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白内障手术后视觉功能的预测。一个经过前瞻性验证的模型。

Prediction of visual function after cataract surgery. A prospectively validated model.

作者信息

Mangione C M, Orav E J, Lawrence M G, Phillips R S, Seddon J M, Goldman L

机构信息

Division of Clinical Epidemiology, Brigham and Women's Hospital, Boston, Mass., USA.

出版信息

Arch Ophthalmol. 1995 Oct;113(10):1305-11. doi: 10.1001/archopht.1995.01100100093037.

Abstract

OBJECTIVE

To develop a model to predict visual functional improvement after cataract extraction with intraocular lens implantation based on preoperative data.

DESIGN

A prospective study with serial evaluations of visual function preoperatively and at 3 and 12 months after surgery.

SETTING

The General Eye Service of the Massachusetts Eye and Ear Infirmary. Boston, Mass, and 33 ophthalmology practices in Boston.

PATIENTS

Patients (N = 426; ages, > or = 65 years) who were undergoing cataract surgery.

METHODS

Twelve-month improvement in visual function was measured by using the Activities of Daily Vision Scale (ADVS). Ordinal logistic regression was used to identify correlates of improved ADVS scores in 281 patients (derivative set). Potential factors included the preoperative visual acuity, preoperative ADVS score, four chronic ocular diseases, eight medical conditions, and demographic characteristics. Five predictors were identified and used to construct a prediction rule. The accuracy of the prediction rule was evaluated in an independent group of 145 patients (validation set).

RESULTS

Postoperatively, 40% of the 281 patients in the derivative set had substantial improvement in their ADVS scores, and 53 (19%) had some improvement. Predictors of improvement included younger age (P < .001), a poorer preoperative ADVS score (P < .001), posterior subcapsular cataract (P = .09), and absence of age-related cataract (P = .09), and absence of age-related macular degeneration (P = .07) and/or diabetes (P = .006). When applied to the independent sample of 145 patients, these five characteristics classified the patients into three groups in which the probabilities of substantial improvement were 85%, 34%, and 3%, thus verifying the discriminatory power of the prediction rule.

CONCLUSIONS

Preoperative data can identify patients who are likely to have improvements in visual function after cataract surgery. Such findings may be useful in the selection of patients for this high-volume procedure.

摘要

目的

基于术前数据开发一种模型,以预测白内障摘除联合人工晶状体植入术后视觉功能的改善情况。

设计

一项前瞻性研究,对患者术前以及术后3个月和12个月的视觉功能进行系列评估。

地点

马萨诸塞州眼耳医院的综合眼科服务部,马萨诸塞州波士顿市,以及波士顿的33家眼科诊所。

患者

接受白内障手术的患者(N = 426;年龄≥65岁)。

方法

采用日常视觉活动量表(ADVS)测量12个月时视觉功能的改善情况。对281例患者(衍生组)使用有序逻辑回归分析来确定与ADVS评分改善相关的因素。潜在因素包括术前视力、术前ADVS评分、四种慢性眼病、八种内科疾病以及人口统计学特征。确定了五个预测因素并用于构建预测规则。在145例独立患者(验证组)中评估该预测规则的准确性。

结果

在衍生组的281例患者中,术后40%的患者ADVS评分有显著改善,53例(19%)有一定程度的改善。改善的预测因素包括年龄较小(P < .001)、术前ADVS评分较差(P < .001)、后囊下白内障(P = .09)、无年龄相关性白内障(P = .09)、无年龄相关性黄斑变性(P = .07)和/或无糖尿病(P = .006)。将这五个特征应用于145例独立样本患者时,可将患者分为三组,其中显著改善的概率分别为85%、34%和3%,从而验证了预测规则的辨别能力。

结论

术前数据可以识别出白内障手术后视觉功能可能改善的患者。这些发现可能有助于为这一高容量手术选择合适的患者。

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