A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients.
A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients.
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DOI：
10.1038/srep31728
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发表时间：
2016-08-26
影响因子：
4.6
通讯作者：
Japanese Archive of Multicentral Database in Glaucoma (JAMDIG) construction group
中科院分区：
文献类型：
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作者：
Japanese Archive of Multicentral Database in Glaucoma (JAMDIG) construction group
回顾性地获得了317例开角型青光眼患者491只眼的视野（VF）数据，这些患者接受了10次VF测试（Humphrey Field Analyzer，24-2，SITA标准）。首先，使用前5个VF（VF 1 -5）的标准线性回归至使用所有9个之前VF（VF 1 -9）预测第10个VF的总偏差值（mTD）的平均值。然后通过简单地使用时间乘以IOP作为线性回归模型中的独立项来进行“眼内压（IOP）-整合VF趋势分析”。从两种方法中获得用于预测mTD的预测误差（绝对预测误差或均方根误差：RMSE）以及第十VF的逐点TD值。当使用VF 1 -6至VF 1 -8时，与IOP积分VF趋势分析相关的MTD绝对预测误差显著小于标准趋势分析的绝对预测误差（p < 0.05）。当使用VF 1 -5至VF 1 -9时，IOP整合趋势分析的逐点RMSE显著小于标准趋势分析的RMSE（p < 0.05）。当更频繁地测量IOP时，情况尤其如此。因此，使用结合IOP测量的简单趋势分析可以显著更准确地预测VF进展。
Visual field (VF) data were retrospectively obtained from 491 eyes in 317 patients with open angle glaucoma who had undergone ten VF tests (Humphrey Field Analyzer, 24-2, SITA standard). First, mean of total deviation values (mTD) in the tenth VF was predicted using standard linear regression of the first five VFs (VF1-5) through to using all nine preceding VFs (VF1-9). Then an ‘intraocular pressure (IOP)-integrated VF trend analysis’ was carried out by simply using time multiplied by IOP as the independent term in the linear regression model. Prediction errors (absolute prediction error or root mean squared error: RMSE) for predicting mTD and also point wise TD values of the tenth VF were obtained from both approaches. The mTD absolute prediction errors associated with the IOP-integrated VF trend analysis were significantly smaller than those from the standard trend analysis when VF1-6 through to VF1-8 were used (p < 0.05). The point wise RMSEs from the IOP-integrated trend analysis were significantly smaller than those from the standard trend analysis when VF1-5 through to VF1-9 were used (p < 0.05). This was especially the case when IOP was measured more frequently. Thus a significantly more accurate prediction of VF progression is possible using a simple trend analysis that incorporates IOP measurements.