Suppr超能文献

用于在新患者群体中检测亚临床圆锥角膜的指标验证。

Validation of metrics for the detection of subclinical keratoconus in a new patient collective.

机构信息

From the Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany.

From the Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany.

出版信息

J Cataract Refract Surg. 2014 Feb;40(2):259-68. doi: 10.1016/j.jcrs.2013.07.044. Epub 2013 Dec 18.

Abstract

PURPOSE

To validate the discriminative ability of wavefront- and pachymetry-based corneal topographic metrics to detect subclinical keratoconus in a new patient collective.

SETTING

Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany.

DESIGN

Retrospective cross-sectional study.

METHODS

Normal fellow eyes with early keratoconus and preoperative eyes with an uneventful follow-up without signs of iatrogenic keratectasia 12 months after laser in situ keratoconus were included. Zernike coefficients from the anterior and posterior surfaces and corneal thickness spatial profiles and corresponding discriminant functions were assessed for their usefulness to discriminate between eyes with subclinical keratoconus and normal eyes using receiver-operating-characteristic (ROC) curve analysis. Discriminant functions were obtained from a previous study and constructed de novo from the present collective.

RESULTS

The anterior C(1,-1) and C(3,-1) coefficients had the highest area under the ROC curve (both 0.87). The anterior 5th-order root mean square (RMS) was the RMS value with the maximum area under the ROC curve (0.90). The discriminant function with input from anterior and posterior Zernike coefficients (DAP) and DAP including pachymetry data (DAPT) performed best (area under ROC curve 0.864 and 0.857, respectively). Applying cutoff values from a previous study resulted in a minimal drop in accuracy (0.0% to 1.3%). The construction of discriminant functions from the present dataset resulted in a gain in accuracy of between 3.5% and 9.6%, with DAPT reaching the maximum area under the ROC curve of 0.956.

CONCLUSION

Validation in a new and larger patient collective proved the usefulness of metrics based on corneal wavefront and pachymetry for the detection of subclinical keratoconus.

FINANCIAL DISCLOSURE

No author has a financial or proprietary interest in any material or method mentioned.

摘要

目的

在新的患者群体中验证基于波前和角膜厚度的角膜地形学指标来检测亚临床圆锥角膜的鉴别能力。

设置

德国法兰克福歌德大学眼科。

设计

回顾性横断面研究。

方法

纳入正常对侧眼伴早期圆锥角膜和术前眼伴无并发症随访,激光原位角膜磨镶术后 12 个月无医源性角膜扩张迹象。评估前后面的泽尼克系数和角膜厚度空间分布以及相应的判别函数,以使用接收器操作特性(ROC)曲线分析来区分亚临床圆锥角膜眼和正常眼。判别函数来自先前的研究,并从本研究中重新构建。

结果

前 C(1,-1)和 C(3,-1)系数具有最高的 ROC 曲线下面积(均为 0.87)。前 5 阶均方根(RMS)是 ROC 曲线下面积最大的 RMS 值(0.90)。基于前后面泽尼克系数的判别函数(DAP)和包括角膜厚度数据的 DAP(DAPT)的性能最佳(ROC 曲线下面积分别为 0.864 和 0.857)。应用先前研究的截断值会导致准确性略有下降(0.0%至 1.3%)。从本数据集构建判别函数可使准确性提高 3.5%至 9.6%,其中 DAPT 达到 ROC 曲线下面积的最大值 0.956。

结论

在新的更大患者群体中的验证证明了基于角膜波前和角膜厚度的指标用于检测亚临床圆锥角膜的有效性。

财务披露

没有作者在任何材料或方法上有财务或专有利益。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验