Signs and Symptoms of Dry Eye in Keratoconus Patients: A Pilot Study

Purpose: To compare signs and symptoms of dry eye in keratoconus (KC) patients versus healthy subjects. Methods: A total of 15 KC patients (KC group, n = 15 eyes) and 16 healthy subjects (control group, 16 eyes) were enrolled in this study. The Schirmer I test with no anesthetic, tear break-up time (TBUT), corneal staining characteristics, and ocular surface disease index (OSDI) scores were evaluated for both groups. Impression cytology, combined with/scanning laser confocal microscopy (LCM), was performed to evaluate goblet cell density, mucin cloud height (MCH), and goblet cell layer thickness (CLT). Finally, tear concentrations of di-adenosine tetraphosphate (Ap4A) were assessed. Results were statistically analyzed using Shapiro–Wilk and non-parametric Wilcoxon rank sum tests. Statistical significance was set at p < 0.05. Results: KC patients had lower tear volumes and greater corneal staining than did healthy subjects (p < 0.05). OSDI scores were 44.96 ± 8.65 and 17.78 ± 6.50 for the KC and control groups, respectively (p < 0.05). We found no statistically significant differences in TBUT between groups. Impression cytology revealed lower goblet cell densities in KC group patients versus control group subjects (84.88 ± 32.98 and 128.88 ± 50.60 cells/mm,2 respectively, p < 0.05). There was a statistically significant reduction in MCH and CLT in KC group patients compared with control group subjects. Ap4A tear concentrations were higher in KC group patients than in control group subjects (2.56 ± 1.10 and 0.15 ± 0.12 µM, respectively, p < 0.05). Conclusions: The parameters evaluated in this study indicate that KC patients suffer greater symptoms of dry eye and greater tear instability, primarily due to the decreased mucin production in their tears, than do healthy patients with no KC.

The role of parametric assumptions in adaptive Bayesian estimation.

Variants of adaptive Bayesian procedures for estimating the 5% point on a psychometric function were studied by simulation. Bias and standard error were the criteria to evaluate performance. The results indicated a superiority of (a) uniform priors, (b) model likelihood functions that are odd symmetric about threshold and that have parameter values larger than their counterparts in the psychometric function, (c) stimulus placement at the prior mean, and (d) estimates defined as the posterior mean. Unbiasedness arises in only 10 trials, and 20 trials ensure constant standard errors. The standard error of the estimates equals 0.617 times the inverse of the square root of the number of trials. Other variants yielded bias and larger standard errors.