Related Experiment Video
Updated: Aug 2, 2025
06:29
Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19
Published on: May 25, 2022
2.4K
Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study
Ken Nagino1,2,3, Takenori Inomata4,5,6,7, Masahiro Nakamura2,3,8
1Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Eye (London, England)
|April 15, 2023
Summary
A dry eye disease (DED) symptom stratification algorithm, previously developed for the general population, was successfully applied to patients visiting ophthalmologists. This stratification helps understand DED heterogeneity and tailor treatments for individual patients.
Area of Science:
- Ophthalmology
- Clinical Research
- Data Science
Background:
- Dry eye disease (DED) presents with heterogeneous symptoms, complicating diagnosis and treatment.
- A symptom-based stratification algorithm for DED was previously established for the general population.
Purpose of the Study:
- To evaluate the feasibility of applying a pre-existing DED symptom stratification algorithm to patients seeking ophthalmological care.
- To identify distinct patient clusters within an ophthalmology setting using the algorithm.
Main Methods:
- Retrospective cross-sectional study of 426 participants at a Japanese university hospital (Dec 2015-Oct 2021).
- Included patients with comprehensive DED examinations and completed the Japanese Ocular Surface Disease Index (J-OSDI).
- DED patients were stratified into seven clusters using the established algorithm; cluster characteristics were compared.
Main Results:
- 291 (68.3%) DED patients were successfully stratified into seven clusters.
- Cluster 1 showed the highest J-OSDI scores and shortest tear film breakup time.
- Stratified cluster J-OSDI scores correlated significantly with a previous study (r=0.991, P<0.001).
Conclusions:
- The established DED symptom stratification algorithm is feasible for patients in an ophthalmology setting.
- Stratification revealed patterns in the variable clinical characteristics of DED.
- Findings support tailored treatment interventions and future smartphone-based data collection for DED management.
