ABSTRACT

Purpose

The G-ROP model was proposed to improve the retinopathy of prematurity (ROP) screening efficiency. It is based on gestational age, birth weight and postnatal weight gain. The current study aimed to validate the G-ROP model's ability to predict ROP in cohorts of premature infants from Egypt and the United Kingdom (UK).

Methods

We retrospectively reviewed the records of preterm infants born between 1st of January and 30th of June 2018 with a known outcome for ROP screening and regular weight measurements until day 39 after birth. We applied the G-ROP model to the study group and calculated the sensitivity of the model for detecting Early Treatment of ROP (ETROP) study type 1 ROP and for any ROP and calculated the reduction of the number of infants requiring ROP screening by the model application.

Results

We applied the G-ROP model on 605 infants (504 from Egypt and 101 from the UK). The model successfully predicted all type 1 ROP cases (100% sensitivity) in both cohorts (95% confidence interval [CI], 91.1–100% in the Egyptian cohort and 65.5–100% in the UK cohort). The model reduced the number of infants requiring screening by 14.1% in the Egyptian cohort and 21.8% in the UK cohort.

Conclusions

The G-ROP model was successfully validated for detecting type 1 ROP and in both cohorts from Egypt and the UK.

中文翻译：

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早产儿模型的产后生长和视网膜病变：一项多机构验证研究

摘要

目的

提出G-ROP模型以提高早产儿视网膜病变（ROP）的筛查效率。它基于胎龄、出生体重和出生后体重增加。目前的研究旨在验证 G-ROP 模型在来自埃及和英国 (UK) 的早产儿队列中预测 ROP 的能力。

方法

我们回顾性审查了 2018 年 1 月 1 日至 6 月 30 日期间出生的早产儿的记录，这些早产儿的 ROP 筛查和定期体重测量结果已知，直到出生后第 39 天。我们将 G-ROP 模型应用于研究组，并计算了模型检测 ROP 早期治疗 (ETROP) 研究 1 型 ROP 和任何 ROP 的敏感性，并计算了该模型需要 ROP 筛查的婴儿数量的减少应用。

结果

我们将 G-ROP 模型应用于 605 名婴儿（504 名来自埃及，101 名来自英国）。该模型成功预测了两个队列中的所有 1 型 ROP 病例（100% 敏感性）（95% 置信区间 [CI]，埃及队列为 91.1-100%，英国队列为 65.5-100%）。该模型将需要筛查的婴儿数量在埃及队列中减少了 14.1%，在英国队列中减少了 21.8%。

结论

G-ROP 模型已成功验证用于检测 1 型 ROP，并在来自埃及和英国的两个队列中进行了验证。