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眼部生物测量的双高斯特性。

The bigaussian nature of ocular biometry.

作者信息

Rozema Jos J, Tassignon Marie-José

机构信息

*PhD †MD, PhD Department of Ophthalmology, Antwerp University Hospital, Edegem, Belgium (both authors); and Department of Medicine and Health Sciences, Antwerp University, Wilrijk, Belgium (both authors).

出版信息

Optom Vis Sci. 2014 Jul;91(7):713-22. doi: 10.1097/OPX.0000000000000296.

Abstract

PURPOSE

To study how the leptokurtic shape of the refractive distribution can be derived from ocular biometry by means of a multivariate Gaussian model.

METHODS

Autorefraction and optical biometry data (Scheimpflug and partial coherence interferometry) were obtained for 1136 right eyes of healthy white subjects recruited by various European ophthalmological centers participating in Project Gullstrand. These biometric data were fitted with linear combinations of multivariate Gaussians to create a Monte Carlo simulation of the biometry, from which the corresponding refraction was calculated. These simulated data were then compared with the original data by histogram analysis.

RESULTS

The distribution of the ocular refraction more closely resembled a bigaussian than a single Gaussian function (F test, p < 0.001). This also applied to the axial length, which caused the combined biometry data to be better represented by a linear combination of two multivariate Gaussians rather than by a single one (F test, p < 0.001). Corneal curvature, anterior chamber depth, and lens power, on the other hand, displayed a normal distribution. All distributions were found to gradually change with age. The statistical descriptors of these two subgroups were compared and found to differ significantly in average and SD for the refraction, axial length, and anterior chamber depth. All distributions were also found to change significantly with age.

CONCLUSIONS

The bigaussian model provides a more accurate description of the data from the original refractive distribution and suggests that the general population may be composed of two separate subgroups with different biometric properties.

摘要

目的

研究如何通过多元高斯模型从眼生物测量中得出屈光分布的尖峰态形状。

方法

获取了参与古尔斯特兰德项目的多个欧洲眼科中心招募的1136名健康白人受试者右眼的自动验光和光学生物测量数据(Scheimpflug和部分相干干涉测量法)。这些生物测量数据用多元高斯的线性组合进行拟合,以创建生物测量的蒙特卡罗模拟,从中计算出相应的屈光度数。然后通过直方图分析将这些模拟数据与原始数据进行比较。

结果

眼屈光分布更类似于双高斯分布而非单高斯函数(F检验,p < 0.001)。这也适用于眼轴长度,这使得组合生物测量数据由两个多元高斯的线性组合而非单个多元高斯能更好地表示(F检验,p < 0.001)。另一方面,角膜曲率、前房深度和晶状体屈光力呈现正态分布。所有分布均随年龄逐渐变化。对这两个亚组的统计描述符进行比较,发现屈光度数、眼轴长度和前房深度在平均值和标准差方面存在显著差异。还发现所有分布均随年龄显著变化。

结论

双高斯模型能更准确地描述原始屈光分布的数据,并表明普通人群可能由具有不同生物测量特性的两个独立亚组组成。

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