Validation of an objective measure of dry eye severity

Sezen Karakus, Esen K. Akpek, Devika Agrawal, Robert W. Massof

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Purpose: We evaluated the validity of a single dry eye severity measure estimated using Rasch analysis from a battery of clinical tests and patient symptoms. Methods: This study included 203 dry eye patients and 51 controls. Administered tests included the Ocular Surface Disease Index (OSDI), tear osmolarity, Schirmer’s test, noninvasive break-up time, and ocular surface staining. Each of the 12 OSDI questions and each clinical test was defined to be a separate indicator to estimate a single dry eye severity measure from Rasch analysis. Measures of severity were estimated for each subject (person measures) and measures of sensitivity to severity were estimated for each sign and symptom (indicator measures). Results: The average severity measure for dry eye patients was significantly greater than the average severity measure for controls (0.39 vs. 1.2, P < 0.001). The distribution of indicator measures was well matched to the distribution of person measures. No indicator carried <10% of the total information about dry eye severity carried by all indicators together. However, the most informative indicators were corneal and conjunctival staining. Conclusions: Our study indicated that there is no single “best” dry eye test. Clinical tests and symptoms should be used in combination to estimate a single dry eye severity measure. Translational Relevance: There is no single “gold standard” testing method for dry eye that correlates with the severity of disease. We propose that Rasch analysis can be used to calculate an objective dry eye severity score from a battery of clinical indicators.

Original languageEnglish (US)
Article number26
JournalTranslational Vision Science and Technology
Issue number5
StatePublished - Sep 2018


  • Dry eye
  • Grading
  • Rasch analysis
  • Severity

ASJC Scopus subject areas

  • Biomedical Engineering
  • Ophthalmology


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