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基于机器学习分析手术和角膜参数对近视眼中SMILE术后屈光结果的影响。

Analyzing the Effect of Surgical and Corneal Parameters on the Postoperative Refractive Outcomes of Smile in Myopic Eyes Based on Machine Learning.

作者信息

Zhang Mingdong, Ji Shufan, Huo Yan, Bai Shaohu, Tao Ziheng, Zhang Jiamei, Cao Huazheng, Zou Haohan, Zhao Xinheng, Wang Yan

机构信息

From the Clinical College of Ophthalmology (M.Z., S.B., Y.W.), Tianjin Medical University, Tianjin, China.

School of Computer and Engineer (S.J., Z.T.), Beihang University, Beijing, China.

出版信息

Am J Ophthalmol. 2025 Mar;271:455-465. doi: 10.1016/j.ajo.2024.12.017. Epub 2024 Dec 27.

DOI:10.1016/j.ajo.2024.12.017
PMID:39733784
Abstract

PURPOSE

To analyze the influence of individual parameters on the postoperative refractive outcomes of small incision lenticule extraction (SMILE) in myopic eyes using machine learning.

DESIGN

Retrospective Clinical Cohort Study METHODS: This study included 477 patients (922 eyes) of SMILE and divided them into two groups based on postoperative spherical equivalent (SE) ≤ -0.50D to analyze the factors influencing postoperative refractive outcomes. The XGBoost model took 72 clinical parameters (34 biomechanical, 31 morphological, 4 surgical-related, and 3 preoperative refractive parameters) as features; randomly selected 42 eyes from the good refractive outcomes group and all eyes (a total of 42 eyes) from the poor refractive outcomes group to conduct 100 times influence factors analysis.

RESULTS

The 10 most important factors influencing postoperative refractive outcomes included 3 surgery-related parameters (PTA, LTmax, and RST), 3 corneal biomechanical parameters (HC Time, Deflection Amp Max (ms), and SSI), 2 corneal morphological parameters (R Per F and Rs F), and 2 preoperative refractive parameters (SE and SD). When PTA ≥ 25.09%, LTmax ≥ 139μm, SE ≤ -7.00D, or SD ≤ -6.75D, the postoperative SE significantly increased (all P < 0.05), with averages of -0.183D, -0.171D, -0.188D, and -0.184D. After controlling for age, intraocular pressure, and corneal thickness, the postoperative SE significantly increased when HC time ≥ 17.422 and Deflection Amp Max (ms) ≥ 16.616, reaching -0.209D and -0.202D.

CONCLUSIONS

More corneal tissue ablation, longer HC Time and Deflection Amp Max (ms), lower SSI, and higher preoperative refractive error may result in poor postoperative refractive outcomes.

摘要

目的

运用机器学习分析个体参数对近视眼微小切口基质透镜切除术(SMILE)术后屈光结果的影响。

设计

回顾性临床队列研究

方法

本研究纳入477例接受SMILE手术的患者(922只眼),根据术后等效球镜度(SE)≤-0.50D将其分为两组,以分析影响术后屈光结果的因素。XGBoost模型将72个临床参数(34个生物力学参数、31个形态学参数、4个手术相关参数和3个术前屈光参数)作为特征;从屈光结果良好组中随机选取42只眼,从屈光结果较差组中选取所有眼(共42只眼)进行100次影响因素分析。

结果

影响术后屈光结果的10个最重要因素包括3个手术相关参数(PTA、LTmax和RST)、3个角膜生物力学参数(HC时间、最大偏转幅度(毫秒)和SSI)、2个角膜形态学参数(R Per F和Rs F)以及2个术前屈光参数(SE和SD)。当PTA≥25.09%、LTmax≥139μm、SE≤-7.00D或SD≤-6.75D时,术后SE显著增加(均P<0.),平均值分别为-0.183D、-0.171D、-0.188D和-0.184D。在控制年龄、眼压和角膜厚度后,当HC时间≥17.422且最大偏转幅度(毫秒)≥16.616时,术后SE显著增加,分别达到-0.209D和-0.202D。

结论

更多的角膜组织消融、更长的HC时间和最大偏转幅度(毫秒)、更低的SSI以及更高的术前屈光不正可能导致术后屈光结果不佳。

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