@article{471,
  author = {Kuniyoshi Kanai and Meredith Whiteside and Michel Wong and Tammy La and Maryam Nassiri and Sam Lee and Sze Yeung and Adrienne Coulter and Kevin Ruder and Cindi Chen and David Liu and Thomas Abraham and Armin Hinterwirth and Thomas Lietmanb and Thuy Doan and Gerami Seitzman and Seasonal Group},
  title = {Case Series: Unbiased Deep Sequencing Analysis of Acute Infectious Conjunctivitis in an Ambulatory Eye Center in Berkeley, California.},
  abstract = {<p><b>SIGNIFICANCE: </b>Acute infectious conjunctivitis poses significant challenges to eye care providers. It can be highly transmissible and as etiology is often presumed, correct treatment and management can be difficult. This study utilizes unbiased deep sequencing to identify causative pathogens of infectious conjunctivitis, potentially allowing for improved approaches to diagnosis and management.</p>

<p><b>PURPOSES: </b>To identified associated pathogens of acute infectious conjunctivitis in a single ambulatory eye care center.Case ReportsThis study included patients who presented to the University of California Berkeley eye center with signs and symptoms suggestive of infectious conjunctivitis. From December 2021 to July 2021, samples were collected from 7 subjects (ages ranging from 18 to 38 years old). Deep sequencing identified associated pathogens in 5 out of 7 samples, including human adenovirus D (HAdV), Haemophilus influenzae, Chlamydia trachomatis, and human coronavirus 229E (HCoV-229E).</p>

<p><b>CONCLUSIONS: </b>Unbiased deep sequencing identified some unexpected pathogens in subjects with acute infectious conjunctivitis. HAdV was recovered from only one patient in this series. While all samples were obtained during the COVID-19 pandemic, only one case of HCoV-229E and no SARS-CoV-2was identified.</p>
},
  year = {2023},
  journal = {Optom Vis Sci},
  month = {2023 Mar 07},
  issn = {1538-9235},
  doi = {10.1097/OPX.0000000000002010},
  language = {eng},
}