To evaluate the implantable collamer lens (ICL)-sizing method using the partial regression coefficient of the implanted ICL size to review the conventional horizontal compression coefficient and match the results of clinical observation.
Purpose
To predict the anterior chamber volume (ACV) after implantable collamer lens (ICL) implantation based on ICL size and parameters of anterior segment optical coherence tomography (AS-OCT).
Design
Retrospective study.
Methods
This study included 222 eyes of 222 patients who underwent ICL implantation at Nagoya Eye Clinic. The patients were divided into two groups: prediction group, for creating the prediction equation (148 eyes, mean age: 32.11 ± 8.04 years), and verification group, for verifying the equation (74 eyes, mean age: 33.03 ± 6.74 years). The angle opening distance (AOD), anterior chamber width (ACW), ACV, anterior chamber depth, lens vault, angle-to-angle distance, angle recess area, and trabecular iris space area were calculated using AS-OCT. A stepwise multiple regression analysis was performed. After the creation of the prediction equation, its accuracy was verified in the verification group.
Results
The ACV, AOD750, ACW, and ICL size were selected as explanatory variables to predict postoperative ACV. Mean predicted (114.2 ± 21.83 mm3) and actual postoperative ACVs (116.1 ± 25.41 mm3) were not significantly different (P = 0.269); absolute error was 10.59 ± 9.13 mm3. In addition, there was high correlation between actual and predictive ACV (adjusted R2 = 0.6996, p < 0.0001). Bland-Altman plot revealed that there was no addition or proportional error between predicted and actual postoperative ACV.
Conclusion
Postoperative ACV was accurately predicted using AS-OCT parameters and ICL size. This prediction equation may be useful for making decisions regarding ICL size.
Purpose:
This study aimed to predict the best-corrected visual acuity (BCVA) based on swept-source optical coherence tomography (SS-OCT) parameters in eyes with keratoconus.
Methods:
We retrospectively reviewed 135 eyes of 135 patients with keratoconus (mean age: 31.9 ± 12.4 years). The average keratometry value and BCVA (logarithm of the minimal angle of resolution [Snellen]) were 48.68 ± 5.44 diopter and 0.20 ± 0.36 (20/25), respectively. Eleven parameters were calculated using SS-OCT. Apart from the corneal height and elevation, all the other parameters were calculated from both anterior and posterior corneal OCT data. The patients were divided into 2 groups, 1 for creating the prediction equation (prediction group, 86 eyes) and another for verifying the equation (verification group, 49 eyes). In the former, individual correlations between the BCVA and SS-OCT parameters were analyzed. A stepwise multiple regression analysis was performed with the BCVA as a dependent variable and SS-OCT parameters as independent variables. After its creation, the accuracy of the prediction equation was verified in the verification group.
Results:
All the parameters, except for age and total corneal cylinder, showed statistically significant correlations with BCVA (P < 0.0001). Using the stepwise multiple regression analysis, we selected 2 explanatory variables: root mean square of anterior corneal elevation (standardized regression coefficient: 1.221; P < 0.0001) and total coma aberration (standardized regression coefficient: −0.575; P = 0.001; adjusted R2 = 0.546). The prediction was correct in 84.6% of the eyes within ±1 line of Snellen BCVA.
Conclusions:
Using the equation we derived from SS-OCT parameters is a promising method to predict visual function in patients with keratoconus.
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