新生儿坏死性小肠结肠炎（necrotizing enterocolitis, NEC）是一种威胁早产儿生命的急性胃肠道重症，以高发病率和高病死率为特征。20%~60%的NEC患儿因肠穿孔或内科治疗无效需接受急诊外科手术干预，肠穿孔后接受外科手术的患儿死亡风险显著增高。然而，传统影像学检查和生物标志物对手术时机的预测效能欠佳。近年来，多模态影像学技术、新型生物标志物及机器学习算法在NEC手术时机预测中较传统检查方法和临床指标展现出更高的预测价值。该文就NEC手术时机预测研究的新进展作一综述。

Neonatal necrotizing enterocolitis (NEC) is a life-threatening acute gastrointestinal disorder in preterm infants, characterized by high morbidity and mortality. Approximately 20%-60% of infants with NEC require emergency surgical intervention due to intestinal perforation or failure of medical management, and mortality risk increases markedly when surgery follows perforation. Traditional imaging and biomarkers have limited performance in predicting surgical timing. In recent years, multimodal imaging technologies, novel biomarkers, and machine learning algorithms have shown higher predictive value than conventional tests and clinical indicators for determining surgical timing in NEC. This review summarizes recent advances in predictive methodologies for surgical decision-making in NEC.