International Journal of Keratoconus and Ectatic Corneal Diseases

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VOLUME 1 , ISSUE 3 ( September-December, 2012 ) > List of Articles

RESEARCH ARTICLE

Evaluation of Ocular Biomechanical Indices to Distinguish Normal from Keratoconus Eyes

Bernardo Lopes, Allan Luz, Bruno Fontes, Isaac C Ramos, Fernando Correia, Paulo Schor

Citation Information : Lopes B, Luz A, Fontes B, Ramos IC, Correia F, Schor P. Evaluation of Ocular Biomechanical Indices to Distinguish Normal from Keratoconus Eyes. Int J Kerat Ect Cor Dis 2012; 1 (3):145-150.

DOI: 10.5005/jp-journals-10025-1028

Published Online: 01-12-2014

Copyright Statement:  Copyright © 2012; The Author(s).


Abstract

Purpose

To compare and assess the ability of pressure-derived parameters and corneal deformation waveform signal-derived parameters of the ocular response analyzer (ORA) measurement to distinguish between keratoconus and normal eyes, and to develop a combined parameter to optimize the diagnosis of keratoconus.

Materials and methods

One hundred and seventy-seven eyes (177 patients) with keratoconus (group KC) and 205 normal eyes (205 patients; group N) were included. One eye from each subject was randomly selected for analysis. Patients underwent a complete clinical eye examination, corneal topography (Humphrey ATLAS), tomography (Pentacam Oculus) and biomechanical evaluations (ORA Reichert). Differences in the distributions between the groups were assessed using the Mann- Whitney test. The receiver operating characteristic (ROC) curve was used to identify cutoff points that maximized sensitivity and specificity in discriminating keratoconus from normal corneas. Logistic regression was used to identify a combined linear model (Fisher 1.0).

Results

Significant differences in all studied parameters were detected (p < 0.05), except for W2. For the corneal resistance factor (CRF): Area under the ROC curve (AUROC) 89.1%, sensitivity 81.36%, specificity 84.88%. For the p1area: AUROC 91.5%, sensitivity 87.1%, specificity 81.95%. Of the individual parameters, the highest predictive accuracy was for the Fisher 1.0, which represents the combination of all parameters (AUROC 95.5%, sensitivity 88.14%, specificity 93.17%).

Conclusion

Waveform-derived ORA parameters displayed greater accuracy than pressure-derived parameters for identifying keratoconus. Corneal hysteresis (CH) and CRF, a diagnostic linear model that combines different parameters, provided the greatest accuracy for differentiating keratoconus from normal corneas.

How to cite this article

Luz A, Fontes B, Ramos IC, Lopes B, Correia F, Schor P, Ambrósio R. Evaluation of Ocular Biomechanical Indices to Distinguish Normal from Keratoconus Eyes. Int J Kerat Ect Cor Dis 2012;1(3):145-150.


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