| Literature DB >> 32138781 |
Xiaoli Xing1, Liangyu Huang2, Fang Tian2, Yan Zhang2, Yingjuan Lv2, Wei Liu2, Aihua Liu2.
Abstract
BACKGROUND: To compare the anterior biometrics in eyes with secondary acute angle closure induced by occult lens subluxation (ASAC-LS), misdiagnosed as acute primary angle closure (APAC) at the first visit with APAC, chronic primary angle closure glaucoma (CPACG), and cataract.Entities:
Keywords: Acute angle-closure; Anterior chamber depth; Axial length; Biometry; Lens subluxation; Lens thickness
Mesh:
Year: 2020 PMID: 32138781 PMCID: PMC7059282 DOI: 10.1186/s12886-020-01355-7
Source DB: PubMed Journal: BMC Ophthalmol ISSN: 1471-2415 Impact factor: 2.209
Biometry parameters in groups
| Parameters | Pvalue | ||||
|---|---|---|---|---|---|
| ASAC-LS | APAC | CPACG | Cataract | ||
| Gender | 0.025* | ||||
| Male | 11 | 12 | 16 | 20 | |
| Female | 7 | 44 | 38 | 36 | |
| Age (y) | 64.47 ± 7.82 | 66.05 ± 8.41 | 67.44 ± 7.97 | 67.61 ± 11.14 | 0.540 |
| AL (mm) | 23.23 ± 0.68 | 22.42 ± 0.77 | 22.56 ± 0.92 | 23.47 ± 1.30 | 0.000* |
| CCT (μm) | 569.00 ± 91.66 | 552.98 ± 40.29 | 527.57 ± 39.24 | 536.46 ± 37.29 | 0.002* |
| AD (mm) | 1.25 ± 0.35 | 1.64 ± 0.26 | 1.77 ± 0.22 | 2.59 ± 0.39 | 0.000* |
| ACD (mm) | 2.49 ± 0.56 | 2.21 ± 0.26 | 2.33 ± 0.32 | 3.13 ± 0.39 | 0.000* |
| LT (mm) | 5.13 ± 0.41 | 4.97 ± 0.30 | 4.92 ± 0.30 | 4.48 ± 0.41 | 0.000* |
| LP | 4.39 ± 0.32 | 4.69 ± 0.21 | 4.79 ± 0.33 | 5.37 ± 0.27 | 0.0008 |
| RLP | 1.89 ± 0.14 | 2.09 ± 0.09 | 2.12 ± 0.16 | 2.29 ± 0.12 | 0.000* |
| CLP | 3.82 ± 0.33 | 4.13 ± 0.21 | 4.23 ± 0.19 | 4.83 ± 0.28 | 0.000 |
*:P < 0.05
Comparison of biometry parameters in different groups
| Mean difference ( | ||||||
|---|---|---|---|---|---|---|
| APAC vs ASAC-LS | CATA vs ASAC-LS | CPACG vs ASAC-LS | CATA vs APAC | APAC vs CPACG | CATA vs CPACG | |
| AL | −0.80827(0.002) ** | 0.23638(0.902) | −0.66763(0.016) * | 1.044643(0.000) ** | −0.140642(0.945) | 0.904001(0.000) ** |
| CCT | 16.01786(0.212) | 32.53571(0.012) * | −41.42593(0.001) ** | −16.517857(0.147) | 25.408069(0.007) ** | 8.890212(0.780) |
| ACD | 0.388887 (0.001) ** | 1.31764(0.000) ** | 0.51779(0.000) ** | 0.928750(0.000) ** | −0.128902(0.127) | 0.799848(0.000)** |
| AD | 0.398697 (0.002)** | 1.346555 (0.000) ** | 0.52756(0.000) ** | 0.947857(0.000) ** | −0.128862(0.035) * | 0.818995(0.000) ** |
| LT | −0.17181(0.526) | −0.65895(0.000)** | − 0.22342(0.256) | −0.487143(0.000) ** | 0.051614(0.936) | −0.435529(0.000)** |
| LP | 0.305305 (0.009) ** | 0.98816(0.000) ** | 0.40608(0.001) ** | 0.682857(0.000) ** | −0.100774(0.323) | 0.582083(0.000) ** |
| CLP | 0.31512(0.009)** | 1.01708(0.000)** | 0.41585(0.001)** | 0.701964(0.000) ** | −0.100734(0.058) | 0.601230(0.000) ** |
| RLP | 0.20384(0.000)** | 0.4047594(0.000)** | 0.23708(0.000)** | 0.200923(0.000) ** | −0.033242(0.678) | 0.167681(0.000) ** |
Fig. 1ROC curves plotting sensitivity against one-specificity adjusted for gender. In our study, RLP is the best value to distiguish APAC from ASAC-LS
Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and cutoff value in ASAC-LS and APAC subjects
| VALUE | AUC | 95%CI | Cut off value |
|---|---|---|---|
| AD | 0.928 | 0.845–1.001 | 2.16 |
| ACD | 0.933 | 0.867–0.999 | 2.67 |
| LP | 0.896 | 0.813–0.979 | 4.87 |
| RLP | 0.936 | 0.879–0.993 | 2.27 |
| CLP | 0.906 | 0.831–0.981 | 4.37 |
| AL | 0.370 | 0.214–0.527 | 24.19 |
| CCT | 0.470 | 0.274–0.665 | 603 |
| LT | 0.340 | 0.156–0.524 | 5.23 |
(LP = ACD + 1/2LT, RLP = [ACD + 1/2LT] /AL × 10, CLP = AD+ 1/2LT. P < 0.05 was considered statistically significant)