目的：分析新型冠状病毒肺炎疫情期间实时面对面线上教学(以“腾讯会议”教学为例)在医学教育中的利弊及其与医学生眼表疾病的相关性，为改进线上教育方案、预防干眼提供依据。方法：以中南大学湘雅医学院本科学生为研究对象，采用横断面研究的方法，使用问卷星收集数据，研究实时面对面线上教学的效果及对眼表疾病的影响。结果：共收集到131份有效数据，绝大多数学生(84.73%)认为实时面对面线上教学是有效的，96.18%的学生认为实时面对面线上教学达到或部分达到了学习的目的，但是实时面对面线上教学的师生互动与课堂氛围有待加强，另外网络设备问题也是实时面对面线上教学需要面对的问题。同时，调查显示实时面对面线上教学参与学生的干眼患病率达66.41%，家庭所在地、家庭人均月收入、使用设备、是否全程专注听课与干眼患病率之间无相关性。结论：新型冠状病毒疫情期间实时面对面线上教学在医学教育中是有效的，但是师生互动不足、课堂氛围不够活跃、网络连接不稳定是其主要问题。此外，实时面对面线上教学会增加干眼的发病率，需要提高护眼意识，积极预防。
Objective: To analyze the advantages and disadvantages of real-time face-to-face online teaching (taking “Tencent Conference” teaching as an example) in medical education and its correlation with ocular surface diseases during the COVID-19 pandemic, and to provide basis for improving online education programs and preventing dry eye. Methods: The undergraduate students of Xiangya School of Medicine of Central South University were selected as the research objects. The method of cross-sectional study was used to collect data using questionnaires to study the effect of real-time face-to-face online teaching and its impact on ocular surface diseases. Results: A total of 131 valid data were collected. Among them, the vast majority of students (84.73%) think real time face to face online teaching is effective, and 96.18% of the students believe that real-time face-to-face online teaching at least partly achieved the purpose of learning. However, the interaction between teachers and students and the classroom atmosphere of real-time face-to-face online teaching needs to be strengthened. In addition, network equipment is also a problem that real-time face-to-face online teaching needs to face. Meanwhile, the survey showed that the prevalence rate of dry eye among the students who participated in real-time face-to-face online teaching reached 66.41%, and there was no correlation between the incidence rate of dry eye and the location of family, the per capita monthly income of family, the equipment, and whether they paid full attention to the lectures. Conclusion: Real-time face-to-face online teaching is effective in medical education during COVID-19, but the main problems are insufficient teacher-student interaction, inactive classroom atmosphere and unstable Internet connection. In addition, real-time face-to face online teaching will increase the incidence of dry eye, so it is necessary to improve the awareness of eye protection and actively prevent it.
猫抓病(cat scratch disease，CSD)是由巴尔通体引起的一种人畜共患病。该病不仅有多种全身表现，还可能出现各种危害视力的眼部并发症。随着家庭饲养宠物不断增多，CSD发病率逐年上升，眼科医生应重视此病。CSD的临床表现多种多样，容易误诊，与猫等宠物接触的病史、高滴度的血清免疫球蛋白G抗体是诊断的关键，聚合酶链反应也有助于诊断。由于CSD通常是免疫能力强的个体的自限性感染，因此通常不需要抗生素治疗。然而，当免疫力低或感染重时，多西环素是最常用的抗生素。
Cat scratch disease (CSD) is a zoonotic disease caused by Bartonella, which not only has a variety of systemic manifestations, but also may have various ocular complications that endanger vision. With the increasing number of pets kept at home, its incidence shows an increasing trend year by year. Therefore, ophthalmologists should pay attention to this disease. The clinical manifestations of CSD are various, which easily lead to misdiagnosis. The medical history of contact with cats and other pets and serum immunoglobulin G antibody with high titer are the key to diagnosis, and polymerase chain reaction is also helpful to diagnosis. Because CSD is usually a self-limiting infection of individuals with strong immune ability, antibiotic treatment is usually not required. However, when immunity is low or infection is severe, doxycycline is the most commonly used antibiotic.
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.
