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Combining Structural and Vascular Parameters to Discriminate Among Glaucoma Patients, Glaucoma Suspects, and Healthy Subjects

PURPOSE: Compare the ability of peripapillary and macular structural parameters, vascular parameters, and their integration to discriminate among glaucoma, suspected glaucoma (GS), and healthy controls (HCs). METHODS: In this study, 196 eyes of 119 patients with glaucoma (n = 81), patients with GS (...

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Detalles Bibliográficos
Autores principales: Rabiolo, Alessandro, Fantaguzzi, Federico, Sacconi, Riccardo, Gelormini, Francesco, Borrelli, Enrico, Triolo, Giacinto, Bettin, Paolo, McNaught, Andrew I., Caprioli, Joseph, Querques, Giuseppe, Bandello, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8709930/
https://www.ncbi.nlm.nih.gov/pubmed/34928324
http://dx.doi.org/10.1167/tvst.10.14.20
Descripción
Sumario:PURPOSE: Compare the ability of peripapillary and macular structural parameters, vascular parameters, and their integration to discriminate among glaucoma, suspected glaucoma (GS), and healthy controls (HCs). METHODS: In this study, 196 eyes of 119 patients with glaucoma (n = 81), patients with GS (n = 48), and HCs (n = 67) underwent optical coherence tomography (OCT) and OCT angiography to measure peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell–inner plexiform layer (mGCIPL) thicknesses, radial peripapillary capillary perfusion density (RPC-PD), and macular GCIPL perfusion density (GCIPL-PD). Parameters were integrated regionally with logistic regression and globally with machine learning algorithms. Diagnostic performances were evaluated with area under the receiver operating characteristic (AUROC) curves. RESULTS: Patients with glaucoma had mild to moderate damage (median, −3.3 dB; interquartile range, −6.5 to −1.4). In discriminating between patients with glaucoma and the HCs, pRNFL thickness had higher AUROC curve values than RPC-PD for average (0.87 vs. 0.62; P < 0.001), superior (0.86 vs. 0.54; P < 0.001), inferior (0.90 vs. 0.71; P < 0.001), and temporal (0.65 vs. 0.51; P = 0.02) quadrants. mGCIPL thickness had higher AUROC curve values than GCIPL-PD for average (0.84 vs. 0.68; P < 0.001), superotemporal (0.76 vs. 0.65; P = 0.016), superior (0.72 vs. 0.57; P = 0.004), superonasal (0.70 vs. 0.56; P = 0.01), inferotemporal (0.90 vs. 0.72; P < 0.001), inferior (0.87 vs. 0.69; P < 0.001), and inferonasal (0.78 vs. 0.65, P = 0.012) sectors. All structural multisector indices had higher diagnostic ability than vascular ones (P < 0.001). Combined structural–vascular indices did not outperform structural indices. Similar results were found to discriminate glaucoma from GS. CONCLUSIONS: Combining structural and vascular parameters in a structural–vascular index does not improve diagnostic ability over structural parameters alone. TRANSLATIONAL RELEVANCE: OCT angiography does not add additional benefit to structural OCT in early to moderate glaucoma diagnosis.