Joelle A Hallak1, Sapna Tibrewal, Sandeep Jain. 1. *Corneal Neurobiology Laboratory, Department of Ophthalmology and Visual Sciences, College of Medicine, University of Illinois at Chicago, Chicago, IL; and †Quantitative Scientific Solutions, LLC, Arlington, Virginia.
Abstract
PURPOSE: To measure depressive symptoms in patients with dry eye disease (DED) and controls using the Beck Depression Inventory (BDI) and to determine the association between depressive and DED symptoms. METHODS: Fifty-three patients with DED and 41 controls were recruited to the study. DED symptoms were assessed using the Symptom Burden Tool and Ocular Surface Disease Index tool. Depressive symptoms were assessed using the BDI. Regression diagnostics were performed to detect outliers. Linear statistical models and polynomial regression were used to determine the relationship between depressive symptoms and DED symptoms. An independent t test was performed to determine differences in BDI scores between cases and controls. Scatter plots were generated and linear regression was used to estimate the association between scores. Logistic regression was used for the DED dichotomous outcome and depression status as exposure. RESULTS: Regression models revealed that the association is linear more than quadratic or cubic. After adjusting for age, sex, race, and psychiatric medication, the regression coefficient between DED symptoms and depressive symptoms among DED cases was 1.22 (95% confidence interval, 0.27-2.18). DED symptom scores and depression scores were statistically significantly different between DED cases and controls. Adjusted logistic regression revealed an odds ratio of 2.79 (95% confidence interval, 0.96-8.12). CONCLUSIONS: This study provides further evidence regarding the association between DED and depression and their symptoms. Prospective studies are needed to understand the mechanisms underlying the association between symptoms of depression and symptoms of DED.
PURPOSE: To measure depressive symptoms in patients with dry eye disease (DED) and controls using the Beck Depression Inventory (BDI) and to determine the association between depressive and DED symptoms. METHODS: Fifty-three patients with DED and 41 controls were recruited to the study. DED symptoms were assessed using the Symptom Burden Tool and Ocular Surface Disease Index tool. Depressive symptoms were assessed using the BDI. Regression diagnostics were performed to detect outliers. Linear statistical models and polynomial regression were used to determine the relationship between depressive symptoms and DED symptoms. An independent t test was performed to determine differences in BDI scores between cases and controls. Scatter plots were generated and linear regression was used to estimate the association between scores. Logistic regression was used for the DED dichotomous outcome and depression status as exposure. RESULTS: Regression models revealed that the association is linear more than quadratic or cubic. After adjusting for age, sex, race, and psychiatric medication, the regression coefficient between DED symptoms and depressive symptoms among DED cases was 1.22 (95% confidence interval, 0.27-2.18). DED symptom scores and depression scores were statistically significantly different between DED cases and controls. Adjusted logistic regression revealed an odds ratio of 2.79 (95% confidence interval, 0.96-8.12). CONCLUSIONS: This study provides further evidence regarding the association between DED and depression and their symptoms. Prospective studies are needed to understand the mechanisms underlying the association between symptoms of depression and symptoms of DED.
Authors: Johanna E Vriezekolk; Rinie Geenen; André Hartkamp; Guido L R Godaert; Hendrika Bootsma; Aike A Kruize; Johannes W J Bijlsma; Ronald H W M Derksen Journal: J Rheumatol Date: 2005-12 Impact factor: 4.666
Authors: Roni M Shtein; Daniel E Harper; Vincent Pallazola; Steven E Harte; Munira Hussain; Alan Sugar; David A Williams; Daniel J Clauw Journal: Trans Am Ophthalmol Soc Date: 2016-08