Jung Soyeon, Chin Hee Seung, Kim Na Rae, Lee Kang Won, Jung Ji Won
Department of Ophthalmology and Inha Vision Science Laboratory, Inha University School of Medicine, Incheon, Republic of Korea.
J Ophthalmol. 2017;2017:1516395. doi: 10.1155/2017/1516395. Epub 2017 Dec 10.
To assess the repeatability and agreement of parameters obtained with two biometers and to compare the predictability.
Biometry was performed on 101 eyes with cataract using the IOLMaster 700 and the Galilei G6. Three measurements were obtained per eye with each device, and repeatability was evaluated. The axial length (AL), anterior chamber depth (ACD), keratometry (K), white-to-white (WTW) corneal diameter, central corneal thickness (CCT), and lens thickness (LT) were measured and postoperative predictability was compared.
Measurements could not be obtained with the IOLMaster 700 in one eye and in seven eyes with the Galilei G6 due to dense cataract. Both the IOLMaster 700 and Galilei G6 showed good repeatability, although the IOLMaster 700 showed better repeatability than the Galilei G6. There were no statistically significant differences in AL, ACD, steepest K, WTW, and LT ( > 0.050), although flattest K, mean K, and CCT differed ( < 0.050). The proportion of eyes with an absolute prediction error within 0.5 D was 85.0% for the IOLMaster 700 and was 80.0% for the Galilei G6 based on the SRK/T formula.
Two biometers showed high repeatability and relatively good agreements. The swept-source optical biometer demonstrated better repeatability, penetration, and an overall lower prediction error.
评估两种生物测量仪所获得参数的可重复性和一致性,并比较其预测性。
使用IOLMaster 700和Galilei G6对101只白内障患眼进行生物测量。每台设备对每只眼睛进行三次测量,并评估其可重复性。测量眼轴长度(AL)、前房深度(ACD)、角膜曲率(K)、角膜白对白(WTW)直径、中央角膜厚度(CCT)和晶状体厚度(LT),并比较术后预测性。
由于白内障致密,IOLMaster 700有1只眼、Galilei G6有7只眼无法获得测量值。IOLMaster 700和Galilei G6均显示出良好的可重复性,尽管IOLMaster 700的可重复性优于Galilei G6。AL、ACD、最陡K值、WTW和LT无统计学显著差异(>0.050),但最平K值、平均K值和CCT存在差异(<0.050)。根据SRK/T公式,IOLMaster 700预测误差绝对值在0.5 D以内的眼比例为85.0%,Galilei G6为80.0%。
两种生物测量仪显示出高可重复性和相对较好的一致性。扫频光学生物测量仪显示出更好的可重复性、穿透性和总体较低的预测误差。