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近视防控的六维度评估及防控模式 被引量:17

Six Dimensional Evaluation for Myopia Prevention and Control
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摘要 2017 年爱眼日,中国政府公告近视是华人首位致盲眼病,其依据来自北京、邯郸眼病研究。医学正在进入精准医疗、大数据、人工智能时代,对近视进行多维度、量化、标准化是实现人工智能辅助防控的基础。近视防控的六维度评估即遗传度、屈光度、用眼度、裂变度、病理度、干预度。①遗传度:主要评价学生近视的易感性;②屈光度:主要记录近视发展速度;③用眼度:采用智能穿戴产品监测;④裂变度:指视盘周围萎缩弧的变化程度;⑤病理度:参照Ohno-Matsui视网膜脉络膜萎缩程度分4 级;⑥干预度:其强弱程度参考国际近视干预临床试验的荟萃分析分级。为了预防病理性近视的发生,应该监测盘周萎缩弧的早期变化。从高度近视的眼底长期监测图像可看出盘周萎缩弧 与视网膜脉络膜萎缩的关系。 In 2017, the Chinese government has announced that myopia is the first irreversible blindness in Chinese, and it is based on the eye study in Beijing and Handan. Medical science is entering the era of precision medicine, big data and artificial intelligence. Multi-dimensional, quantitative and standardized measurement of myopia is the basis for the realization of artificial intelligence. The six dimensional evaluation of myopia control is heredity, diopter, increased nearwork, peripapillary atrophy, pathological myopia degree, intervention degree. ①Heredity: mainly evaluate the susceptibility of students to myopia;②Diopter: mainly record the development rate of myopia per year; ③Increased nearwork: using wearable instrument for monitoring; ④Monitoring the change of peripapillary atrophy; ⑤The level of chorioretinal atrophy: refer to Ohno-Matsui's grade; ⑥The level of intervention: it is referenced in the meta-analysis of international myopia intervention clinical trials. In order to prevent of pathological myopia, it should monitor the changes of the peripapillary atrophy in early state. Long-term monitoring of the fundus image from high myopia can see the relationship between the peripapillary atrophy and the chorioretinal atrophy.
作者 徐捷 徐亮 Jie Xu, Liang Xu(Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Lab, Beijing 100005, Chin)
出处 《中华眼视光学与视觉科学杂志》 CAS CSCD 2018年第3期129-132,共4页 Chinese Journal Of Optometry Ophthalmology And Visual Science
基金 北京市医院管理局“青苗”计划专项经费资助(QML20170206)
关键词 近视 防控 人工智能 myopia prevention and control artificial intelligence
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