Evaluation of Intermediate Visual Outcomes in Eyes Implanted with Bilateral Advanced Monofocal Intraocular Lens Targeting for Mini-Monovision and Its Association with Age and Corneal Asphericity

Purpose

To assess the visual outcomes in patients bilaterally implanted with novel Clareon® intraocular lens when targeting mini monovision post-operatively.

Setting

The study was conducted at Laxmi Eye Institute; it is a tertiary care eye institution in Panvel, India.

Design

This is an investigator initiated, prospective, single-centre longitudinal study of 45 patients to assess the visual outcomes in patients who were implanted with Clareon ® IOL bilaterally.

Methods

Patients with corneal astigmatism of ≤0.75 D who underwent bilateral cataract surgery with pseudophakic mini-monovision and implanted with novel Clareon® intraocular lens were included. Patients having post op manifest refraction >±0.25 D in the dominant eye and <-0.5 D or >-0.75 D in the non-dominant eye were excluded. The main study outcomes were assessed at 1 and 3 months; it included uncorrected visual acuities assessment, defocus curve, and patient reported spectacle use.

Results

The mean (SD) binocular distance corrected intermediate visual acuity at 3 months was 0.22 (0.09) LogMAR. At 3 months, 54% of patients enjoyed 0.4 LogMAR or better BUCNVA. The defocus curve showed good distance and intermediate visual acuity with >0.2 LogMAR vision from +0.50 D to -1.50 D. We found a positive correlation between the Q value of the dominant eye and the BCIVA at 3 months postoperatively, however it was not statistically significant. The Q value was more negative when the intermediate vision was closer to 0 LogMAR. Post operatively, at 3 months, 95% patients did not need glasses for distance and intermediate vision and 73% of patients were comfortable for intermediate vision without glasses all the time.

Conclusion

Mini-monovision with Clareon® monofocal IOL implantation can offer overall satisfactory vision for far and intermediate distances with minimal need for use of spectacles for near vision.

Training data size and predication errors in the use of machine-learning assisted intraocular lens power calculation

This retrospective study examined the effect of the size of training data on the accuracy of machine learning-assisted SRK/T power calculation. Clinical records of 4800 eyes of 4800 Japanese patients with intraocular lenses (IOLs) were reviewed. A support vector regressor (SVR) was used for refining the SRK/T formula, and dataset sizes for training and evaluation were reduced from full to 1/64. The prediction errors from the postoperative refractions were calculated, and the proportion within ± 0.25 D, ± 0.50 D, and ± 1.00 D of errors were compared with those using full data. The influence of the difference in A-constant was also evaluated. Prediction errors within ± 0.50 D in the use of full data were obtained with the dataset of ≥ 150 eyes (P = 0.016), whereas the datasets of ≥ 300 eyes were required for the error within ± 0.25 D (P < 0.030). The prediction errors did not alter with the A-constant values among IOLs with open-loop haptics, except for IOLs with plated haptics. In conclusion, the accuracy of SVR-assisted SRK/T could be achieved with the training dataset of ≥ 150 eyes for the Japanese population, and the calculation was versatile for any open-looped IOLs.

Limits of the precision in refractive results after cataract surgery

BACKGROUND AND OBJECTIVE

In order to improve refractive results in cataract surgery with an intraocular lens implant, it is important to know the sources of error as well as the limit of this process. Therefore, the objective of the present work is to approximate the theoretical limit in the precision in the refractive result after cataract surgery with the currently available means and to assess the impact of different sources of error in this process.

MATERIALS AND METHODS

We conducted a search of the literature to determine the variability provided by each component of the process. Based on the Barrett Universal-II formula, we performed an error propagation analysis. The theoretical limit was defined as the situation in which the refractive result is only affected by the variability in the parameters introduced in the formula, the tolerance of the intraocular lens and the subjective refraction.

