Lin Meng-Yin, Chang David C K, Shen Yun-Dun, Lin Yen-Kuang, Lin Chang-Ping, Wang I-Jong
Department of Ophthalmology, Shuang Ho Hospital, Taipei Medical School of Medicine, Taipei Medical University, Taipei County, Taiwan.
Institute of Clinical Medicine, School of Medicine, National Taiwan University, Taipei, Taiwan.
PLoS One. 2016 Jan 29;11(1):e0147699. doi: 10.1371/journal.pone.0147699. eCollection 2016.
The aim of this study is to describe factors that influence the measured intraocular pressure (IOP) change and to develop a predictive model after myopic laser in situ keratomileusis (LASIK) with a femtosecond (FS) laser or a microkeratome (MK). We retrospectively reviewed preoperative, intraoperative, and 12-month postoperative medical records in 2485 eyes of 1309 patients who underwent LASIK with an FS laser or an MK for myopia and myopic astigmatism. Data were extracted, such as preoperative age, sex, IOP, manifest spherical equivalent (MSE), central corneal keratometry (CCK), central corneal thickness (CCT), and intended flap thickness and postoperative IOP (postIOP) at 1, 6 and 12 months. Linear mixed model (LMM) and multivariate linear regression (MLR) method were used for data analysis. In both models, the preoperative CCT and ablation depth had significant effects on predicting IOP changes in the FS and MK groups. The intended flap thickness was a significant predictor only in the FS laser group (P < .0001 in both models). In the FS group, LMM and MLR could respectively explain 47.00% and 18.91% of the variation of postoperative IOP underestimation (R2 = 0.47 and R(2) = 0.1891). In the MK group, LMM and MLR could explain 37.79% and 19.13% of the variation of IOP underestimation (R(2) = 0.3779 and 0.1913 respectively). The best-fit model for prediction of IOP changes was the LMM in LASIK with an FS laser.
本研究旨在描述影响测量的眼压（IOP）变化的因素，并建立飞秒（FS）激光或微型角膜刀（MK）近视准分子原位角膜磨镶术（LASIK）后的预测模型。我们回顾性分析了1309例接受FS激光或MK近视及近视散光LASIK手术患者的2485只眼的术前、术中和术后12个月的病历。提取的数据包括术前年龄、性别、眼压、明显球镜等效度（MSE）、中央角膜曲率（CCK）、中央角膜厚度（CCT）、预期瓣厚度以及术后1、6和12个月的眼压（postIOP）。采用线性混合模型（LMM）和多元线性回归（MLR）方法进行数据分析。在这两种模型中，术前CCT和消融深度对FS组和MK组的眼压变化预测均有显著影响。预期瓣厚度仅在FS激光组是一个显著的预测因素（两种模型中P均<0.0001）。在FS组，LMM和MLR分别可以解释术后眼压低估变化的47.00%和18.91%（R2 = 0.47 和R(2) = 0.1891）。在MK组，LMM和MLR分别可以解释眼压低估变化的37.79%和19.13%（R(2) = 0.3779 和0.1913）。预测眼压变化的最佳拟合模型是FS激光LASIK中的LMM。
