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[摘要]
目的:比较不同角膜曲率和前房深度短眼轴白内障人群7种人工晶状体计算公式的屈光预测准确性,并分析预测误差的影响因素。
方法:回顾性分析了2020-11/2021-12在沈阳何氏眼科医院单纯行白内障超声乳化术的短眼轴患者125例125眼。按角膜曲率(Km)分为低平Km组(≤45.5 D)、中高Km组(45.5 D结果:总体比较时,各公式的预测误差存在显著差异(χ2=49.934,P<0.001),Barrett Universal Ⅱ公式的MedAE最小(0.17 D)。分组比较时,中高及陡峭Km组各公式的预测误差存在显著差异(χ2=34.372、34.804,均P<0.001),Barrett Universal Ⅱ公式的MedAE(0.14 D; 0.20 D)最小; ACD 3个分组的各公式预测误差均存在差异(χ2=22.863、25.568、13.647,均P<0.05),Barrett Universal Ⅱ公式的MedAE(0.27 D; 0.15 D; 0.16 D)最小。多元线性回归分析显示Km、AL及IOL度数是导致术后预测误差的重要相关因素。结论:短眼轴人群在不同生物测量参数下Barrett Universal Ⅱ公式较其他公式准确性更高,AL、Km及IOL度数与预测准确性密切相关。
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[Abstract]
AIM: To compare the refractive prediction accuracy of 7 intraocular lens(IOL)calculation formulas in the cataract eyes with short axial length(AL)at different corneal curvatures and anterior chamber depth(ACD), and analyze relevant influencing factors contributing to prediction errors.
METHODS: A retrospective analysis was performed for 125 patients(125 eyes)with a short AL, who received cataract phacoemulsification at Shenyang He Eye Specialist Hospital from November 2020 to December 2021. According to the keratometry(Km), they were divided into low flat Km group(≤45.5 D), medium and high Km group(45.5 DRESULTS: There was a significant difference in the absolute prediction error of each formula(χ2=49.934, P<0.001)in the overall comparative analysis, and the MedAE of the Barrett Universal Ⅱ formula was the smallest(0.17 D). There were significant statistical differences in the middle-high and steep Km groups(χ2=34.372, 34.804, all P<0.001), and the MedAE(0.14 D; 0.20 D)of the Barrett Universal Ⅱ formula was the smallest. The absolute prediction error of the 3 ACD subgroups was statistically significant(χ2=22.863, 25.568, 13.647, all P<0.05), and the MedAE(0.27 D; 0.15 D; 0.16 D)of the Barrett Universal Ⅱ formula was the smallest. Multiple linear regression analysis showed that Km, AL, and the IOL degree were important correlated factor leading to postoperative prediction error.CONCLUSION: The accuracy of the Barrett Universal Ⅱ formula was higher in the short AL population under different biometric parameters, and AL, Km and IOL degree are closely related to the prediction accuracy.
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