Statistical analysis was conducted in the R statistical analysis package (R Foundation for Statistical Computing, Vienna, Austria). Intraobserver repeatability for GALILEI G2 was assessed with the 3D-printed mount in place using the six measurements taken in the unaccommodated state for each participant.
22,23 Repeatability was quantified using the within-subject standard deviation (S
w), precision, test-retest variability (repeatability), coefficient of variation (CoV), and intraclass correlation (ICC). Precision was calculated as 1.96 × S
w, because for 95% of observations, the difference between a subject's measurement and the true value would be expected to be less than 1.96 × S
w. Test-retest variability, or repeatability, was calculated as 2.77 × S
w. The within-subject CoV was calculated as the S
w divided by the overall mean and expressed as a percentage. The ICC is defined as the ratio of the between-subjects' variance to the sum of the combined within-subjects and between-subjects' variance. The ICC values range from 0 to 1, with 1 indicating perfect agreement.
The Bland-Altman method was used to assess the effect of the 3D-printed mount and ocular elevation on GALILEI G2 measurements, compared to measurements in the same eye of the same single participant.
24 For the Bland-Altman analysis, the same participant was measured five times in each of the following measurement conditions: neutral eye position with no device modifications, neutral eye position with 3D-printed mount in place, and elevated eye (to view study target) with 3D-printed mount in place. Significant differences were identified with a one-sample
t-test with the test value equal to zero.
22,24 The 95% limits of agreement (mean difference ± 1.96 × standard deviation) were used to define the confidence interval within which most differences between measurements from the pairwise comparisons will occur.
22,24
Arithmetic means of each data point were calculated for the six scans in the accommodated and unaccommodated conditions, for each parameter, for each participant. The difference between the accommodated and unaccommodated conditions were calculated by subtracting the accommodated value from the unaccommodated value. These data were interpolated onto a 100 × 100 matrix to generate individual contour plots (
Fig. 5A).
25 Statistically significant changes were detected with paired
t-tests by comparing the series of six scans in the accommodated and unaccommodated conditions. The
P values of the tests were extracted and interpolated onto a 100 × 100 matrix to create statistical significance contour plots (
Fig. 5B).
25 The cornea was split into 12 sectors to statistically assess the distribution of changes. These 12 sectors comprised of 3 zones (Central [
r ≤ 1.5 mm], Paracentral [1.5 >
r ≥ 3.5 mm], and Peripheral [3.5 >
r ≥ 5 mm]) in each of four quadrants (Upper, Lower, Nasal [left], and Temporal [right]). The percentage of data points with a
P value <0.05 were calculated in each sector and compared with proportion tests to assess statistical differences between sectors.
26 Mean corneal changes across the entire study population were assessed by taking the arithmetic mean change at each data point. Statistically significant mean changes were identified with one-sample
t-tests with the test value equal to zero.
Multiple regression analysis was used to determine if corneal biomechanical parameters predict corneal changes occurring during accommodation. Total corneal changes were estimated using the sum of squared displacement for each data point from the plane
x +
y +
z = 0. Biomechanical parameters for regression were extracted from CorVis ST. To avoid including highly collinear variables in the analysis, variables with the largest mean absolute correlation from pairs of variables with correlation coefficients >0.7 were removed from the analysis. The remaining variables that had been previously shown to be associated with corneal stiffness were included in the analysis with the additional variables of ethnicity, age, sex, and percentage anterior chamber depth (ACD) change.
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