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Evaluation of prediction errors in nine intraocular lens calculation formulas using an explainable machine learning model.

Authors :
Oh R
Oh JY
Choi HJ
Kim MK
Yoon CH
Source :
BMC ophthalmology [BMC Ophthalmol] 2024 Dec 19; Vol. 24 (1), pp. 531. Date of Electronic Publication: 2024 Dec 19.
Publication Year :
2024

Abstract

Background: The purpose of the study was to evaluate the relationship between prediction errors (PEs) and ocular biometric variables in cataract surgery using nine intraocular lens (IOL) formulas with an explainable machine learning model.<br />Methods: We retrospectively analyzed the medical records of consecutive patients who underwent standard cataract surgery with a Tecnis 1-piece IOL (ZCB00) at a single center. We calculated predicted refraction using the following IOL formulas: Barrett Universal II (BUII), Cooke K6, EVO V2.0, Haigis, Hoffer QST, Holladay 1, Kane, SRK/T, and PEARL-DGS. We used a LightGBM-based machine learning model to evaluate the explanatory power of ocular biometric variables for PEs and assessed the relationship between PEs and ocular biometric variables using Shapley additive explanation (SHAP) values.<br />Results: We included 1,430 eyes of 1,430 patients in the analysis. The SRK/T formula exhibited the highest R <superscript>2</superscript> value (0.231) in the test set among the machine-learning models. In contrast, the Kane formula exhibited the lowest R <superscript>2</superscript> value (0.021) in the test set, indicating that the model could explain only 2.1% of the PEs using ocular biometric variables. BUII, Cooke K6, EVO V2.0, Haigis, Hoffer QST, Holladay 1, PEARL-DGS formulas exhibited R <superscript>2</superscript> values of 0.046, 0.025, 0.037, 0.194, 0.106, 0.191, and 0.058, respectively. Lower R <superscript>2</superscript> values for the IOL formulas corresponded to smaller SHAP values.<br />Conclusion: The explanatory power of currently used ocular biometric variables for PEs in new-generation formulas such as BUII, Cooke K6, EVO V2.0 and Kane is low, implying that these formulas are already optimized. Therefore, the introduction of new ocular biometric variables into IOL calculation formulas could potentially reduce PEs, enhancing the accuracy of surgical outcomes.<br />Competing Interests: Declarations. Ethics approval and consent to participate: This study was approved by the Institutional Review Board of Seoul National University Hospital (IRB No. 2112-132-1284) and was conducted in accordance with the Declaration of Helsinki. The need for written informed consent was waived because of the retrospective design and the use of deidentified patient data. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Meeting presentation: 16th Joint Meeting of Korea-China-Japan Ophthalmologists, 2023.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
1471-2415
Volume :
24
Issue :
1
Database :
MEDLINE
Journal :
BMC ophthalmology
Publication Type :
Academic Journal
Accession number :
39696028
Full Text :
https://doi.org/10.1186/s12886-024-03801-2