Evaluation of factors relating to the development of multiple subepithelial corneal infiltrates of adenoviral keratoconjunctivitis using categorical data analysis program.

IF 2.1 3区 医学 Q2 OPHTHALMOLOGY
Nobuyoshi Kitaichi, Ryosuke Dei, Rikutaro Hinokuma, Ippei Yoshikawa, Miki Hiraoka, Kazuo Nakajima
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Abstract

Purpose: Adenoviral keratoconjunctivitis is the most common infectious disease in ophthalmology. Its clinical forms include epidemic keratoconjunctivitis (EKC) and pharyngoconjunctival fever (PCF). EKC can be complicated by multiple subepithelial infiltrates (MSI) of the cornea, which affect visual outcomes. As at present, artificial intelligence and machine learning are becoming increasingly important not only in the diagnostic imaging field but also in the clinical data science field, we investigated a predictive model for the development of corneal MSI in adenoviral keratoconjunctivitis.

Study design: Retrospective cohort study.

Methods: One hundred and forty cases of adenovirus keratoconjunctivitis diagnosed at Hinokuma Eye Clinic were enrolled. The dependent variable was corneal MSI, and the independent variables were adenovirus genotype, bilaterality, subconjunctival hemorrhage, eyelid swelling, conjunctival edema, conjunctival opacity, pseudomembrane, corneal epithelial findings, preauricular lymphadenopathy, eye discharge, lacrimation, eye pain, foreign body sensation, and itchy eye, which were analyzed by a categorical data analysis program (CATDAP).

Results: For single independent variables, corneal epithelial findings (Akaike information criterion, AIC=-6.46) and type 54 (AIC=-4.30) showed high predictive performance. In the combination of multiple independent variables, Type 56 or Type 37 with corneal epithelial damage also showed high predictive performance.

Conclusion: Predicting the occurrence of corneal MSI has until now been considered difficult. When a patient with EKC has marginal corneal epithelial or subepithelial opacities at initial presentation, it is presumed that the patient has a relatively high risk of developing MSI. Knowing the prevalent virus type in advance, would prove helpful in the diagnosis.

使用分类数据分析程序评估与腺病毒性角膜结膜炎多发上皮下角膜浸润相关的因素。
目的:腺病毒性角膜结膜炎是眼科最常见的感染性疾病。其临床表现包括流行性角膜结膜炎(EKC)和咽结膜热(PCF)。EKC可并发多个角膜上皮下浸润(MSI),影响视力。目前,人工智能和机器学习不仅在诊断成像领域,而且在临床数据科学领域都变得越来越重要,我们研究了腺病毒性角膜结膜炎角膜MSI发展的预测模型。研究设计:回顾性队列研究。方法:选取140例在Hinokuma眼科诊所确诊的腺病毒性角膜结膜炎患者。因变量为角膜MSI,自变量为腺病毒基因型、双侧性、结膜下出血、眼睑肿胀、结膜水肿、结膜混浊、假膜、角膜上皮表现、耳前淋巴结病变、眼分泌物、流泪、眼痛、异物感、眼痒,通过分类数据分析程序(CATDAP)进行分析。结果:对于单一自变量,角膜上皮结果(Akaike信息标准,AIC=-6.46)和54型(AIC=-4.30)具有较高的预测性能。在多个自变量的组合中,56型或37型角膜上皮损伤也表现出较高的预测性能。结论:预测角膜MSI的发生一直被认为是困难的。当EKC患者最初表现为角膜边缘上皮或上皮下混浊时,可以认为患者发生MSI的风险相对较高。提前了解流行的病毒类型,将有助于诊断。
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来源期刊
CiteScore
4.80
自引率
8.30%
发文量
65
审稿时长
6-12 weeks
期刊介绍: The Japanese Journal of Ophthalmology (JJO) was inaugurated in 1957 as a quarterly journal published in English by the Ophthalmology Department of the University of Tokyo, with the aim of disseminating the achievements of Japanese ophthalmologists worldwide. JJO remains the only Japanese ophthalmology journal published in English. In 1997, the Japanese Ophthalmological Society assumed the responsibility for publishing the Japanese Journal of Ophthalmology as its official English-language publication. Currently the journal is published bimonthly and accepts papers from authors worldwide. JJO has become an international interdisciplinary forum for the publication of basic science and clinical research papers.
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