ArticleIndian journal of ophthalmology2026
Results of ocular biometry from a population-based study in detecting angle-closure disease in a clinical setting.
Article in Indian journal of ophthalmology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Changes in anterior segment parameters after laser peripheral iridotomy in patients with primary angle closure suspect.Frontiers in medicine · 2026Article
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6 authors.
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Abstract
purposeTo use the Chennai glaucoma study (CGS) dataset to calculate biometric cutoffs to detect primary angle-closure disease (PACD) and assess its accuracy in detecting PACD in a separate clinical subset.
methodsClinical subset, prospective recruitment. Categories - normal, PACD (included primary angle-closure suspect-PACS, primary angle closure - PAC, and primary angle-closure glaucoma-PACG), and primary open-angle glaucoma (POAG). Biometric parameters assessed included axial length (AXL), anterior chamber depth (ACD), lens thickness (LT), lens position, relative lens position, and simple crowding value. Additionally, the CGS dataset biometric parameters were used to determine the optimal cutoff values (CVs) for the detection of PACD. These were applied to the clinical dataset.
resultsA total of 942 eyes (474 patients) - clinical, 1844 eyes (1844 patients) - CGS. Mean age: 55.77+/-9.63 yrs - clinical, 52.04 ± 9.75 yrs - CGS (rural), 53.95 ± 9.57 yrs - CGS (urban). Among all biometric parameters across all datasets, ACD had the highest area under the curve (AUC, 0.86-0.89), accuracy (75.56-82.91%). Assessed the ability of ACD CV determined from CGS to detect PACD in the clinical dataset - highest sensitivity, specificity combination seen with CV from CGS (rural) - ACD ≤ 2.815 mm: sensitivity - 63.59%, specificity - 93.21%. Urban and combined rural and urban (U and C) CGS dataset had a similar ACD CV of ≤ 2.695 mm (44.77% sensitivity, 96.74%specificity). At 10% population prevalence, ACD ≤ 2.695 (U and C) had the highest accuracy (91.54%), followed by CGS (rural) CV-ACD ≤ 2.815 (90.24%). At a prevalence 30% accuracy: 81.15% for the U and C and 84.32% for rural CV.
conclusionACD determined from CGS had an accuracy of 92% and 84% in detecting PACD in a clinical setting at 10% and 30% prevalence, respectively. Use of these parameters to determine PACD may be considered with due caution in resource-constrained areas, along with cataract screening.
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