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利用产后每日体重增加、出生体重和胎龄实施临床预测模型对视网膜病变进行风险分层。

Implementation of a Clinical Prediction Model Using Daily Postnatal Weight Gain, Birth Weight, and Gestational Age to Risk Stratify ROP.

作者信息

McCauley Kortany, Chundu Anupama, Song Helen, High Robin, Suh Donny

出版信息

J Pediatr Ophthalmol Strabismus. 2018 Sep 20;55(5):326-334. doi: 10.3928/01913913-20180405-02. Epub 2018 Jun 19.

Abstract

PURPOSE

To develop a simple prognostic model using postnatal weight gain, birth weight, and gestational age to identify infants at risk for developing severe retinopathy of prematurity (ROP).

METHODS

Medical records from two tertiary referral centers with the diagnosis code "Retinopathy of Prematurity" were evaluated. Those with a birth weight of 1,500 g or less, gestational age of 30 weeks or younger, and unstable clinical courses were included. Multivariate regression analysis was applied to transform three independent variables into a growth rate algorithm.

RESULTS

Seventeen of 191 neonates had severe ROP. Weight gain of at least 23 g/d was determined as a protective cut-off value against development of severe ROP. This value maintained 100% sensitivity with 62% specificity to ensure all neonates who require treatment would be captured. Overall, the Omaha (OMA)-ROP model calculated a 58% reduction in eye examinations within the cohort.

CONCLUSIONS

Inclusion of postnatal growth rate in risk stratification will minimize the number of eye examinations performed without increasing adverse visual outcomes. The OMA-ROP model predicts neonates who gain less than 23 g/d are at higher risk for developing severe ROP. Although promising, larger cohort studies may be necessary to validate and implement new screening practices among preterm infants. [J Pediatr Ophthalmol Strabismus. 2018;55(5):326-334.].

摘要

目的

利用出生后体重增加、出生体重和胎龄建立一个简单的预后模型,以识别有发生严重早产儿视网膜病变(ROP)风险的婴儿。

方法

对两个三级转诊中心诊断编码为“早产儿视网膜病变”的病历进行评估。纳入出生体重1500g及以下、胎龄30周及以下且临床病程不稳定的婴儿。应用多变量回归分析将三个独立变量转化为生长速率算法。

结果

191例新生儿中有17例发生严重ROP。确定每日体重增加至少23g为预防严重ROP发生的保护临界值。该值保持100%的敏感性和62%的特异性,以确保所有需要治疗的新生儿都能被发现。总体而言,奥马哈(OMA)-ROP模型计算出队列中的眼部检查减少了58%。

结论

将出生后生长速率纳入风险分层将在不增加不良视觉结局的情况下减少眼部检查的次数。OMA-ROP模型预测每日体重增加少于23g的新生儿发生严重ROP的风险更高。尽管前景乐观,但可能需要更大规模的队列研究来验证和实施针对早产儿的新筛查方法。[《小儿眼科与斜视杂志》。2018;55(5):326 - 334。]

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