Predicting bacterial cause in infectious conjunctivitis: cohort study on informativeness of combinations of signs and symptoms

BMJ. 2004 Jul 24;329(7459):206-10. doi: 10.1136/bmj.38128.631319.AE. Epub 2004 Jun 16.

Abstract

Objective: To find an efficient set of diagnostic indicators that are optimally informative in the diagnosis of a bacterial origin of acute infectious conjunctivitis.

Design: Cohort study involving consecutive patients. Results of index tests and reference standard were collected independently from each other.

Setting: 25 Dutch health centres.

Participants: 184 adults presenting with a red eye and either (muco)purulent discharge or glued eyelid(s), not wearing contact lenses.

Main outcome measures: Probability of a positive bacterial culture, given different combinations of index test results; area under receiver operating characteristics curve.

Results: Logistic regression analysis showed optimal diagnostic discrimination for the combination of early morning glued eye(s), itch, and a history of conjunctivitis. The first of these indicators increased the likelihood of a bacterial cause, whereas the other two decreased it. The area under the receiver operating characteristics curve for this combination of symptoms was 0.74 (95% confidence interval 0.63 to 0.80). The overall prevalence of bacterial involvement of 32% could be lowered to 4% or raised to 77%, depending on the pattern of index test results.

Conclusion: A bacterial origin of complaints indicative of acute infectious conjunctivitis can be made much more likely or unlikely by the answers to three simple questions posed during clinical history taking (possibly by telephone). These results may have consequences for more targeted prescription of ocular antibiotics.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Analysis of Variance
  • Cohort Studies
  • Conjunctivitis, Bacterial / diagnosis
  • Conjunctivitis, Bacterial / microbiology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Regression Analysis
  • Streptococcal Infections / diagnosis