Distribution of ocular biometric parameters and optimal model of anterior chamber depth regression in 28,709 adult cataract patients in China using swept-source optical biometry.

Background: The purpose of this study was to evaluate the ocular biometric parameters in adult cataract patients from China and create an anterior chamber depth (ACD) regression model.

Methods: The ocular biometric records of 28,709 right eyes of cataract surgery candidates who were treated at Aier Eye Hospitals in nine cities from 2018 to 2019 were retrospectively analyzed. All measurements were taken with IOLMaster 700. We included patients who were at least 40 years old and were diagnosed with cataract.

Results: The mean age of the patients was 68.6 ± 11.0 years. The mean values recorded were as follows: axial length (AL), 24.17 ± 2.47 mm; mean keratometry (Km) value, 44.26 ± 1.70 D; corneal astigmatism (CA), 1.06 ± 0.96 D; ACD, 3.02 ± 0.45 mm; lens thickness (LT), 4.52 ± 0.45 mm; central corneal thickness (CCT), 0.534 ± 0.04 mm; and white to white (WTW) corneal diameter, 11.64 ± 0.46 mm. ACD correlated positively with AL (Spearman coefficient, 0.544) and WTW (0.300), but negatively with LT (-0.660) and age (-0.285) (all P < 0.01). In the multivariate regression analysis of ACD, which included LT, AL, WTW, sex, Km, CCT, and age, there was a reasonable prediction with adjusted R = 0.641.

Conclusions: Cataract patients with longer AL and wider WTW have deeper ACD. With increasing age and lens thickening ACD becomes shallower. Based on the standardized coefficients of ACD multivariate regression analysis from the study, LT is the main factor that affects ACD, and is followed by AL.