Catalán-López Sara, Cadarso-Suárez Luis, López-Ratón Mónica, Cadarso-Suárez Carmen
Clínica Cadarso, Vigo, Spain.
Biostatistics Unit, Department of Statistics and Operations Research, School of Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain *
Optom Vis Sci. 2018 Jul;95(7):608-615. doi: 10.1097/OPX.0000000000001241.
Before the appearance of evident keratoconus, corneal biomechanical changes may be detectable. Here, these properties are analyzed to detect any difference that could help in the early recognition of keratoconus to allow patients to benefit from early treatments and to avoid refractive procedures in these corneas.
The purpose of this study was to compare corneal biomechanical characteristics as determined by Corvis Scheimpflug Technology tonometry between normal eyes and asymmetric keratoconic eyes.
Retrospective data from normal eyes (n = 100), keratoconic eyes (n = 18), and their topographically normal fellow eyes (n = 18) were analyzed. Differences in the variables among the groups were determined. For the parameters that showed significant differences, the receiver operating characteristic curve and the area under the curve (AUC) were used to assess the diagnostic accuracy of each variable. The optimal cutoff points were determined when comparing normal and fellow eyes. Also, a new linear combination of variables was performed to obtain better discriminative values.
The following variables differed significantly between normal and fellow eyes: length of the flattened cornea in the second applanation, peak distance, curvature radius at highest concavity, and central corneal thickness. When each variable was independently considered, AUCs, sensitivity, and specificity were insufficiently high for good discrimination between the two groups. However, using a linear combination of variables, an optimal cutoff point (0.157) was obtained with an AUC of 0.78, sensitivity of 0.84, and specificity of 0.69.
A best predictive linear combination of corneal biomechanical variables was tested including diameter of the flattened cornea in the second applanation and central corneal thickness. This combination was considered as the best in terms of its prediction capacity, simplicity and clinical application. This formula may be useful in clinical practice to discriminate between normal eyes and incipient keratoconus.
在明显的圆锥角膜出现之前，角膜生物力学变化可能是可检测到的。在此，对这些特性进行分析，以检测有助于早期识别圆锥角膜的任何差异，从而使患者能够从早期治疗中获益，并避免对这些角膜进行屈光手术。
本研究的目的是比较通过Corvis Scheimpflug技术眼压测量法测定的正常眼与不对称圆锥角膜眼的角膜生物力学特征。
分析来自正常眼（n = 100）、圆锥角膜眼（n = 18）及其地形正常的对侧眼（n = 18）的回顾性数据。确定各组间变量的差异。对于显示出显著差异的参数，使用受试者工作特征曲线和曲线下面积（AUC）来评估每个变量的诊断准确性。在比较正常眼和对侧眼时确定最佳截断点。此外，对变量进行新的线性组合以获得更好的判别值。
正常眼和对侧眼之间在以下变量上存在显著差异：第二次压平角膜的长度、峰值距离、最高凹度处的曲率半径以及中央角膜厚度。当单独考虑每个变量时，AUC、敏感性和特异性不足以高到能够很好地区分两组。然而，使用变量的线性组合，获得了最佳截断点（0.157），AUC为0.78，敏感性为0.84，特异性为0.69。
测试了一种最佳预测性角膜生物力学变量线性组合，包括第二次压平角膜的直径和中央角膜厚度。就其预测能力、简单性和临床应用而言，这种组合被认为是最佳的。该公式在临床实践中可能有助于区分正常眼和早期圆锥角膜。
