SARS-CoV-2 in Conjunctiva and Tears and Ocular Symptoms of Patients with COVID-19

Author:

Rodríguez-Ares Teresa,Lamas-Francis DavidORCID,Treviño Mercedes,Navarro Daniel,Cea María,López-Valladares María Jesús,Martínez Laura,Gude FranciscoORCID,Touriño Rosario

Abstract

This study investigates the presence of SARS-CoV-2 in conjunctival secretions and tears and evaluates ocular symptoms in a group of patients with COVID-19. We included 56 hospitalized patients with COVID-19 in this cross-sectional cohort study. Conjunctival secretions and tears were collected using flocked swabs and Schirmer strips for SARS-CoV-2 reverse-transcriptase polymerase chain reaction (RT-PCR). Assessment of ocular surface manifestations included an OSDI (Ocular Surface Disease Index) questionnaire. Patients had been admitted to hospital for an average of 2.4 days (range 0–7) and had shown general symptoms for an average of 7.1 days (range 1–20) prior to ocular testing. Four (7.1%) of 56 conjunctival swabs and four (4%) of 112 Schirmer strips were positive for SARS-CoV-2. The mean E-gene cycle threshold values (Ct values) were 31.2 (SD 5.0) in conjunctival swabs and 32.9 (SD 2.7) in left eye Schirmer strips. Overall, 17 (30%) patients presented ocular symptoms. No association was found between positive ocular samples and ocular symptoms. This study shows that SARS-CoV-2 can be detected on the conjunctiva and tears of patients with COVID-19. Contact with the ocular surface may transmit the virus and preventive measures should be taken in this direction.

Publisher

MDPI AG

Subject

Cell Biology,Cognitive Neuroscience,Sensory Systems,Optometry,Ophthalmology

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3