Predicting the Keratoconus Disease Severity Based on Pachymetric Progression Indices Measured by Pentacam

Reza Soltani Moghadam, Ebrahim Azaripour, M. Akbari
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Abstract

Background Keratoconus (KCN) is a bilateral, progressive, and non-inflammatory disorder in the cornea, which results in thinning and protrusion of the cornea. Objective This study aims to determine the effectiveness of using pachymetric progression indices (PPIs) in grading the severity of KCN disease. Methods In this study, 76 patients with different stages of KCN were enrolled. The severity of KCN was graded according to maximum keratometry, cornea thickness, and spherical equivalent. The PPIs measured by Pentacam and the demographic characteristics were recorded and their correlation with the severity of KCN was assessed. Results In terms of KCN severity, 18% of patients were at grade 1, 31% at grade 2, 42% at grade 3, and 7% at grade 4. The power of PPIs in predicting KCN grade 4, grade 3 and grade 2 based on the area under the curve ranged from 0.722 to 0.993. Conclusion The PPIs (Minimum, Maximum, Average) can predict the severity of KCN disease with good sensitivity and specificity.
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Pentacam测定角膜厚度进展指数预测圆锥角膜疾病严重程度
圆锥角膜(KCN)是一种双侧、进行性、非炎症性的角膜疾病,导致角膜变薄和突出。目的本研究旨在确定使用厚测进展指数(PPIs)对KCN疾病严重程度分级的有效性。方法选取76例不同分期KCN患者作为研究对象。KCN的严重程度根据最大角膜厚度、角膜厚度和球面等效度进行分级。记录Pentacam测量的ppi和人口学特征,并评估其与KCN严重程度的相关性。结果就KCN严重程度而言,18%的患者为1级,31%为2级,42%为3级,7%为4级。ppi以曲线下面积预测KCN 4级、3级和2级的能力范围为0.722 ~ 0.993。结论PPIs (Minimum, Maximum, Average)可预测KCN疾病的严重程度,具有良好的敏感性和特异性。
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