Secondary Analysis of the Data from the Telemedicine Approaches to Evaluating Acute-phase ROP (e-ROP)

对评估急性期 ROP (e-ROP) 的远程医疗方法数据进行二次分析

• 批准号: 9148235
• 负责人: Gui-shuang Ying
• 金额: $ 22.72万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9148235
• 关键词: Acute; Blindness; Caring; Characteristics; Childhood; Clinical; Data; Data Analyses; Data Set; Detection; Development; Diagnosis; Diagnostic; Disease; Disease Progression; Documentation; Early Diagnosis; Enrollment; Evaluation; Eye; Goals; Gold; Health; Image; Image Analysis; Individual; Infant; Lead; Methods; Monitor; Multicenter Studies; National Eye Institute; Ophthalmic examination and evaluation; Ophthalmologist; Ophthalmoscopy; Paper; Phase; Premature Infant; Productivity; Protocols documentation; Publications; Publishing; Reader; Research; Research Personnel; Resources; Retinal; Retinopathy of Prematurity; Risk; Sample Size; Sensitivity and Specificity; Specificity; Staging; Stratification; System; Telemedicine; Time; Training; United States; Weight Gain; adjudicate; adjudication; base; digital; experience; group support; high risk infant; imaging system; improved; insight; meetings; operation; premature; screening; secondary outcome

 DESCRIPTION (provided by applicant): The proposed project will utilize the comprehensive dataset from the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP), a large-scale multi-center study, sponsored by the National Eye Institute, to evaluate the validity of a telemedicine system to identify infants who have sufficiently severe ROP to require evaluation by an ophthalmologist. The specific aims of this proposal do not include the major goals of the e-ROP Study, which have been accomplished already. Instead, the goals of the proposed project involve additional secondary analyses of the e-ROP data to further evaluate the validity of telemedicine for ROP and to refine the system for image evaluation to optimize accuracy and efficiency. The Specific Aims to achieve these goals are: (1) To describe characteristics of image evaluation findings, including the symmetry of ROP features (stage, zone, and plus disease) between paired eyes of infants, the time of their first detection, and the progression of ROP features over time. (2) To describe the characteristics of eyes that were found to have RW-ROP by image evaluation earlier than by diagnostic exam. (3) To evaluate whether the number of ROP evaluations can be reduced based on the risk stratification using a combination of image evaluation and weight gain assessment at the time of imaging. (4) To evaluate whether a single reader system provides equivalent sensitivity and specificity as a system with two readers and adjudication of discrepancies by a third reader, and to describe the characteristics of images that require adjudication. (5) To calculate the sensitiviy and specificity of image evaluation using latent class analysis that considers the clinical diagnostic examination finding as imperfect. The e-ROP dataset is a unique and valuable resource for accomplishing these Aims. The analyses of the image grading results from 7749 image sets of 1257 infants may lead to the development of more accurate and efficient grading protocol for identifying high risk infants for ROP evaluation by an ophthalmologist. The very large sample size, high quality of the dataset, as well as the rich experience and high productivity of the investigators along with the full support of the e-ROP Collaborative Group, support the feasibility and likelihood of high yield of the proposed project.

 描述（由适用提供）：拟议的项目将利用远程医疗方法中的全面数据集评估急性阶段 - 早产性视网膜病变（E-ROP），这是一项由国家眼中的大规模多中心研究，由国家眼中的大型多中心研究，以评估远程医疗机构的有效性，以评估远程医疗机构的有效性，以便对远程医疗机构进行评估。该提案的具体目的不包括已经完成的电子跑研究的主要目标。取而代之的是，所提出的项目的目标涉及对电子跑数据的其他二级分析，以进一步评估远程医疗对ROP的有效性，并改进系统以进行图像评估以优化准确性和效率。实现这些目标的具体目的是：（1）描述图像评估发现的特征，包括婴儿对的ROP特征（阶段，区域和加上疾病）在婴儿的双眼之间的对称性，第一次检测的时间以及随着时间的推移ROP的发展。 （2）描述与诊断检查相比，发现通过图像评估具有RW-ROP的眼睛的特征。 （3）评估是否可以根据风险分层使用图像评估和成像时的体重增加评估的组合来减少ROP评估的数量。 （4）评估单个阅读器系统是否提供了等效的灵敏度和特异性作为一个系统，并通过两个读者提供了对第三读者的差异的调整，并描述了需要适应的图像的特征。 （5）使用潜在类别分析计算图像评估的感觉VI和特异性，将临床诊断检查发现视为不完美。 E-ROP数据集是完成这些目标的独特且宝贵的资源。图像分级的分析来自7749个1257个婴儿的图像集，可能会导致开发更准确，更有效的分级方案，以识别眼科医生的高风险婴儿进行ROP评估。非常大的样本量，数据集的高质量，以及研究人员的丰富经验和高生产率，以及E-ROP协作小组的全部支持，支持拟议项目的高收益的可行性和可能性。