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C. D. Coe, K. S. Bower, D. S. Ryan, R. A. Sack, P. Pavel Iserovich, M. A. Shatos, D. A. Dartt; Predicting Post-Operative Dry Eye: Multivariate Analysis of Clinical Findings, Tear Proteins, and Goblet Cells. Invest. Ophthalmol. Vis. Sci. 2010;51(13):3364.
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To examine the significance of subjective symptoms, the clinical examination, conjunctival goblet cells, and inflammatory tear proteins and cytokines in predicting post-operative dry eye in refractive surgery patients.
A prospective, non-randomized, multicenter study comparing the effect of LASIK and PRK on the clinical findings of cochet-bonnet aesthesiometry, tear break up time (TBUT), rose Bengal staining (RB), videokeratoscopy surface indices, percent of filled goblet cells (GC), 16 cytokines, 7 matrix metalloproteinases, 2 matrix metalloproteinases inhibitors, and subjective sxs of dry eye quantified using the McMonnies questionnaire. Discriminant analysis was conducted at 1 week (1W), 1 month (1M), and 3 months (3M) to determine if significant differences existed across the predictor variables of two groups: subjects with and without postoperative dry eye.
Seventy-two eyes underwent either PRK(n=39) or intralase LASIK (n=33). At one week post-op, only MMP10 (Wilks’ lambda=0.461) and IL1α(Wilks’ lambda=0.302) were significant predictor variables. At one month, percent filled of goblet cells (WL=.791), Rose Bengal Staining (WL=0.617), and age (WL=0.533) were different across the two groups. At 3M, McMonnies questionnaire (WL=0.724), Rose Bengal staining (WL=0.565), Schirmer’s with anesthesia (WL=0.478), and age (WL=0.413) were significantly different across the two groups. The level of tear proteins were not significantly different across the two groups at either 1M or 3M and at no time point did videokeratoscopy surface indices distinguish between the dry eye group and non-dry eye group.
In the immediate post-operative period, there are changes in both the magnitude of tear proteins and goblet cells that contribute to dry eye. Beginning at 1M, the clinical exam and patient demographics are the best predictors of post-operative dry eye
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