Big Data-Based Epidemiology of Uveitis and Related Intraocular Inflammation.
Big Data-Based Epidemiology of Uveitis and Related Intraocular Inflammation.
复制标题
基于大数据的葡萄膜炎及相关眼内炎症的流行病学。
DOI：
10.1097/apo.0000000000000364
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发表时间：
2021
影响因子：
4.4
通讯作者：
Brian C. Toy
中科院分区：
文献类型：
--
作者：
Mashal Akhter;Brian C. Toy
摘要
大型行政健康数据库、全国范围的调查以及电子病历的广泛采用，导致眼部炎症性疾病的健康相关数据越来越多，使我们能够阐明葡萄膜炎的真实流行病学，并检查患者和系统层面的葡萄膜炎特定病因及其并发症发生率的风险因素。尽管使用大数据库有很多优点，但临床医生在得出结论并推断到一般人群时也必须意识到一些限制，例如缺乏命名和编码的标准化。随着更强大的数据集的可用性增加，临床医生和科学家应该准备好利用这些工具来提高我们对疾病病理生理学的理解以及我们管理眼部炎症性疾病患者的能力。
ABSTRACT
Large administrative health databases, nationwide surveys, and the widespread adoption of electronic medical records have led to an increasing availability of health-related data on ocular inflammatory disease, allowing us to elucidate the real-world epidemiology of uveitis and examine patient and systems-level risk factors for the incidence of specific etiologies of uveitis and its complications. Despite the many advantages to using big databases, there are also limitations that clinicians must be aware of when making conclusions and extrapolating to the general population, such as the lack of standardization of nomenclature and coding. As the availability of even more robust datasets increases, clinicians and scientists should be prepared to leverage these tools to improve our understanding of disease pathophysiology and our ability to manage patients with ocular inflammatory disease.