Accuracy of 8 intraocular lens calculation formulas in relation to anterior chamber depth in patients with normal axial lengths

Gökçe, Sabite Emine; de, Ildamaris Montes; Cooke, David L.; Wang, Li; Koch, Douglas D.; Al-Mohtaseb, Zaina

doi:10.1016/j.jcrs.2018.01.015

Cited by 42 publications

(42 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There are several studies that report the predictability of vergence formulas for eyes with different axial lengths, but high discrepancies are found in the percentage of eyes within ±0.50 D between studies [4, 8–13]. For instance, Shrivastava et al [14] reported no differences between SRK/T and the newer formulas in short eyes, but a meta-analysis reported superiority of the Haigis formula [15].…”

Section: Introductionmentioning

confidence: 99%

New Approach for the Calculation of the Intraocular Lens Power Based on the Fictitious Corneal Refractive Index Estimation

Fernández

Rodríguez‐Vallejo²,

Martínez³

et al. 2019

Journal of Ophthalmology

View full text Add to dashboard Cite

Purpose. To identify the sources of error in predictability beyond the effective lens position and to develop two new thick lens equations. Methods. Retrospective observational case series with 43 eyes. Information related to the actual lens position, corneal radii measured with specular reflection and Scheimpflug-based technologies, and the characteristics of the implanted lenses (radii and thickness) were used for obtaining the fictitious indexes that better predicted the postoperative spherical equivalent (SE) when the real effective lens position (ELP) was known. These fictitious indexes were used to develop two thick lens equations that were compared with the predictability of SRK/T and Barrett Universal II. Results. The SE relative to the intended target was correlated to the difference between real ELP and the value estimated by SRK/T (ΔELP) (r = −0.47, p=0.002), but this only predicted 22% of variability in a linear regression model. The fictitious index for the specular reflection (nk) and Scheimpflug-based devices (nc) were significantly correlated with axial length. Including both indexes fitted to axial length in the prediction model with the ΔELP increased the r-square of the model up to 83% and 39%, respectively. Equations derived from these fictitious indexes reduced the mean SE in comparison to SRK/T and Barrett Universal II. Conclusions. The predictability with the trifocal IOL evaluated is not explained by an error in the ELP. An adjustment fitting the fictitious index with the axial length improves the predictability without false estimations of the ELP.

show abstract

Section: Introductionmentioning

confidence: 99%

New Approach for the Calculation of the Intraocular Lens Power Based on the Fictitious Corneal Refractive Index Estimation

Fernández

Rodríguez‐Vallejo²,

Martínez³

et al. 2019

Journal of Ophthalmology

View full text Add to dashboard Cite

show abstract

“…Zeroing out of the mean error has been proposed in experimental practice, in order to compare the various IOL calculation formulas in retrospective studies, but it could be introduced in clinical practice to improve the IOL power calculation [ 23 , 30 – 32 ]. Further studies on a larger patients’ database are imperative to understand the feasibility of the proposed method for clinical practice.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the criticism received by this protocol, the zeroing of the mean error has been recommended by other study groups too [30][31][32] and it represents a milestone in the realization of valid and accurate studies and the most recently published papers concerning IOL power calculation took it into consideration [25,[33][34][35][36][37][38][39][40].…”

Section: Plos Onementioning

confidence: 99%

An Advanced Lens Measurement Approach (ALMA) in post refractive surgery IOL power calculation with unknown preoperative parameters

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Undoubtedly, the reason for the significantly worse results of CR group is its simplicity, where only AL and K is used for IOL power calculation. Modern calculation methods, in order to increase the calculation accuracy, take into account more circumstances, which could affect the refractive predictability of the surgery (Olsen, 2007;Haigis, 2012;Gökce et al, 2018). Input parameters used in our models are standard parameters acquired using regular patient examination prior the cataract surgery.…”

Section: Discussionmentioning

confidence: 99%

Peer Review #1 of "Improving clinical refractive results of cataract surgery by machine learning (v0.1)"

2019

View full text Add to dashboard Cite

To evaluate potential of Support Vector Machine Regression model (SVM-RM) and Multilayer Neural Network Ensemble model (MLNN-EM) as an intraocular lens (IOL) power calculation improvement for clinical workflow. Background. Current IOL power calculation methods offer limited accuracy and especially in eyes with an unusual ocular dimension the accuracy may decrease. In case of an improperly calculated power of the IOL in cataract or refractive lens replacement surgery, there is a risk of re-operation or further refractive correction. This may potentially induce complications and discomfort to the patient. Methods. A dataset containing information about 2194 eyes was obtained using data mining process from Electronic Health Record (EHR) system database of Gemini Eye Clinic. The dataset was optimized and split into Selection set (used in design of models and training), and Verification set (used in the evaluation). Set of mean prediction errors and distribution of predicted refractive error were evaluated for both models and Clinical results. Results. Both models performed significantly better for the most evaluated parameters compared to the clinical results. There was no significant difference between both evaluated models. In the ± 0.50 D prediction error category both SVM-RM and MLNN-EM were slightly better than Barrett Universal II formula (which is often presented as the most accurate calculation formula). Conclusion. In comparison to the method currently used in a clinical setting, both SVM-RM and MLNN-EM has achieved significantly better results in IOL calculations and therefore there is a strong potential to improve clinical cataract refractive outcomes.

show abstract

Accuracy of 8 intraocular lens calculation formulas in relation to anterior chamber depth in patients with normal axial lengths

Abstract: In eyes with normal ALs, taking preoperative ACD values into consideration might improve refractive outcomes.

Cited by 42 publications

References 10 publications

New Approach for the Calculation of the Intraocular Lens Power Based on the Fictitious Corneal Refractive Index Estimation

New Approach for the Calculation of the Intraocular Lens Power Based on the Fictitious Corneal Refractive Index Estimation

An Advanced Lens Measurement Approach (ALMA) in post refractive surgery IOL power calculation with unknown preoperative parameters

Peer Review #1 of "Improving clinical refractive results of cataract surgery by machine learning (v0.1)"

Contact Info

Product

Resources

About