One hundred fifty healthy volunteers from the hospital staff with normal eyes on slit lamp examination and no history of previous ocular diseases, trauma, or surgery contributed 228 eyes that were evaluated in a prospective single-center study. Informed consent, according to the tenets of the Declaration of Helsinki, was obtained from each volunteer.
All measurements were taken by the same examiner in the following order: biometry, pachymetry, GAT, and DCT. First, axial length, corneal curvature, and anterior chamber depth were measured with an optical biometry system (IOL Master; Carl Zeiss AG, Feldbach, Switzerland). Second, CCT was measured with an ultrasonic pachymeter (model SP-2000; Tomey Corp., Cambridge, MA). The pachymeter probe was placed on the center of the cornea over an undilated pupil and the mean of three readings within a range of ±5 μm was calculated for each eye. Third, GAT was performed on a slit lamp (Haag-Streit, Köniz, Switzerland) with a tonometer calibrated according to the manufacturer’s guidelines. Before each reading, the measuring drum was reset to approximately 2 mm Hg, and the mean of three consecutive readings was recorded.
Fourth, DCT was performed using a technically identical prototype of the model launched in November 2003 (Pascal dynamic contour tonometer; Swiss Microtechnology AG, Port, Switzerland; slit-lamp–mounted, self-calibrating, 1 g appositional force, 100 Hz sampling rate, 7 mm tip diameter, 1.2 mm pressure sensor diameter). As DCT provides a digital readout of the IOP on a liquid crystal display (LCD), prior knowledge of the GAT result would not influence the result and made it unnecessary to randomize the order of IOP measurements (always GAT followed by DCT) or to mask the investigator. However, for the study of the intra- and interobserver variability, all four investigators were fully masked to all results. For this part of the study, three GAT readings followed by three DCT readings were taken in eight participants by each investigator, resulting in 192 measurements. The delay between readings by different investigators was kept as short as possible (<30 seconds).
Data are presented as medians and 25th to 75th percentile limits. Comparisons in pressure measurements were performed using the nonparametric Wilcoxon signed ranks test to account for the skewed and nonsymmetrical distribution of data points. P < 0.05 was considered significant. To correct for related data, when two eyes of the same subject were entered into analysis, we performed clustered analyses, using the subject identifier as the cluster variable. We fitted models in which DCT and GAT, respectively, acted as the dependent variable. To adjust for the skewed data distribution, DCT and GAT were transformed into their logarithms. Corneal thickness, corneal curvature, astigmatism, anterior chamber depth, and axial length were entered as continuous independent variables. First each independent variable was assessed in a univariate analysis. Then all independent variables were fitted into two multivariable models (one for GAT and one DCT).
To study the variability between the different investigators and the two measurement readings, we performed analyses of variance (ANOVAs). We used the variance components procedure to estimate the contribution of an independent variable (observer, test, subjects, observer subject interaction, and residual error) to the variance of the dependent variable (pressure measurement). Based on the variance components, we calculated the intraclass correlation coefficients (ICC) for GAT and DCT using the variance component of the subjects in the numerator and the sum of all variances in the denominator. To test for significant differences between the ICCs, we calculated the sum of variance of all noise components for the two tests (all variance components except the subjects variance component). The division of the two noise components was bootstrapped and tested using a one-sample t-test.
To assess the intra- and interobserver variability of DCT and GAT, we calculated the interobserver variability for each of the two tests as the sum of the variance components of the investigator and the investigator–subject interaction. The variance component of the residual error was used as the intraobserver variability.
Statistical analysis was performed on computer (SPSS statistical software, ver. 10; SPSS Inc., Chicago, IL).