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Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population

PURPOSE: To model prediction of undetected glaucoma in a predominantly white population, based on intraocular pressure (IOP) and subject age. METHODS: In 1992–1997, a population screening for glaucoma was performed at Malmö University Hospital where individuals between 55–79 years of age (n = 46 614...

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Autores principales: Oskarsdottir, Sigridur E., Heijl, Anders, Bengtsson, Boel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465174/
https://www.ncbi.nlm.nih.gov/pubmed/30324772
http://dx.doi.org/10.1111/aos.13941
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author Oskarsdottir, Sigridur E.
Heijl, Anders
Bengtsson, Boel
author_facet Oskarsdottir, Sigridur E.
Heijl, Anders
Bengtsson, Boel
author_sort Oskarsdottir, Sigridur E.
collection PubMed
description PURPOSE: To model prediction of undetected glaucoma in a predominantly white population, based on intraocular pressure (IOP) and subject age. METHODS: In 1992–1997, a population screening for glaucoma was performed at Malmö University Hospital where individuals between 55–79 years of age (n = 46 614) living in Malmö, were invited to a free eye health examination. Recently examined patients were not invited (n = 4117). IOP and age were recorded for all screened subjects. Subjects who screened positive were further examined to establish or reject a glaucoma diagnosis. We performed multiple regression analysis of the combined effect of age and IOP on the likelihood of undetected glaucoma. RESULTS: In all, 32 918 subjects attended the screening (77.5% of invited), 22 218 women and 11 700 men, while 9579 refrained from participation. Glaucoma was diagnosed in 406 subjects. The proportion of subjects with glaucoma increased exponentially with increasing IOP and older age. Still, the majority of subjects with glaucoma (57%) had ≤IOP 21 mmHg. The predicted rate of undetected glaucoma was low, <5%, for subjects with IOP <25 mmHg, but rose rapidly with higher IOP, reaching 81% in the group with IOP >35 mmHg and age 75–79 years. The model fit well to the data (R (2) = 0.97). CONCLUSION: We created a model estimating the combined effect of IOP and age on the likelihood of undetected glaucoma. The model may facilitate case‐finding in European‐derived populations. Despite the important impact of IOP on the risk of glaucoma, a large proportion of subjects with undetected glaucoma had IOP ≤ 21 mmHg.
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spelling pubmed-64651742019-05-21 Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population Oskarsdottir, Sigridur E. Heijl, Anders Bengtsson, Boel Acta Ophthalmol Original Articles PURPOSE: To model prediction of undetected glaucoma in a predominantly white population, based on intraocular pressure (IOP) and subject age. METHODS: In 1992–1997, a population screening for glaucoma was performed at Malmö University Hospital where individuals between 55–79 years of age (n = 46 614) living in Malmö, were invited to a free eye health examination. Recently examined patients were not invited (n = 4117). IOP and age were recorded for all screened subjects. Subjects who screened positive were further examined to establish or reject a glaucoma diagnosis. We performed multiple regression analysis of the combined effect of age and IOP on the likelihood of undetected glaucoma. RESULTS: In all, 32 918 subjects attended the screening (77.5% of invited), 22 218 women and 11 700 men, while 9579 refrained from participation. Glaucoma was diagnosed in 406 subjects. The proportion of subjects with glaucoma increased exponentially with increasing IOP and older age. Still, the majority of subjects with glaucoma (57%) had ≤IOP 21 mmHg. The predicted rate of undetected glaucoma was low, <5%, for subjects with IOP <25 mmHg, but rose rapidly with higher IOP, reaching 81% in the group with IOP >35 mmHg and age 75–79 years. The model fit well to the data (R (2) = 0.97). CONCLUSION: We created a model estimating the combined effect of IOP and age on the likelihood of undetected glaucoma. The model may facilitate case‐finding in European‐derived populations. Despite the important impact of IOP on the risk of glaucoma, a large proportion of subjects with undetected glaucoma had IOP ≤ 21 mmHg. John Wiley and Sons Inc. 2018-10-15 2019-06 /pmc/articles/PMC6465174/ /pubmed/30324772 http://dx.doi.org/10.1111/aos.13941 Text en © 2018 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Oskarsdottir, Sigridur E.
Heijl, Anders
Bengtsson, Boel
Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population
title Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population
title_full Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population
title_fullStr Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population
title_full_unstemmed Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population
title_short Predicting undetected glaucoma according to age and IOP: a prediction model developed from a primarily European‐derived population
title_sort predicting undetected glaucoma according to age and iop: a prediction model developed from a primarily european‐derived population
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465174/
https://www.ncbi.nlm.nih.gov/pubmed/30324772
http://dx.doi.org/10.1111/aos.13941
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