June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Automated Determination of Conjunctival Redness in Dry Eye Syndrome
Author Affiliations & Notes
  • David Finis
    Ophthalmology, Universitatsaugenklinik Dusseldorf, Dusseldorf, Germany
  • Maria Borrelli
    Ophthalmology, Universitatsaugenklinik Dusseldorf, Dusseldorf, Germany
  • Stefan Schrader
    Ophthalmology, Universitatsaugenklinik Dusseldorf, Dusseldorf, Germany
  • Gerd Geerling
    Ophthalmology, Universitatsaugenklinik Dusseldorf, Dusseldorf, Germany
  • Footnotes
    Commercial Relationships David Finis, Oculus (R); Maria Borrelli, None; Stefan Schrader, None; Gerd Geerling, Oculus (R)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 4444. doi:
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      David Finis, Maria Borrelli, Stefan Schrader, Gerd Geerling; Automated Determination of Conjunctival Redness in Dry Eye Syndrome. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):4444.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: To evaluate the diagnostic potential of a standardized automated measurement of conjunctival redness in patients with dry eye syndrome.

Methods: 717 eyes of 365 patients with dry eye syndrome were included in this retrospective analysis. Conjunctival redness was determined with the Oculus Keratograph 5M ®, which automatically generates a value (R-score) between 0.0 (absolutely no redness) and 4.0 (maximal redness). A correlation analysis between this parameter and subjective symptoms, tear film lipid layer thickness (LLT), Meibomian gland assessment, meibography, tear film break-up time (BUT), tear osmolarity, corneal and conjunctival staining (Oxford scale), Lid margin parallel conjunctival folds (LIPCOFs), Schirmer test values and tear meniscus height was performed.

Results: The results showed significant positive correlations between conjunctival redness and age (r = 0.487, p < 0.0001), lipid layer thickness (r = 0.254, p < 0.0001), tear meniscus height (r = 0.198, p < 0.0001), meibography (r = 0.244, p < 0.0001), corneal and conjunctival staining (r = 0.286 p < 0.0001) and LIPCOFs (r = 0.297, p < 0.0001). An inverse correlation was found between conjunctival redness and BUT (r = -0.173, p < 0.0001). For the other investigated parameters no correlation was found.

Conclusions: Standardized automated determination of conjunctival redness seems to be a promising new diagnostic parameter in dry eye syndrome. However aging appears to be an important confounding factor. In the future prospective studies are needed to further evaluate the value of this new parameter as a screening as well as a monitoring tool for dry eye syndrome.

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