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Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection

Purpose. To thoroughly analyze corneal deformation responses curves obtained by Ocular Response Analyzer (ORA) testing in order to improve subclinical keratoconus detection. Methods. Observational case series of 87 control and 73 subclinical keratoconus eyes. Examination included corneal topography,...

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Autores principales: Galletti, Jonatán D., Ruiseñor Vázquez, Pablo R., Fuentes Bonthoux, Fernando, Pförtner, Tomás, Galletti, Jeremías G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4446487/
https://www.ncbi.nlm.nih.gov/pubmed/26075085
http://dx.doi.org/10.1155/2015/496382
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author Galletti, Jonatán D.
Ruiseñor Vázquez, Pablo R.
Fuentes Bonthoux, Fernando
Pförtner, Tomás
Galletti, Jeremías G.
author_facet Galletti, Jonatán D.
Ruiseñor Vázquez, Pablo R.
Fuentes Bonthoux, Fernando
Pförtner, Tomás
Galletti, Jeremías G.
author_sort Galletti, Jonatán D.
collection PubMed
description Purpose. To thoroughly analyze corneal deformation responses curves obtained by Ocular Response Analyzer (ORA) testing in order to improve subclinical keratoconus detection. Methods. Observational case series of 87 control and 73 subclinical keratoconus eyes. Examination included corneal topography, tomography, and biomechanical testing with ORA. Factor analysis, logistic regression, and receiver operating characteristic curves were used to extract combinations of 45 corneal waveform descriptors. Main outcome measures were corneal-thickness-corrected corneal resistance factor (ccCRF), combinations of corneal descriptors, and their diagnostic performance. Results. Thirty-seven descriptors differed significantly in means between groups, and among them ccCRF afforded the highest individual diagnostic performance. Factor analysis identified first- and second-peak related descriptors as the most variable one. However, conventional biomechanical descriptors corneal resistance factor and hysteresis differed the most between control and keratoconic eyes. A combination of three factors including several corneal descriptors did not show better diagnostic performance than a combination of conventional indices. Conclusion. Multivariate analysis of ORA signals did not surpass simpler models in subclinical keratoconus detection, and there is considerable overlap between normal and ectatic eyes irrespective of the analysis model. Conventional biomechanical indices seem to already provide the best performance when appropriately considered.
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spelling pubmed-44464872015-06-14 Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection Galletti, Jonatán D. Ruiseñor Vázquez, Pablo R. Fuentes Bonthoux, Fernando Pförtner, Tomás Galletti, Jeremías G. J Ophthalmol Research Article Purpose. To thoroughly analyze corneal deformation responses curves obtained by Ocular Response Analyzer (ORA) testing in order to improve subclinical keratoconus detection. Methods. Observational case series of 87 control and 73 subclinical keratoconus eyes. Examination included corneal topography, tomography, and biomechanical testing with ORA. Factor analysis, logistic regression, and receiver operating characteristic curves were used to extract combinations of 45 corneal waveform descriptors. Main outcome measures were corneal-thickness-corrected corneal resistance factor (ccCRF), combinations of corneal descriptors, and their diagnostic performance. Results. Thirty-seven descriptors differed significantly in means between groups, and among them ccCRF afforded the highest individual diagnostic performance. Factor analysis identified first- and second-peak related descriptors as the most variable one. However, conventional biomechanical descriptors corneal resistance factor and hysteresis differed the most between control and keratoconic eyes. A combination of three factors including several corneal descriptors did not show better diagnostic performance than a combination of conventional indices. Conclusion. Multivariate analysis of ORA signals did not surpass simpler models in subclinical keratoconus detection, and there is considerable overlap between normal and ectatic eyes irrespective of the analysis model. Conventional biomechanical indices seem to already provide the best performance when appropriately considered. Hindawi Publishing Corporation 2015 2015-05-14 /pmc/articles/PMC4446487/ /pubmed/26075085 http://dx.doi.org/10.1155/2015/496382 Text en Copyright © 2015 Jonatán D. Galletti et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Galletti, Jonatán D.
Ruiseñor Vázquez, Pablo R.
Fuentes Bonthoux, Fernando
Pförtner, Tomás
Galletti, Jeremías G.
Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection
title Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection
title_full Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection
title_fullStr Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection
title_full_unstemmed Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection
title_short Multivariate Analysis of the Ocular Response Analyzer's Corneal Deformation Response Curve for Early Keratoconus Detection
title_sort multivariate analysis of the ocular response analyzer's corneal deformation response curve for early keratoconus detection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4446487/
https://www.ncbi.nlm.nih.gov/pubmed/26075085
http://dx.doi.org/10.1155/2015/496382
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