RESULTS

The main contributors to the error were (1) intraoperative and postoperative variability variables not considered by the formulas (49.33%), (2) postoperative subjective refraction (38.29%), (3) mean keratometry (5.98%) and (4) the variability in the labelling of the power of the intraocular lens (5.09%). The theoretical limit obtained for the intraocular lens calculation with the means available today was 91.9% of the eyes between ±0.50D.

CONCLUSIONS

We found a theoretical limit for the intraocular lens calculation of 91.9% of the eyes between ±0.50D. Approaching the precision limit described in the study requires the use of optical biometrics and state-of-the-art formulas, a reproducible surgical technique, and the compensation of systematic errors by adjusting constants.

Conditional Process Analysis for Effective Lens Position According to Preoperative Axial Length

PURPOSE

To predict the effective lens position (ELP) using conditional process analysis according to preoperative axial length.

SETTING

Yeouido St. Mary hospital.

DESIGN

A retrospective case series.

METHODS

This study included 621 eyes from 621 patients who underwent conventional cataract surgery at Yeouido St. Mary Hospital. Preoperative axial length (AL), mean corneal power (K), and anterior chamber depth (ACD) were measured by partial coherence interferometry. AL was used as an independent variable for the prediction of ELP, and 621 eyes were classified into four groups according to AL. Using conditional process analysis, we developed 24 structural equation models, with ACD and K acting as mediator, moderator or not included as variables, and investigated the model that best predicted ELP.

RESULTS

When AL was 23.0 mm or shorter, the predictability for ELP was highest when ACD and K acted as moderating variables (R2 = 0.217). When AL was between 23.0 mm and 24.5 mm or longer than 26.0 mm, the predictability was highest when K acted as a mediating variable and ACD acted as a moderating variable (R2 = 0.217 and R2 = 0.401). On the other hand, when AL ranged from 24.5 mm to 26.0 mm, the model with ACD as a mediating variable and K as a moderating variable was the most accurate (R2 = 0.220).

CONCLUSIONS

The optimal structural equation model for ELP prediction in each group varied according to AL. Conditional process analysis can be an alternative to conventional multiple linear regression analysis in ELP prediction.

Accuracy of intraocular lens power calculation formulas in long eyes: a systematic review and meta-analysis

IMPORTANCE

Visual outcome after intraocular lens (IOL) implantation in long eyes is considerably affected by IOL power calculation. Various formulas have been designed to achieve an accurate IOL power prediction. However, controversy about the accuracy remains.

BACKGROUND

To evaluate the accuracy of IOL power calculation formulas in long eyes.

DESIGN

Meta-analysis.

PARTICIPANTS

Patients with ocular axial length (AL) over 24.5 mm.

METHODS

A comprehensive search in PubMed, EMBASE, Cochrane Data Base of Systematic Reviews and the Cochrane Central Register of Controlled Trials were conducted by September, 2017. The weighted mean differences of mean absolute errors (MAE) and the odds ratio of percentage of eyes within ±0.50D of prediction error among formulas were analysed.

MAIN OUTCOMES MEASURES

Between-group differences of MAE among formulas.

RESULTS

Eleven observational studies, involving 4047 eyes, were enrolled. Six formulas for IOL power calculation were compared: Barrett Universal II, Haigis, Holladay 2, SRK/T, Hoffer Q and Holladay 1. The MAE of Barrett Universal II was statistically lower than that of Holladay 2 (mean difference, MD = -0.04D, P = 0.0002), SRK/T (MD = -0.05D, P < 0.00001), Hoffer Q (MD = -0.07D, P < 0.00001) and Holladay 1 (MD = -0.07D, P < 0.00001). Barrett Universal II yielded significantly higher percentage of eyes within ±0.50D of the prediction error than the other formulas. The heterogeneity was minimized through dividing eyes into two groups by the AL of 26 mm.

CONCLUSIONS AND RELEVANCE

This study demonstrates the superiority of Barrett Universal II over Holladay 2, SRK/T, Hoffer Q and Holladay 1 in predicting IOL power in long eyes.