介绍一种评估进展性圆锥角膜的新工具:斯堪的纳维亚圆锥角膜进展应用

Ingemar Gustafsson, O. Neumann, Dimitrios Bizios, A. Ivarsen, J. Hjortdal
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引用次数: 0

摘要

开发Pentacam HR的应用程序,以优化进行性圆锥角膜的诊断准确性。根据Amsler-Krumeich分级,对25例1-2期圆锥角膜患者的一只随机眼进行两次测量,间隔三天。每次由一名审查员进行四次重复测量。根据以下参数:K2和Kmax,以及Belin ABCD进展显示的参数A、B和C,计算进行性圆锥角膜诊断的日间重复性和检出限。作为输入的测量值将自动从Pentacam HR数据库中提取,作为逗号分隔的值。该应用程序是在R编程环境中开发的,提供了一个基于web浏览器的用户界面,以数字和图形两种方式呈现这些参数。应用程序包括诊断进行性圆锥角膜的检出限,这些检出限来自于先前两项关于圆锥角膜受试者日间测量可重复性的研究。检出限基于日间可重复性,根据疾病严重程度分层,允许对单个测量值或四个重复的平均值进行比较。这是第一个使用基于日间可重复性的检测限来评估进展性圆锥角膜的应用。我们相信这种应用将有助于更准确地诊断进行性圆锥角膜。它还有助于诊断和改善临床工作流程,因为所有相关信息都以数字、图形和颜色编码的方式呈现在一个界面中。
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Introducing a new tool for the assessment of progressive keratoconus: the Scandinavian Keratoconus Progression Application
To develop an application for the Pentacam HR for the purpose of optimising the accuracy of the diagnosis of progressive keratoconus. Measurements were performed on one randomised eye in twenty-five subjects with keratoconus Stage 1-2 according to the Amsler-Krumeich classification on two occasions, three days apart. Four replicate measurements were made by a single examiner on each occasion. The inter-day repeatability and detection limits for the diagnosis of progressive keratoconus were calculated for the following parameters: K2 and Kmax, and the parameters A, B and C from the Belin ABCD Progression Display. The measurements used as input are automatically extracted from the Pentacam HR database as comma-separated values. The application, developed in the R programming environment, provides a web browser-based user interface that presents these parameters both numerically and graphically. The application includes detection limits for the diagnosis of progressive keratoconus obtained from two previous studies on the inter-day repeatability of measurements in subjects with keratoconus. The detection limits are based on inter-day repeatability, stratified according to disease severity, allowing the comparison of single measurements or a mean of four replicates. This is the first application to provide an assessment of progressive keratoconus using detection limits based on inter-day repeatability. We believe this application will contribute to the more accurate diagnosis of progressive keratoconus. It also facilitates diagnosis and improves the clinical workflow as all the relevant information is presented numerically, graphically, and colour-coded in one interface.
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