The goal of this observational study is to evaluate the long-term refractive outcomes of advanced intraocular lens (IOL) power calculation formulas in cataract patients with posterior corneal elevation (PCE ≥ 15 μm). The main question it aims to answer is: Do PK-based formulas provide superior refractive accuracy compared with Without-PK-based formulas in patients with elevated posterior corneal surfaces? Participants undergoing routine cataract surgery will have their biometry measured by both Pentacam AXL and IOLMaster 700, and postoperative refraction will be collected at 1 month, 3 months, and 6 months postoperatively.
Study Type
OBSERVATIONAL
Enrollment
102
The study evaluates four groups of intraocular lens (IOL) power calculation formulas, totaling 13 distinct formulas, to compare their accuracy in predicting postoperative refractive outcomes in cataract patients. Group 1 - Without PK: Barrett Universal II (BUⅡ), EVO 2.0, Kane, Hill-RBF 3.0, LADAS, Pearl-DGS, and K6, which do not incorporate PK. Group 2 - Measured PK-I: Barrett TK measured (I) and EVO Advanced (I), which use measured PK from IOLMaster 700. Group 3 - Measured PK-P: Barrett TK measured (P) and EVO Advanced (P), which use measured PK from Pentacam AXL. Group 4 - Predicted PK: Barrett TK predicted and Kane KC, which estimate PK through prediction algorithms rather than direct measurement. This observational study does not introduce experimental procedures; all data are collected during routine cataract surgery and postoperative follow-up to determine the comparative accuracy of these formulas
Department of Ophthalmology, The Second Affiliated Hospital of Xi'an Jiaotong University
Xi'an, Shaanxi, China
absolute SEQ-PE(accuracy)
the absolute values of SEQ-PE
Time frame: From enrollment to the end of treatment at 6 months
SEQ-PE(trueness)
Spherical Equivalent Prediction Error 1. SEQ=Sphere+2Cylinder 2. PE=Postoperative Manifest SEQ-Predicted SEQ
Time frame: From enrollment to the end of treatment at 6 months
Precision
Precision refers to the consistency of the prediction errors (PE) of a formula across a study population, indicating how closely the individual prediction errors cluster around the central tendency (e.g., mean or median). A formula with higher precision shows smaller variability in its prediction errors.
Time frame: From enrollment to the end of treatment at 6 months
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