Zhao Xinyu, Wu Zhenquan, Liu Yaling, Zhang Honglang, Hu Yarou, Yuan Duo, Luo Xiayuan, Zheng Mianying, Yu Zhen, Ma Dahui, Zhang Guoming
Shenzhen Eye Hospital, Shenzhen Eye Institute, Jinan University, Futian District, 18 Zetian Road, Shenzhen, 518040 China.
EPMA J. 2024 Jul 11;15(3):501-510. doi: 10.1007/s13167-024-00372-6. eCollection 2024 Sep.
Clinical data are essential for developing cloud platforms for intelligent diagnosis and treatment decision of diseases. However, cloud platforms for data sharing and exchange with clinicians are poorly suited. We aim to establish Eyecare-cloud, a platform which provide a novel method for clinical data and medical image sharing, to provide a convenient tool for clinicians.
In this study, we displayed the main functions of Eyecare-cloud that we established. Based on clinical data from the cloud platform, we analyzed the incidence trend of the most common infantile retinal diseases, such as retinopathy of prematurity (ROP), over the past 20 years, as well as the associated risk factors for ROP occurrence. Statistical analyses were performed using GraphPad Prism (V.8.0) and SPSS software (V.26.0).
The Eyecare-cloud offers numerous advantages, including systematic archiving of patient information, one-click export data, simplifying data collection and management, eliminating the need for manual input of clinical information, reducing clinical data migration time, and lowering data management costs significantly. A total of 22,913 premature infants from Eyecare-cloud were included in the data analysis. Based on 20 years of premature infant screening data analysis, we found that the ROP incidence began to slowly decline starting in 2003 but showed a gradual increase trend again in 2016. The incidence of severe ROP remained relatively stable at a low level since 2010. The number of premature infants increased steadily before 2016 but decreased since then. ROP occurrence was significantly associated with male sex, lower gestational age, and lower birth weight ( < 0.001).
Eyecare-cloud provides clinicians and researchers with convenient tools for big data analysis, which helps alleviate clinical workloads and integrate research data. This cloud platform supports the principles of predictive, preventive, and personalized medicine (PPPM/3PM), empowering clinicians and researchers to deliver more precise, proactive, and patient-centered eye care.
临床数据对于开发疾病智能诊断与治疗决策的云平台至关重要。然而,用于与临床医生进行数据共享和交换的云平台却不尽人意。我们旨在建立眼保健云平台,该平台提供一种临床数据和医学图像共享的新方法,为临床医生提供便利工具。
在本研究中,我们展示了所建立的眼保健云平台的主要功能。基于云平台的临床数据,我们分析了过去20年中最常见的婴儿视网膜疾病,如早产儿视网膜病变(ROP)的发病趋势,以及ROP发生的相关危险因素。使用GraphPad Prism(V.8.0)和SPSS软件(V.26.0)进行统计分析。
眼保健云平台具有诸多优势,包括患者信息的系统存档、一键导出数据、简化数据收集和管理、无需手动输入临床信息、减少临床数据迁移时间以及显著降低数据管理成本。数据分析纳入了眼保健云平台的22913名早产儿。基于20年的早产儿筛查数据分析,我们发现ROP发病率自2003年开始缓慢下降,但在2016年又呈逐渐上升趋势。自2010年以来,重度ROP的发病率一直保持在较低水平且相对稳定。2016年前早产儿数量稳步增加,但此后有所下降。ROP的发生与男性性别、较低的胎龄和较低的出生体重显著相关(P<0.001)。
眼保健云平台为临床医生和研究人员提供了方便的大数据分析工具,有助于减轻临床工作量并整合研究数据。这个云平台支持预测、预防和个性化医疗(PPPM/3PM)原则,使临床医生和研究人员能够提供更精确、主动和以患者为中心的眼保健服务。