Susanne Goebels1, Timo Eppig2, Stefan Wagenpfeil3, Alan Cayless4, Berthold Seitz5, Achim Langenbucher2. 1. Department of Ophthalmology, Saarland University Medical Center, Homburg/Saar, Germany. Electronic address: susanne.goebels@uks.eu. 2. Experimental Ophthalmology, Saarland University, Homburg/Saar, Germany. 3. Institute for Medical Biometry, Epidemiology and Medical Informatics, Saarland University, Homburg/Saar, Germany. 4. Department of Physical Sciences, Open University, Milton Keynes, United Kingdom. 5. Department of Ophthalmology, Saarland University Medical Center, Homburg/Saar, Germany.
Abstract
PURPOSE: To derive limits of metric keratoconus indices for classification into keratoconus stages. DESIGN: Validity and reliability analysis of diagnostic tools. METHODS: A total of 126 patients from the keratoconus center of Homburg/Saar were evaluated with respect to Amsler criteria, using Pentacam (Keratoconus Index [KI], Topographic Keratoconus Classification [TKC]), Topographic Modeling System (Smolek/Klyce, Klyce/Maeda), and Ocular Response Analyzer (Keratoconus Match Probability [KMP], Keratoconus Match Index [KMI]). Mean value, standard deviation, 90% confidence interval, and the Youden J index for definition of the thresholds were evaluated. RESULTS: For separation of keratoconus stages 0/1/2/3/4 we derived the following optimum thresholds: for KI 1.05/1.15/1.31/1.49 and for KMI 0.77/0.32/-0.08/-0.3. For Smolek/Klyce and Klyce/Maeda high standard deviations and overlapping confidence intervals were found; therefore no discrete thresholds could be defined. Nevertheless, for them we still found a good sensitivity and specificity in discriminating between healthy (stage 0) and keratoconus (stages 2-4) eyes in comparison with the other indices. CONCLUSIONS: We derived thresholds for the metric keratoconus indices KI and KMI, which allow classification of keratoconus stages. These now need to be validated in clinical use. Smolek/Klyce and Klyce/Maeda were not sufficiently sensitive to allow classification into individual stages, but these indices did show a good specificity and sensitivity in discriminating between keratoconus and healthy eyes.
PURPOSE: To derive limits of metric keratoconus indices for classification into keratoconus stages. DESIGN: Validity and reliability analysis of diagnostic tools. METHODS: A total of 126 patients from the keratoconus center of Homburg/Saar were evaluated with respect to Amsler criteria, using Pentacam (Keratoconus Index [KI], Topographic Keratoconus Classification [TKC]), Topographic Modeling System (Smolek/Klyce, Klyce/Maeda), and Ocular Response Analyzer (Keratoconus Match Probability [KMP], Keratoconus Match Index [KMI]). Mean value, standard deviation, 90% confidence interval, and the Youden J index for definition of the thresholds were evaluated. RESULTS: For separation of keratoconus stages 0/1/2/3/4 we derived the following optimum thresholds: for KI 1.05/1.15/1.31/1.49 and for KMI 0.77/0.32/-0.08/-0.3. For Smolek/Klyce and Klyce/Maeda high standard deviations and overlapping confidence intervals were found; therefore no discrete thresholds could be defined. Nevertheless, for them we still found a good sensitivity and specificity in discriminating between healthy (stage 0) and keratoconus (stages 2-4) eyes in comparison with the other indices. CONCLUSIONS: We derived thresholds for the metric keratoconus indices KI and KMI, which allow classification of keratoconus stages. These now need to be validated in clinical use. Smolek/Klyce and Klyce/Maeda were not sufficiently sensitive to allow classification into individual stages, but these indices did show a good specificity and sensitivity in discriminating between keratoconus and healthy eyes.
Authors: Renato Ambrósio; Fernando Faria Correia; Bernardo Lopes; Marcella Q Salomão; Allan Luz; Daniel G Dawson; Ahmed Elsheikh; Riccardo Vinciguerra; Paolo Vinciguerra; Cynthia J Roberts Journal: Open Ophthalmol J Date: 2017-07-31
Authors: Susanne Goebels; Timo Eppig; Stefan Wagenpfeil; Alan Cayless; Berthold Seitz; Achim Langenbucher Journal: Comput Math Methods Med Date: 2017-02-07 Impact factor: 2.238