Abstract

ABSTRACT Clinical relevance This study identifies key signs and symptoms of acute conjunctivitis, that when combined with a point-of-care test, can improve clinician accuracy of diagnosing adenoviral conjunctivitis. Background Adenoviral conjunctivitis is a common ocular infection with the potential for high economic impact due to widespread outbreaks and subsequent furloughs from work and school. In this report, we describe clinical signs and participant-reported symptoms that most accurately identify polymerase chain reaction (PCR)-confirmed adenoviral conjunctivitis. Methods Adults with ‘red eye’ symptoms of four days or less were enrolled. Participants rated 10 ocular symptoms from 0 (not bothersome) to 10 (very bothersome), and indicated the presence or absence of systemic flu-like symptoms. Clinicians determined the presence or absence of swollen lymph nodes and rated the severity of eight ocular signs using a 5-point scale. An immunoassay targeting adenovirus antigen was utilised for the point-of-care test, and conjunctival swab samples were obtained for subsequent adenovirus detection by PCR analyses. Univariate and multivariate logistic regression models were used to identify symptoms and signs associated with PCR-confirmed adenoviral conjunctivitis. The diagnostic accuracy of these clinical findings, and the potential benefit of incorporating point-of-care test results, was assessed by calculating areas under the receiver operating characteristic curves (AUC). Results Clinician-rated bulbar conjunctival redness, participant-rated eyelid swelling and overall ocular discomfort had the best predictive value in the multivariate logistic regression model with an AUC of 0.83. The addition of the point-of-care test results to these three clinical sign/symptom scores improved diagnostic accuracy, increasing the AUC to 0.94. Conclusions Conjunctival redness severity and participant-reported eyelid swelling and overall discomfort, along with adenoviral point-of-care test results, were highly predictive in identifying individuals with PCR-confirmed adenoviral conjunctivitis. Improved diagnostic accuracy by clinicians at the initial presenting visit could prevent unnecessary work furloughs and facilitate earlier treatment decisions.

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