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Pradeep Y Ramulu, Shwetha Mudalegundi, Aleksandra Mihailovic, Nazlee Zebardast, Rengaraj Venkatesh, Kavitha Srinivasan; Patient features associated with a higher sibling risk of angle closure disease. Invest. Ophthalmol. Vis. Sci. 2022;63(7):4012 – A0354.
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To assess if specific findings gathered during an examination of patients with a known angle closure diagnosis (probands) could better determine the risk of angle closure in the patient’s sibling.
Patients 30 years and older with suspect primary angle closure (PACS) or primary angle closure/primary angle closure glaucoma (PAC/G) seen at the Aravind Eye Hospital in Pondicherry, Tamil Nadu, and a biological sibling above age 30 years, were recruited as ‘probands’ and ‘siblings’ (n=346 pairs). Demographics, ocular history, and an ophthalmic examination with Anterior Segment Optical Coherence Tomography (ASOCT) were obtained. Siblings were classified as having open angles (OA), PACS, or PAC/G per ISGEO criteria. Models were created to analyze the contribution of specific proband factors in predicting sibling angle closure diagnosis.
When predicting (1) any sibling angle closure (PACS or PAC/G ) vs. open angles, (2) sibling PAC/G vs PACS or OA, or (3) PAC/G vs. PACS amongst siblings with angle closure, models incorporating proband ASOCT data outperformed models including proband diagnosis alone or proband diagnosis plus demographic (age/gender) and exam metrics (gonioscopy, optic nerve exam, visual acuity, and intraocular pressure). For example, in the prediction of PAC/G vs. PACS amongst siblings with angle closure, the model using only proband diagnosis had the lowest explained variability (0.64%). Adding proband demographics and ocular exam metrics improved model accuracy to a limited extent (1.99% of variability explained), while adding ASOCT Metrics created a significant improvement (17% of variability explained, p<.0001 vs other models). The model incorporating ASOCT metrics resulted in the lowest Bayesian Information Criterion (101.9 vs. 123.6 for the diagnosis-only model and 119.7 for the diagnosis + demographics + exam metrics model).
Utilizing ASOCT information from angle closure patients can help better predict sibling angle closure status, leading to more efficient and cost-effective screening of family members.
This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.
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