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Related Experiment Video

Updated: May 2, 2026

Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19

Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19

Published on: May 25, 2022

Diagnosing the severity of dry eye: a clear and practical algorithm.

Christophe Baudouin¹, Pasquale Aragona², Gysbert Van Setten³

¹Quinze-Vingts National Ophthalmology Hospital, Paris, France UPMC University, Paris 6, Vision Institute, INSERM UMRS968, CNRS UMR7210, Paris, France University of Versailles Saint-Quentin en Yvelines, Versailles, France.

The British Journal of Ophthalmology

|March 15, 2014

Summary

Diagnosing severe dry eye disease (DED) is challenging due to inconsistent signs and symptoms. A new algorithm using symptom assessment and corneal staining simplifies severe DED diagnosis for better treatment.

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Area of Science:

Ophthalmology
Ocular Surface Disease

Background:

Dry eye disease (DED) presents multifactorial challenges, leading to inconsistent clinical signs and symptoms, complicating severity assessment.
The lack of a gold-standard model for DED severity impacts treatment decisions and clinical trial evaluations.
Ophthalmologists face daily challenges in managing ocular surface disease, necessitating improved diagnostic approaches.

Framework:

The ODISSEY European Consensus Group developed a consensus-based algorithm for evaluating and diagnosing severe DED.
The algorithm assessed 14 commonly used DED severity criteria.
A core panel identified symptom-based assessment and corneal fluorescein staining as key indicators for severe DED.

Implementation:

The ODISSEY algorithm simplifies severe DED diagnosis by prioritizing symptom assessment and corneal staining.
In cases of sign-symptom discordance, the algorithm recommends further evaluation using additional criteria.
This practical approach aims to standardize the diagnosis of severe DED in clinical and research settings.

Implications:

The proposed algorithm facilitates the diagnosis of severe DED, even with conflicting clinical signs and patient-reported symptoms.
This standardized approach can improve treatment decisions and disease progression monitoring.
The ODISSEY algorithm offers a valuable tool for both clinical practice and the development of new DED therapies.