AIM: To assess the changes in anterior chamber parameters and examine the factors associated with changes in the intraocular pressure(IOP)in individuals who have undergone phacoemulsification surgery.

METHODS: It was a longitudinal analysis of secondary clinical data collected from 105 non-glaucomatous eyes(of 82 patients)undergoing a cataract surgery. We studied the association between anterior chamber parameters, grade of cataract, demographics, and changes in the IOP over a period of 3wk. We also evaluated the association between the pressure-depth(PD)ratio and changes in the IOP during this time.

RESULTS: The mean age [standard deviation(SD)] of the 82 patients was 60.1(7.8)years. The mean SD IOP was 15.06(3.36)mmHg pre-operatively; it increased to 15.75(4.21)mmHg on day one(P=0.20). In the multifactorial models, the mean IOP was -1.715 \〖95% confidence intervals(CI): -2.795, -0.636\〗 mmHg on day 21(±5)compared with the pre-operative values. The anterior chamber depth(ACD), axial length, age, sex, and grade of cataract were not significantly associated with changes in the IOP. Each unit increase in the PD ratio was associated with an increase in the mean IOP by 1.289 mmHg(95% CI: 0.906, 1.671). After adjusting for pre-operative PD ratio, none of the other variables(ACD, axial length, temporal angle)were significantly associated with changes in mean IOP.

CONCLUSION: The PD ratio was the single most important factor associated with the changes in post-operative IOP over 3wk post surgery.

AIM:To assess the anterior corneal astigmatism (ACA)and posterior corneal astigmatism (PCA) patterns across various age groups.We also evaluated the association between magnitudes and axes of the ACA and PCA across these age groups.METHODS:The present study was a cross-sectional analysis of clinical data of 381 eyes.We converted the clinical astigmatic notation to vector notation for analysis of ACA and PCA.We estimated the correlation between magnitude and axes of the ACA and PCA in the whole population and in four age groups (5-19,20-39,40-59,and ≥ 60y).We used random effects linear regression models for estimating the association between the magnitudes of ACA and PCA.RESULTS:The mean of the magnitude of the ACA (3.59D) and the PCA (0.50D) was highest in children (5 to 9y).Overall,the magnitude of the ACA ranged from 0D to 10.0 Diopters (D) and the magnitude of the PCA ranged from 0 to 3.5 D.There was a significant correlation between the ACA and the PCA in the younger age group (r=0.85,P＜0.001).In those 60y or older,the PCA increased by 0.04 units (95％ confidence intervals:0.005,0.07;P=0.03) with each unit increase in the ACA,the increase was the smallest in this age group.CONCLUSION:It will be prudent to measure the both the magnitude and axis of the PCA,particularly in those above 60y rather than rely on rule-of-thumb calculations based on ACA parameters for IOL power calculation.