The relationship between mean TD and PSD among matched patients is shown in Figure 2. In NTG, HTG, and PACG eyes, the PSD worsened as mean TD worsened until the damage was so extensive that the PSD began to decline, which resulted in an inverted-U shape. The best-fit quadratic curves for the three subtypes demonstrated that the PSD values of the NTG eyes were highest, followed by the HTG eyes and then the PACG eyes, for a given mean TD. After controlling for age, sex, mean TD, and (mean TD)2, the NTG eyes had significantly higher PSD values for a given mean TD than did the HTG and PACG eyes (GEE, all p < 0.05).
Scatterplot of pattern standard deviation (PSD) versus mean total deviation (TD) for eyes with PACG, HTG, and NTG. Black circles represent NTG eyes; hollow squares represent HTG eyes; dark-shadow triangles represent PACG eyes. The lines represent the best-fit quadratic functions for each group.
Scatterplot of pattern standard deviation (PSD) versus mean total deviation (TD) for eyes with PACG, HTG, and NTG. Black circles represent NTG eyes; hollow squares represent HTG eyes; dark-shadow triangles represent PACG eyes. The lines represent the best-fit quadratic functions for each group.
Discussion
In this cross-sectional study of propensity score-matched patients with PACG, HTG, and NTG, we observed that the partial arcuate defects were the most common types of VF defects in the PACG eyes, altitudinal (superior hemifield) and partial arcuate (superior hemifield) defects were the two most common types of VF defects in HTG eyes, and arcuate defects (partial arcuate and arcuate) were most common in NTG eyes. Furthermore, the nasal region was more depressed among the regions within almost every hemifield in the three subtypes. In contrast, the peripheral arcuate 2 region of NTG eyes and the central regions of PACG and HTG eyes were relatively less affected. In addition, PACG and HTG eyes tended to have more diffused VF loss than NTG eyes.
In the PACG eyes in the current study, the partial arcuate defect was the most prevalent VF defect pattern in both superior and inferior hemifields. These results are consistent with reports by Atalay and associates [36], who evaluated the patterns of VF defects in 340 patients with PACG and found that in mild or moderate PACG eyes, the partial arcuate defect was the most common VF defect pattern. In the current study, arcuate defects were more prevalent in NTG eyes than in HTG eyes. Kosior-Jarecka et al. [37] evaluated VF defects among 215 NTG patients and found that the arcuate defect was the most common VF defect pattern. They also compared the patterns of VF defects between 170 patients with NTG and 125 patients with HTG, finding that arcuate scotoma was more common in NTG than HTG [38]. Zhou et al. [39] compared the patterns of VF defects between 22 NTG eyes and 39 HTG eyes in Chinese patients. They found that arcuate VF defects were more prevalent in NTG eyes than HTG eyes. These results are consistent with our study.
In the current study, the nasal region had the most significant VF damage among the regions within either hemifield in most glaucoma subtypes. These results agree with several studies on patients with various subtypes of glaucoma. Lau et al. [40] evaluated the patterns of VF defects in 146 PACG eyes by dividing probability plots into three areas (nasal, paracentral, and arcuate areas) in each hemifield. They found that the MD of the nasal area was the worst in each hemifield in the mild and moderate groups. Atalay et al. [36] investigated the characteristics of VF defects in 304 PACG patients. They divided each hemifield into five regions according to GHT sectors and found that the MDs in the nasal region were the worst among the regions in each hemifield. Similarly, Heijl and Lundqvist [41] found that the defect points were most numerous in the upper nasal field in patients with HTG. Among the 139 POAG patients in the study of Yousef and associates [42], the average TD of the nasal region was the worst among the five regions in each hemifield in the early and moderate groups and the superior hemifield of the advanced group. The location of VF defects is related to the glaucomatous structural changes in the optic nerve head. According to the Garway-Heath structure-function map [43], VF defects in the superior and inferior nasal GHT regions are primarily associated with inferotemporal and superotemporal glaucomatous optic nerve head damage, respectively, and glaucomatous damage occurs preferentially in the inferotemporal and superotemporal sectors of the optic nerve head. Tuulonen and Airaksinen [44] demonstrated that both initial glaucomatous optic disk and retinal nerve fiber layer defects were located in the superior and inferior temporal regions. Jonas et al. [45] reported that glaucomatous neuroretinal rim loss was usually most pronounced in the inferotemporal and superotemporal disc. That could be a reason for more significant depression in the nasal region than in other regions within each hemifield.
