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作 者:刘汉强[1] 马长荣[1] 张慧[1] 马小力[1] 靳英[1] 金学海[1] 时景璞[2] 王海龙[2]
机构地区:[1]中国医科大学附属第一医院眼科,沈阳110001 [2]中国医科大学临床流行病教研室
出 处:《中华流行病学杂志》2003年第4期307-309,共3页Chinese Journal of Epidemiology
摘 要:目的 探讨各种因素与准分子激光角膜原位磨镶术 (LASIK)后屈光度欠矫的关系。方法 对行LASIK的近视患者 696例中屈光度欠矫病例 ,按年龄、性别、职业、住址、近视时间、家族史以及手术前后全部检查资料分左右眼两组进行单因素 χ2 检验和多因素logistic回归分析。结果多因素条件logistic回归分析显示 ,左、右眼两组均与 4种因素有关 :近视时间 (左眼组 OR =1 .0 76,95 %CI:1 .0 30~ 1 .1 2 4 ;右眼组OR =1 .0 93 ,95 %CI:1 .0 4 6~ 1 .1 4 2 )、近视屈光度 (左眼组OR =7.799,95%CI:1 .755~ 34.654 ;右眼组OR =2 8.82 3 ,95%CI:5.750~ 1 4 4 .467)、术前矫正视力 (左眼组OR =0 .0 0 0 ,95%CI:0 .0 0 0~ 0 .2 62 ;右眼组OR =0 .0 0 0 ,95%CI:0 .0 0 0~ 0 .1 4 4 )和角膜厚度 (左眼组OR =0 .976 ,95%CI:0 .965~ 0 .987;右眼组OR =0 .975 ,95 %CI:0 .964~ 0 .986)。结论 近视时间长 ,近视屈光度大是LASIK术后屈光度欠矫的危险因素 ;术前矫正视力好 。Objective To investigate the relationship between various factors and the undercorrection after laser in situ keratomileusis (LASIK). Methods Of 1 391 eyes (696 cases), the undercorrection eyes grouped by left or right eye were analyzed by Chi square test and logistic regression analysis based on age, sex, occupation, address, family history of myopia and all ophthalmologic examination results before and after LASIK. Results The results of logistic regression analysis showed that the undercorrection after LASIK of both groups was related to four factors: the duration of myopia (left eye OR = 1.076 , 95% CI : 1.030 1.124 ; right eye OR = 1.093 ,95% CI : 1.046 1.142 ), preoperative refractive power (left eye OR = 7.799 , 95% CI : 1.755 34.654 ; right eye OR = 28.823 , 95% CI : 5.750 144.467 ), preoperative best corrected vision (left eye OR = 0.000 , 95% CI : 0.000 0.262 ; right eye OR = 0.000 , 95% CI : 0.000 0.144 ) and the corneal thickness(left eye OR = 0.976 , 95% CI : 0.965 0.987 ; right eye OR = 0.975 , 95% CI : 0.964 0.986 ). Conclusion Longer duration of myopia and the more refractive power seemed to be the risk factors, while the better corrected vision and the thicker thickness of cornea the protect factors of undercorrection after LASIK.
关 键 词:准分子激光角膜原位磨镶术 屈光度欠矫 危险因素 LOGISTIC回归分析
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