目的：正确选择人工晶状体（IOL）屈光力计算公式是白内障超声乳化术的重要方面。在这项研究中,描述了当今最常用的公式，并评估了它们的准确性。
方法：本评论包括评估2015年1月至2022年12月期间发布的IOL屈光力计算公式准确性的论文。这些文章是通过对医学和其他数据库(PubMed/MEDLINE，Crossref,WebofScience,SciELO,谷歌学者，和Cochrane库)使用术语“IOL公式，\"\"巴雷特环球II,\"\"凯恩,\"\"Hill-RBF,\"\"奥尔森,\"\"珍珠-DGS,\"\"EVO,\"\"Haigis,\"\"SRK/T,\"和\"HofferQ.\"29个最新的同行评审的英文论文与最大的样本和最多的公式比较被认为。
结果：在±0.5D和±1.0D内的平均绝对误差和预测百分比的结果用于评估公式的准确性。在大多数研究中,Barrett的平均绝对误差最小，PEARL-DGS的患者在短眼中±0.5D的百分比最高，而凯恩在长眼中获得±0.5D的患者比例最高。
结论：第三代和第四代公式正在逐渐被更精确的公式所取代。目前，收敛公式中的BarrettUniversalII以及基于人工智能的公式中的Kane和PEARL-DGS被认为是最精确的。
OBJECTIVE: The proper choice of an intraocular lens (IOL) power calculation formula is an important aspect of phacoemulsification. In this study, the formulas most commonly used today are described and their accuracy is evaluated.
METHODS: This
review includes papers evaluating the accuracy of IOL power calculation formulas published during the period from January 2015 to December 2022. The articles were identified by a literature search of medical and other databases (PubMed/MEDLINE, Crossref, Web of Science, SciELO, Google Scholar, and Cochrane Library) using the terms \"IOL formulas,\" \"Barrett Universal II,\" \"Kane,\" \"Hill-RBF,\" \"Olsen,\" \"PEARL-DGS,\" \"EVO,\" \"Haigis,\" \"SRK/T,\" and \"Hoffer Q.\" Twenty-nine of the most recent peer-reviewed papers in English with the largest samples and largest number of formulas compared were considered.
RESULTS: Outcomes of mean absolute error and percentage of predictions within ±0.5 D and ±1.0 D were used to evaluate the accuracy of the formulas. In most studies, Barrett achieved the smallest mean absolute error and PEARL-DGS the highest percentage of patients with ±0.5 D in short eyes, while Kane obtained the highest percentage of patients with ±0.5 D in long eyes.
CONCLUSIONS: The third- and fourth-generation formulas are gradually being replaced by more accurate ones. The Barrett Universal II among vergence formulas and Kane and PEARL-DGS among artificial intelligence-based formulas are currently most often reported as the most precise.
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