A Comprehensive Evaluation of 16 Old and New Intraocular Lens Power Calculation Formulas in Pediatric Eyes
Bibliographic record
Abstract
Asaf Achiron,1 Tal Yahalomi,2 Amit Biran,1 Eliya Levinger,1 Eyal Cohen,1 Uri Elbaz,3 Asim Ali,4,5 Kamiar Mireskandari,4,5 Raimo Tuuminen,6,7 Oleksiy V Voytsekhivskyy8 1Tel Aviv Sourasky Medical Center, Tel Aviv, Israel and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel; 2Department of Ophthalmology, Samson Assuta Ashdod Hospital and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Be’er Sheva, Israel; 3Department of Ophthalmology, Rabin Medical Center, Petach-Tikva and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel; 4Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, Ontario, Canada; 5Department of Ophthalmology and Vision Sciences, the Hospital for Sick Children, Toronto, Ontario, Canada; 6Helsinki Retina Research Group, Faculty of Medicine, University of Helsinki, Helsinki, Finland; 7Department of Ophthalmology, Kymenlaakso Central Hospital, Kotka, Finland; 8Kyiv Clinical Ophthalmology Hospital Eye Microsurgery Center, Kyiv, UkraineCorrespondence: Oleksiy V Voytsekhivskyy, Kyiv Clinical Ophthalmology Hospital Eye Microsurgery Center, Komarov Ave. 3, Medical City, Kyiv, 03680, Ukraine, Tel +38067-584-28-11, Email iolpower@ukr.netPurpose: To compare the accuracy of 16 intraocular lens (IOL) power calculation formulas in pediatric cataract eyes.Patients and Methods: The data records of pediatric patients who had been implanted with three IOL models (SA60AT, MA60AC, and enVista-MX60) between 2012 and 2018 were analyzed. The accuracy of 16 IOL power calculation methods was evaluated: Barrett Universal II (BUII), Castrop, EVO 2.0, Haigis, Hill-RBF 3.0, Hoffer Q, Hoffer QST, Holladay 1, Kane, LSF AI, Naeser 2, Pearl-DGS, SRK/T, T2, VRF, and VRF-G. The non-optimized (ULIB/IOLcon) and optimized constants were used for IOL power calculation. The mean prediction error (PE), Performance Index (FPI), and all descriptive statistics were calculated.Results: Ninety-seven eyes of 97 pediatric patients aged 13.2 (IQR 11.2– 17.1) were included. No statistically significant difference (HS-test) was observed (p > 0.818) except for the Hoffer Q, and Naeser 2 (P = 0.014). With optimized lens constants, the best FPI indices were obtained by Hoffer Q (0.256) and VRF-G (0.251) formulas, followed by Hill-RBF 3.0 and BUII, with an index of 0.248. The highest FPI indices with non-optimized constants showed SRK/T and T2 formulas (0.246 and 0.245, respectively), followed by VRF-G and Holladay 1, with an index of 0.244. The best median absolute error values (MedAE) were achieved by Hoffer Q (0.50 D), VRF-G (0.53 D), and Hill-RBF 3.0 (0.54 D), all P ≥ 0.074.Conclusion: Our results place the Hoffer Q, VRF-G, Hill-RBF 3.0, and BUII formulas as more accurate predictors of postoperative refraction in pediatric cataract surgery.Keywords: IOL power, formulas, pediatric eyes, calculation, axial length
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".