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科罗拉多早产儿视网膜病变筛查算法(CO-ROP):在一家三级医疗中心进行的验证研究。

Colorado Retinopathy of Prematurity Screening Algorithm (CO-ROP): a validation study at a tertiary care center.

作者信息

Huang Jason M, Lin Xihui, He Yu-Guang, Cao Jennifer H

机构信息

Department of Ophthalmology, University of Texas Southwestern Medical Center, Dallas, Texas.

Department of Ophthalmology, University of Texas Southwestern Medical Center, Dallas, Texas.

出版信息

J AAPOS. 2017 Apr;21(2):152-155. doi: 10.1016/j.jaapos.2017.03.009. Epub 2017 Mar 16.

Abstract

PURPOSE

The Colorado Retinopathy of Prematurity Screening Algorithm (CO-ROP) recommends screening for infants meeting the following criteria for retinopathy of prematurity (ROP): gestational age ≤30 weeks, birth weight of ≤1500 g, and net weight gain of ≤650 g between birth and 4 weeks of age. This study was performed to evaluate the validity of CO-ROP in a tertiary referral county hospital.

METHODS

CO-ROP was used to retrospectively analyze the data from consecutive newborns screened for ROP using national screening guidelines at Parkland Hospital, Dallas, Texas, between April 1, 2009, to August 30, 2013. Sensitivities and specificities for identifying ROP were calculated.

RESULTS

A total of 374 infants were included, of whom 29 (7.8%) developed type 1 ROP and 12 (3.2%) developed type 2 ROP. The CO-ROP model would have decreased number of infants screened by 34% compared to current national screening criteria. CO-ROP had sensitivity of 93.1% (95% CI, 77.2-99.1) and 92.7% (95% CI, 61.5-99.8) for identifying type 1 and type 2 ROP, respectively. Of 29 patients who developed type 1 ROP, 2 were not identified using CO-ROP.

CONCLUSIONS

The CO-ROP model significantly reduced total number screened but failed to detect 2 infants with type 1 ROP, suggesting the need for further modification of the algorithm.

摘要

目的

科罗拉多早产儿视网膜病变筛查算法(CO-ROP)建议对符合以下早产儿视网膜病变(ROP)标准的婴儿进行筛查:胎龄≤30周、出生体重≤1500克、出生至4周龄时体重净增≤650克。本研究旨在评估CO-ROP在一家三级转诊县级医院中的有效性。

方法

采用CO-ROP对2009年4月1日至2013年8月30日期间在得克萨斯州达拉斯帕克兰医院按照国家筛查指南进行ROP筛查的连续新生儿数据进行回顾性分析。计算识别ROP的敏感性和特异性。

结果

共纳入374例婴儿,其中29例(7.8%)发生1型ROP,12例(3.2%)发生2型ROP。与当前国家筛查标准相比,CO-ROP模型可减少34%的筛查婴儿数量。CO-ROP识别1型和2型ROP的敏感性分别为93.1%(95%CI,77.2-99.1)和92.7%(95%CI,61.5-99.8)。在29例发生1型ROP的患者中,有2例未通过CO-ROP识别。

结论

CO-ROP模型显著减少了总筛查数量,但未能检测出2例1型ROP婴儿,提示该算法需要进一步修改。

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