American journal of ophthalmology · 2015
Staging of keratoconus indices regarding tomography, topography, and biomechanical measurements.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Goebels Susanne, Eppig Timo, Wagenpfeil Stefan, Cayless Alan, Seitz Berthold, Langenbucher Achim
Аннотация
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.
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.