Shen Fei, Xu Jie, Rong Hui, Zhang Jing, Yang Yang, Li Xian-Wen
Department of Neonatology, Children's Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
School of Nursing, Nanjing Medical University, Nanjing, People's Republic of China.
Kaohsiung J Med Sci. 2025 Jul;41(7):e70037. doi: 10.1002/kjm2.70037. Epub 2025 May 19.
In the past several years, prediction models for severe intraventricular hemorrhage (IVH) in premature infants have emerged. However, few models have considered the importance of predictors related to the clinical course and hemostatic profile in predicting the risk of hemorrhage, such as the FiO, hematocrit, and platelet count. Moreover, it is noteworthy that most models unreasonably confuse late-onset IVH with early-onset, posing a high risk of bias. The present study was performed to construct a new prediction model for severe IVH. The data for this population-based study came from a children's hospital. After screening by inclusion and exclusion criteria, 1009 very low birth weight infants (VLBWIs) were subsequently recruited in the study and divided into training and validation sets in a ratio of 7:3. Gestational age, Max FiO, hematokrit on admission < 45%, and platelet count on admission < 100 × 10/L were incorporated into the nomogram chart. The area under the curve (AUC) values demonstrated robust predictive performance, with the training set yielding an AUC of 0.884 (bootstrap-corrected AUC = 0.903) and the validation set achieving an AUC of 0.859. The Delong test showed no statistically significant difference in AUCs between the training set and validation set (p = 0.528). The result of the Hosmer-Lemeshow test showed the model is well calibrated (p = 0.757). The present study identified the predictor model associated with severe IVH during the first 7 days of life, and the nomogram performed soundly, which would be a promising tool for early stratification of the risk for severe IVH in VLBWIs.
在过去几年中，早产儿严重脑室内出血（IVH）的预测模型不断涌现。然而，很少有模型在预测出血风险时考虑到与临床病程和止血情况相关的预测因素的重要性，如吸入氧分数（FiO₂）、血细胞比容和血小板计数。此外，值得注意的是，大多数模型不合理地将晚发型IVH与早发型IVH混为一谈，存在较高的偏倚风险。本研究旨在构建一种新的严重IVH预测模型。这项基于人群的研究数据来自一家儿童医院。经纳入和排除标准筛选后，1009例极低出生体重儿（VLBWIs）随后被纳入研究，并按7:3的比例分为训练集和验证集。将胎龄、最高FiO₂、入院时血细胞比容<45%以及入院时血小板计数<100×10⁹/L纳入列线图。曲线下面积（AUC）值显示出强大的预测性能，训练集的AUC为0.884（自抽样校正AUC = 0.903），验证集的AUC为0.859。德龙检验显示训练集和验证集的AUC之间无统计学显著差异（p = 0.528）。霍斯默-莱梅肖检验结果表明该模型校准良好（p = 0.757）。本研究确定了与出生后7天内严重IVH相关的预测模型，列线图表现良好，这将是对VLBWIs严重IVH风险进行早期分层的一个有前景的工具。
