Objective Parameters Associated with Subjective Symptom Severity in Dry Eye Syndrome Patients.
10.3341/jkos.2017.58.3.259
- Author:
Min Hwan SEO
1
;
Joo Youn SHIN
;
Do Hyung LEE
;
Jin Hyoung KIM
Author Information
1. Department of Ophthalmology, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea. jhk0924@hanmail.net
- Publication Type:Original Article
- Keywords:
Dry eye syndrome;
Meibomian gland dysfunction;
Ocular surface disease index
- MeSH:
Blinking;
Conjunctiva;
Dry Eye Syndromes*;
Eyelids;
Humans;
Life Style;
Linear Models;
Logistic Models;
Meibomian Glands;
Odds Ratio;
Risk Factors;
Sleep Initiation and Maintenance Disorders;
Tears
- From:Journal of the Korean Ophthalmological Society
2017;58(3):259-267
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: To evaluate the correlation between the ocular surface disease index (OSDI score) and objectively quantifiable parameters in dry eye syndrome patients, and to assess environmental and lifestyle risk factors in severe OSDI patients. METHODS: The present study was retrograde and included 30 patients (30 eyes) diagnosed with dry eye syndrome at Ilsan Paik Hospital for the first time. Shirmer's test, corneal staining, and conjunctiva staining were assessed, and tear break-up time, meibum quality, and OSDI questionnaires were performed. We measured the lipid layer thickness in tear meniscus and counted the amount of partial eyelid blinking using Lipiview®. Moreover, we modified images of the lower lid meibography and calculated the percentage of meibomian glands outside the lower tarsal plate using the ImageJ® software. We analyzed the Pearson's correlation and performed a multiple linear regression analysis between the test values and OSDI. In addition, logistic regression analysis was used to determine the risk factors of the severe OSDI group, such as insomnia, level of computer use, and exposure to fully air-conditioned indoor environments. RESULTS: According to the Pearson's correlation analysis, quality of the meibum showed the highest statistically significant correlation with OSDI, followed by age, conjunctiva staining score, counts of partial blinking, and corneal staining score. The multiple linear regression analysis revealed that quality of the meibum and age were statistically significant factors affecting the OSDI score. Based on the logistic regression analysis, using a computer for more than 4 hours at a time exhibited a 7.43-fold odds ratio for severe OSDI (p-value = 0.029). CONCLUSIONS: Meibomian gland dysfunction and age should be considered to be important factors, especially in treating dry eye syndrome patients who complain severely. Moreover, we should also consider environmental factors such as long-term computer use for the treatment of dry eye syndrome patients with severe symptoms.