In the current study, NTG and HTG eyes had higher PSDs than those in PACG eyes, which suggests that the VF defect in POAG eyes is more localized than in PACG eyes at the same level of overall VF damage. This finding is consistent with previous studies on different ethnicities [10, 11, 24, 25]. Furthermore, NTG eyes in the current study had higher PSD than those with HTG for a given mean TD, which agrees with previous reports that NTG shows more localized VF defects than HTG [20, 21]. This finding suggests that primary glaucoma with lower IOP tends to produce more localized field defects than cases with higher pressure.
Our study has various strengths. First, NTG patients in the current report were recruited from a longitudinal, community-based study, which may strengthen the generalizability of our findings. Second, the PACG, HTG, and NTG cohorts were matched using propensity score matching to minimize the differences in baseline characteristics. Third, and most importantly, it is one of the first to directly compare the patterns of VF defects in patients with PACG, HTG, and NTG in China. Although there have been several studies on the characteristics of VF damage in glaucoma patients, relatively fewer studies have been conducted on the patterns of VF defects in PACG, especially the comparisons of PACG with NTG. In this study, we systematically compared the differences in VF defects between PACG and the other two types of glaucoma according to the OHT Study and GHT classification system.
The limitations of this study must also be acknowledged. First, the glaucoma patients enrolled in the study were predominantly patients with early or moderate VF loss; the proportion of patients with advanced VF loss included was relatively small, which may affect our findings. However, propensity score matching analysis based on the MD and VF severity level was performed to obviate that bias. Further, this was a cross-sectional study, whereas a long-term prospective study is needed to determine the progression patterns in the different subtypes of primary glaucoma. Finally, although we excluded patients with vision impairment or blindness, cataract severity may have influenced the observed VF defects pattern.
The results of the present study confirmed that PACG patients have the unique characteristics of VF defects which differentiate it from the other subtypes of primary glaucoma. The significant differences in pattern of VF defects found in this study may have a potential diagnostic value in distinguishing the subtypes of glaucoma. The present findings strengthen the hypothesis that IOP is one of the major factors affecting VF defects that evolve spatially.
Conclusion
In conclusion, our findings show that the VF defect pattern of PACG maybe differs from that of HTG and NTG. The differences in the pathogenic mechanisms of glaucomatous optic neuropathy between PACG and POAG may play a role in this discrepancy in VF defects. Future studies with larger sample sizes are needed.
Statement of Ethics
Approval for the study was granted by the Ethics Committee of the Eye Hospital of Wenzhou Medical University, approval number KYK201312. The study was conducted in accordance with the tenets of the Declaration of Helsinki. Written informed consent was obtained from all participants.
Conflict of Interest Statement
The authors have no conflicts of interest to declare.
Funding Sources
This study was supported by the National Key R&D Program of China (2020YFC2008200), Science and Technology Innovation in Zhejiang Province (2021R52012), training program for leading talents in Universities of Zhejiang Province (2020099), and the Basic Scientific Research Foundation of Wenzhou (Y20190695).
Author Contributions
J.J., Y.L., F.L., and C.Y.: study conception and design. J.J., C.Z., Z.L., Y.T., W.Y., and X.X.: data collection, analysis, and interpretation. J.J.: drafting the manuscript. C.Y., S.Z., and Y.L.: revising the manuscript. All the authors contributed to the article and approved the submitted version.
Data Availability Statement
All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.