Literature DB >> 27802518

Diagnostic Performance of Peripapillary Retinal Nerve Fiber Layer Thickness for Detection of Glaucoma in an Elderly Population: The ALIENOR Study.

Cedric Schweitzer1, Jean-Francois Korobelnik1, Melanie Le Goff2, Olivier Rahimian3, Florence Malet4, Marie-Benedicte Rougier4, Marie-Noelle Delyfer1, Jean-Francois Dartigues2, Cecile Delcourt2.   

Abstract

PURPOSE: To assess diagnostic accuracy of spectral-domain optical coherence tomography (SD-OCT) to discriminate glaucoma and control subjects in an elderly population.
METHODS: The antioxidants, essential lipids, nutrition and ocular maladies study (ALIENOR: "Antioxydants, Lipides Essentiels, Nutrition et Maladies Oculaires") is a population-based study. From 2009 to 2010, a total of 624 subjects, aged 74 years or older underwent a complete eye examination, including optic disc color photography and SD-OCT examination of the macula and the optic nerve head. Glaucoma diagnosis was made using retinophotography of the optic nerve head and International Society for Epidemiologic and Geographical Ophthalmology criteria. Average and sectorial peripapillary retinal nerve fiber layer thicknesses (RNFLT) were compared between glaucoma and control subjects using area under the receiver operating characteristic curves (AUC), positive and negative likelihood ratios (LR+/LR-), and diagnostic odds ratios (DOR).
RESULTS: A total of 532 subjects had complete data, 492 were classified as controls and 40 were classified as glaucoma. Mean age was 82.1 ± 4.2 years and average RNFLT was significantly different between both groups (controls: 88.7 ± 12.2 μm, glaucoma: 65.4 ± 14.4 μm, P < 0.001). Highest AUC values were observed for average (0.895), temporal-inferior (0.874), and temporal-superior (0.868) RNFLT. Temporal-superior RNFLT had the highest DOR (25.31; LR+, 4.65; LR-, 0.18), followed by average RNFLT (DOR: 24.80; LR+, 6.36; LR-, 0.26). When using the normative database provided by the machine, DOR increased to 31.03 (LR+, 1.75; LR-, 0.06) if at least one parameter was considered abnormal (at P < 0.05).
CONCLUSIONS: Parameters of SD-OCT RNFL may provide valuable information in a screening strategy to improve glaucoma detection in a general population of elderly people.

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Year:  2016        PMID: 27802518     DOI: 10.1167/iovs.16-20104

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  5 in total

1.  Photopic negative response recorded with RETeval system in eyes with optic nerve disorders.

Authors:  Tsutomu Yamashita; Kumiko Kato; Mineo Kondo; Atsushi Miki; Syunsuke Araki; Katsutoshi Goto; Yoshiaki Ieki; Junichi Kiryu
Journal:  Sci Rep       Date:  2022-05-31       Impact factor: 4.996

2.  Machine Learning Models for Diagnosing Glaucoma from Retinal Nerve Fiber Layer Thickness Maps.

Authors:  Peiyu Wang; Jian Shen; Ryuna Chang; Maemae Moloney; Mina Torres; Bruce Burkemper; Xuejuan Jiang; Damien Rodger; Rohit Varma; Grace M Richter
Journal:  Ophthalmol Glaucoma       Date:  2019-08-23

Review 3.  Ocular Manifestations of Alzheimer's and Other Neurodegenerative Diseases: The Prospect of the Eye as a Tool for the Early Diagnosis of Alzheimer's Disease.

Authors:  Pade Colligris; Maria Jesus Perez de Lara; Basilio Colligris; Jesus Pintor
Journal:  J Ophthalmol       Date:  2018-07-30       Impact factor: 1.909

4.  Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software.

Authors:  Yingna Liu; Firas Jassim; Boy Braaf; Ziad Khoueir; Linda Yi-Chieh Poon; Geulah S Ben-David; Georgia Papadogeorgou; Edem Tsikata; Huseyin Simavli; Christian Que; Ramon Lee; Eric Shieh; Benjamin J Vakoc; Brett E Bouma; Johannes F de Boer; Teresa C Chen
Journal:  J Glaucoma       Date:  2019-08       Impact factor: 2.503

5.  Circulating neurohormone imbalances in canine sudden acquired retinal degeneration syndrome and canine pituitary-dependent hypercortisolism.

Authors:  Annie Oh; Melanie L Foster; Katharine F Lunn; Freya M Mowat
Journal:  J Vet Intern Med       Date:  2019-10-29       Impact factor: 3.333

  5 in total

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