Shen Leilei, Zheng Ruixue, Sun Xiaodong, Chen Sheng
Department of Pediatrics, Third Military Medical University Southwest Hospital, Chongqing, China.
Front Pediatr. 2025 May 9;13:1576979. doi: 10.3389/fped.2025.1576979. eCollection 2025.
To delineate risk factors and develop a predictive nomogram for retinopathy of prematurity (ROP) in infants with gestational age (GA) ≤34 weeks.
We conducted a comprehensive retrospective analysis of infants with GA ≤34 weeks, divided into ROP and non-ROP groups based on fundus screening results. Clinical and laboratory data were collected to identify risk factors associated with ROP. Multivariable logistic regression was performed to identify independent predictors, and a nomogram was developed to predict the occurrence of ROP in infants with GA ≤34 weeks.
Our analysis identified five independent risk factors for ROP in infants with GA ≤34 weeks: hypertensive disorders of pregnancy (HDP), number of blood transfusions, oxygen therapy time (OTT), oxygen therapy concentration (OTC) >50%, and blood glucose spikes in the first postnatal week. These predictors were incorporated into a nomogram to estimate individual ROP risk. The predictive model achieved a C-index of 0.923 (95% CI: 0.888-0.959), indicating high predictive accuracy. Internal validation of the nomogram demonstrated excellent calibration and practical utility for clinical decision-making.
The established predictive model, incorporating five key clinical parameters, offers clinicians a practical instrument to stratify ROP risk in neonates born at ≤34 weeks' gestation. This clinical tool demonstrates significant utility in guiding intervention protocols, potentially enhancing patient outcomes through early identification and optimized management strategies.
ChiCTR2400086213.
明确胎龄(GA)≤34周婴儿发生早产儿视网膜病变(ROP)的危险因素,并建立预测列线图。
我们对GA≤34周的婴儿进行了全面的回顾性分析,根据眼底筛查结果将其分为ROP组和非ROP组。收集临床和实验室数据以确定与ROP相关的危险因素。进行多变量逻辑回归以确定独立预测因素,并建立列线图以预测GA≤34周婴儿发生ROP的情况。
我们的分析确定了GA≤34周婴儿发生ROP的五个独立危险因素:妊娠高血压疾病(HDP)、输血次数、氧疗时间(OTT)、氧疗浓度(OTC)>50%以及出生后第一周的血糖峰值。这些预测因素被纳入列线图以估计个体ROP风险。预测模型的C指数为0.923(95%CI:0.888-0.959),表明预测准确性高。列线图的内部验证显示出良好的校准和临床决策实用性。
所建立的包含五个关键临床参数的预测模型为临床医生提供了一种实用工具,用于对胎龄≤34周出生的新生儿的ROP风险进行分层。这一临床工具在指导干预方案方面具有显著实用性,可能通过早期识别和优化管理策略提高患者预后。
ChiCTR2400086213。