目的：探讨大气污染物NO<sub>2</sub>水平与干眼患病的相关性。方法：选取2014年1月至2018年1月共计75 279例干眼患者的临床资料，进行资料汇总。空气质量和天气数据来自西安市气象局2014—2018年的每日环境空气质量数据。分析中包括的环境空气污染物NO<sub>2</sub>。所有数据均按小时收集。计算每个变量的每日平均值，并计算本研究中使用的每周平均值。本研究中患者均自愿参加，并经南昌大学第一附属医院医学研究伦理委员会批准。结果：干眼的门诊就诊次数与NO<sub>2</sub>水平显著相关。本研究发现不同年龄段的人受到不同的参数变化影响，环境中NO<sub>2</sub>的浓度对于全年龄段的人患干眼有显著相关性，对性别无选择性，男女均会因为NO2在环境中的不同水平而患干眼。较高水平的环境NO<sub>2</sub>会增加门诊患者干眼的概率。我们通过对患者人数的累计与环境中NO<sub>2</sub>浓度进行相关性分析，发现其有显著相关性，因此环境空气污染和天气变化可能导致干眼的恶化。结论：大气污染物NO2与干眼患病有显著相关性。
Objective: To investigate the correlation between NO2 levels in air pollutants and dry eye. Methods: The clinical data of 75 279 patients with dry eye from January 2014 to January 2018 were selected and summarized. The air quality and weather data were from the daily ambient air quality data of Xi’an Meteorological Bureau from 2014 to 2018. Environmental air pollutants NO2 was included in the analysis. All data were collected on an hourly basis. We calculated the daily average for each variable and then calculated the weekly average used in this study.All patients in this study volunteered to participate. , and this study was approved by the Medical Research Ethics Committee of the First Affiliated Hospital of Nanchang University. Results: We found that the number of outpatient visits for dry eye was significantly correlated with NO2 levels. Our study found that people of different ages were affected by different parameter changes. The concentration of NO2 in the environment was significantly correlated with dry eyes in all age groups, and is not selective for gender. Both men and women could develop dry eyes due to different levels of NO2 in the environment. Our results showed that higher levels of environmental NO2 increased the chances of dry eyes in outpatients. By analyzing the correlation between the cumulative number of patients and the NO2 concentration in the environment, we found that the correlation was significant.Therefore, ambient air pollution and weather changes may lead to the deterioration of dry eye. Conclusion: There is a significant correlation between atmospheric pollutant NO2 and dry eye disease.
近年来人工智能(artificial intelligence，AI)技术在医学领域的应用发展迅猛，尤其在眼科领域，成果显著，极大地提高了相关影像数据的诊断效率，推动了该领域研究的进展。然而，大多数AI的应用都集中于成人眼病，在婴幼儿眼病方向的研究较少。究其原因，可能是婴幼儿眼部影像数据采集配合度低，部分影像设备应用受限，且相关领域专业眼科医生数量匮乏。然而，婴幼儿期是视觉发育最重要的阶段，也是出生缺陷早期筛防诊治的重灾区，对患儿的视觉发展具有长远且重要的影响，亟需AI相关产品提高婴幼儿眼病筛查效率，缓解医疗资源不足的现状。本文将对近年AI在婴幼儿眼病领域的研究应用现状、进展及存在的相关问题进行综述。
In recent years, the application of artificial intelligence (AI) in medicine, especially in ophthalmology, has developed rapidly with remarkable results. This has greatly improved the diagnostic efficiency of relevant imaging data and promoted further research in this field. However, most applications of AI are focused on adult eye diseases, and few studies have addressed infantile eye diseases. This may be because of the non-cooperative nature of infants, the limited availability of imaging equipment in infants, and the lack of pediatric ophthalmologists. Infancy is the most important stage of vision development. Disturbance during this period have a profound and lasting influence on vision development. Hence, early screening, diagnosis, and treatment of birth defects is important. AI-related products, which improves the efficacy of infant eye disease screening, are urgently needed. This paper reviews the current status, progress, and existing problems of recent research related to application of AI in infantile eye diseases.
