Prediction of Postoperative Intraocular Lens Position with Angle-to-Angle Depth Using Anterior Segment Optical Coherence Tomography
Prediction of Postoperative Intraocular Lens Position with Angle-to-Angle Depth Using Anterior Segment Optical Coherence Tomography
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DOI：
10.1016/j.ophtha.2016.09.005
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发表时间：
2016-12-01
期刊：
影响因子：
13.7
通讯作者：
Nishida, Kohji
中科院分区：
文献类型：
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作者：
Goto, So;Maeda, Naoyuki;Nishida, Kohji
目得：评估一个新的公式预测术后前房深度（ACD）的准确性与术前角到角（ATA）的深度使用眼前节（AS）光学相干断层扫描（OCT），并将其与已建立的方法进行比较。设计：回顾性连续病例系列。304眼将276例植入丙烯酸酯人工晶状体（IOL）的患者随机分为训练集（152只眼）和验证集方法：基于训练集数据，采用5个术前测量变量，通过多元线性回归分析分析术后1个月测量的术后ACD：ATA深度、ATA宽度、使用AS OCT测量的术前ACD、眼轴长度（AL）和角膜屈光度。根据逐步分析的结果，提出了一个新的预测术后ACD的回归公式。在验证集数据中，将使用新公式获得的术后ACD测量值和术后ACD预测值之间的决定系数（R2）与使用Sanders-Retzlaff-Kraff理论（SRK/T）和Haigis公式获得的决定系数进行比较。绝对预测误差进行了比较，每个formulation.MAIN OUTCOME指标：术后ACD，术后ACD的中位数绝对预测误差，和眼部生物特征parameters.Results：在训练集，ATA深度产生了最高的标准偏回归系数值，表明ATA深度是最有效的参数用于预测术后ACD。建立了新的三变量回归公式; ATA深度、术前ACD和AL。在验证集中，新公式、SRK/T公式和Haigis公式预测术后ACD的R2分别为0.71、0.36和0.55，绝对预测误差的中位数分别为0.10 mm、0.65 mm和0.30 mm。分别新公式的绝对预测误差明显小于SRK/T和Haigis公式（P < 0.0001）。结论：采用3个术前参数（ATA深度、术前ACD和AL）的新公式预测术后ACD比SRK/T和Haigis公式更准确。使用经改进的术后ACD预测以及AS OCT（C）2016美国眼科学会测量的ATA深度，可能会提高IOL屈光度计算的准确性。爱思唯尔公司出版All rights reserved.
PURPOSE: To evaluate the accuracy of a new formula for predicting postoperative anterior chamber depth (ACD) with preoperative angle-to-angle (ATA) depth using anterior segment (AS) optical coherence tomography (OCT) and to compare it with established methods.DESIGN: Retrospective consecutive case series.PARTICIPANTS: Three hundred four eyes (276 patients) implanted with acrylic intraocular lenses (IOLs) were divided randomly into a training set (152 eyes) and a validation set (152 eyes).METHODS: Based on the training set data, the postoperative ACD measured 1 month after surgery was analyzed via multiple linear regression analysis with 5 preoperatively measured variables: ATA depth, ATA width, preoperative ACD measured with AS OCT, axial length (AL), and corneal power. A new regression formula for predicting postoperative ACD was developed using the results of the stepwise analysis. In the validation set data, the coefficients of determination (R2) between the measured postoperative ACD and the predicted postoperative ACD obtained using the new formula were compared with those obtained using the Sanders-Retzlaff-Kraff theoretic (SRK/T) and Haigis formulas. The absolute prediction errors were compared with each formula.MAIN OUTCOME MEASURES: Postoperative ACD, median absolute prediction error of postoperative ACD, and ocular biometric parameters.RESULTS: In the training set, ATA depth yielded the highest standard partial regression coefficient value, indicating that ATA depth is the most effective parameter for predicting postoperative ACD. The new regression formula was developed with 3 variables; ATA depth, preoperative ACD, and AL. In the validation set, the postoperative ACDs of the new formula, the SRK/T formula, and Haigis formula were predicted with R2 of 0.71, 0.36, and 0.55, respectively, and the medians of the absolute prediction errors were 0.10 mm, 0.65 mm, and 0.30 mm, respectively. The absolute prediction error with the new formula was significantly smaller than those obtained with the SRK/T and Haigis formulas (P < 0.0001).CONCLUSIONS: The new formula with 3 preoperative parameters-ATA depth, preoperative ACD, and AL-predicted postoperative ACD more accurately than the SRK/T and Haigis formulas. It may be possible to improve the accuracy of IOL power calculation using an improved postoperative ACD prediction with the ATA depth measured by AS OCT. (C) 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.