Glaucoma Characteristics and Influencing Factors during the COVID-19 Pandemic in the Huizhou Region
Table 4
Potential risk factors for the development of AACG in the AACG group compared with the N-AACG group during phase A.
Potential risk factors
AACG group (N = 21)
N-AACG group (N = 69)
χ2/t
Sex, n (%)
6.579
0.010b
Female
17 (33.33)
34 (66.67)
Male
4 (10.26)
35 (89.74)
Age, years (mean ± SD)
65.86 ± 8.63
58.58 ± 17.01
−1.883
0.063a
COVID-19 status, n (%)
18.378
<0.001c
Negative
1 (2.44)
40 (97.56)
Positive
20 (40.82)
29 (59.18)
Glaucoma started after testing positive for COVID-19, n (%)
20.649
<0.001b
No
7 (10.77)
58 (89.23)
Yes
14 (56.00)
11 (44.00)
Adverse behavior, n (%)
—
0.233c
No
20 (22.47)
69 (77.53)
Yes
1 (100.00)
0(0.0)
History of medication use, n (%)
6.988
0.008b
No
9 (15.00)
51 (85.00)
Yes
12 (40.00)
18 (60.00)
Monocular/binocular involvement, n (%)
0.034
0.853b
Monocular
9 (24.32)
28 (75.68)
Binocular
12 (22.64)
41 (77.36)
Non-COVID-19 systemic diseases, n (%)
1.860
0.173b
No
17 (27.42)
45 (72.58)
Yes
4 (14.29)
24 (85.71)
Note. n (%), Number of patients with glaucoma; %: ratio of the patients. SD = standard deviation. An independent-sample t-test (a) for age, Pearson’s chi-square test (b), and Fisher’s exact test (c) for categorical variables were used to test the difference between the AACG and N-AACG groups. AACG, acute angle-closure glaucoma; N-AACG, nonacute angle-closure glaucoma.
