Journal List > J Korean Ophthalmol Soc > v.58(3) > 1010714

Seo, Shin, Lee, and Kim: Objective Parameters Associated with Subjective Symptom Severity in Dry Eye Syndrome Patients

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.

Figures and Tables

Figure 1

LipiView® (TearScience Inc., Morrisville, NC, USA) Image. Yellow box indicates partial blinking in both eye detecting light interference reflected from lipid layer in tear meniscus.

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Figure 2

Method of modifying images of the original lower lid meibographs. (A) Original meibography of left eye, captured by LipiView®. (B) Modified image of lower lid from original meibography automatically by LipiView® inset setting. (C) Image of substracted background, manually selected clear margin meibomian gland lesion, and excluded blurred-margin lesion medially and laterally from (B) image. (D) Binary modification of meibomian gland in selected lesion. W hitish lesion indicates meibomian glands.

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Figure 3

Ocular surface disease index (OSDI) score according to Korean dry eye syndrome (DES) guideline grade. Value in white box means OSDI average score of each group. OSDI score was not statistically in increasing trend from group 1 to 4 (p-value=0.057 > 0.05, based on Jonckheere-Terpstra test).

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Table 1

Results of objective parameters of subjects

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Values are presented as mean ± SD unless otherwise indicated.

TBUT = tear break-up time; MG = meibomian gland; LLT = lipid layer thickness; MG area (%) = meibomian gland area/inferior tarsal plate ×100 (%).

Table 2

OSDI severity grades of subjects

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Values are presented as mean ± SD unless otherwise indicated.

OSDI = Ocular Surface Disease Index.

Table 3

Pearson correlation coefficient with OSDI

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p-values were determined by Pearson correlation analysis.

OSDI = Ocular Surface Disease Index; MG area (%) = meibomian gland area/inferior tarsal plate ×100 (%); LLT = lipid layer thickness; TBUT = tear break-up time.

*Statistically significant (p < 0.05).

Table 4

Results of univariate logistic regression analysis of lifestyle and environmental factors

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p-values were determined by univariate logistic regression.

OR = odds ratio; CI = confident interval; Air conditioner use > 6 hr = more than 6 hours of air conditioner use a day; Computer use > 4 hr = more than 4 hours of computer use a day.

*Statistically significant (p < 0.05).

Table 5

Age distribution of subjects of the study

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Notes

This study was presented as a narration at the 115th Annual Meeting of the Korean Ophthalmological Society 2016.

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