目的 探讨脐血S100β蛋白、乳酸联合改良Kidokoro磁共振评分(简称改良Kidokoro评分)在中晚期早产儿神经发育障碍早期预测中的应用价值,为临床早期识别高危患儿、制定干预策略提供依据。方法 采用回顾性研究,选取2024年1月—2025年1月晋江市医院收治的127例中晚期早产儿为研究对象。所有早产儿在矫正6月龄时采用0~6岁儿童神经心理发育量表进行神经行为发育评估。按照评估结果分为神经发育障碍组(<85分,16例)和神经发育正常组(≥85分,111例),收集两组早产儿的临床资料、脐血S100β及乳酸,生后7~14天行头颅MRI检查,采用改良后的Kidokoro评分系统对脑白质、灰质及脑室系统进行定量评分,通过受试者工作特征(ROC)曲线分析各指标对中晚期早产儿脑损伤的预测效能。结果 神经发育障碍组患儿脐血S100β蛋白(t=2.732)、乳酸(t=2.576)及改良Kidokoro评分(t=7.531)均显著高于神经发育正常组(P<0.05)。ROC曲线分析显示脐血S100β蛋白、乳酸及改良Kidokoro评分单独预测中晚期早产儿脑损伤的曲线下面积(AUC)分别为0.719(95%CI:0.569~0.870)、0.686(95%CI:0.547~0.825)、0.918(95%CI:0.830~1.000)。基于S100β蛋白、乳酸、改良Kidokoro评分及胎龄构建的联合预测模型中,人工神经网络预测效能最优(AUC=0.937),准确率为0.962,灵敏度为0.850、特异度为0.982。结论 脐血S100β蛋白、乳酸联合改良Kidokoro评分可显著提高对中晚期早产儿神经发育障碍的早期预测效能,为临床早期干预提供可靠的实验室及影像学依据。
Abstract
Objective To investigate the early predictive value of cord blood S100β protein and lactate combined with the modified Kidokoro magnetic resonance imaging (MRI) score (the modified Kidokoro score) for neurodevelopmental disorders at 6 months of corrected age in moderate and late preterm infants. Methods A retrospective analysis was conducted on the clinical data of 127 moderate-to-late preterm infants admitted to Jinjiang Municipal Hospital between January 2024 and January 2025. Using the Neuropsychological Developmental Scale for Children Aged 0 - 6 Years, infants were assessed at corrected age of 6 months and categorized into neurodevelopmental disorder group (n=16) and normal neurodevelopment group (n=111). Clinical data, cord blood S100β protein and lactate levels of the preterm infants were collected. Cranial MRI was performed 7 - 14 days after birth, and brain abnormalities were quantitatively evaluated using the modified Kidokoro scoring system. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of individual and combined biomarker testing for brain injury in mid-to-late term preterm infants. Results The levels of umbilical cord blood S100β protein (t=2.732) and lactate (t=2.576), as well as the modified Kidokoro scores (t=7.531), were significantly higher in the neurodevelopmental disorder group than in the normal group (P<0.05). ROC curve analysis showed that the areas under the curve (AUC) of cord blood S100β protein, lactate and the modified Kidokoro score alone for predicting neurodevelopmental disorders were 0.719 (95%CI: 0.569 - 0.870), 0.686 (95%CI: 0.547 - 0.825) and 0.918 (95%CI: 0.830 - 1.000), respectively. Among the machine learning algorithms, the artificial neural network (ANN) model, combining gestational age, lactate, S100β and the modified Kidokoro score, demonstrated the optimal predictive performance, with an AUC of 0.937, accuracy of 0.962, sensitivity of 0.850, and specificity of 0.982. Conclusion The combination of umbilical cord blood S100β protein, lactate, and the modified Kidokoro score effectively improves the early prediction of neurodevelopmental disorders in moderate-to-late preterm infants, which may provide reliable laboratory and imaging basis for early clinical intervention.
关键词
中晚期早产儿 /
神经发育障碍 /
S100β蛋白 /
乳酸 /
改良 Kidokoro磁共振评分 /
早期预测
Key words
moderate and late preterm infants /
neurodevelopmental disorders /
S100β protein /
lactate /
modified Kidokoro magnetic resonance score /
early prediction
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参考文献
[1] Rite Gracia S, Agüera Arenas JJ, Ginovart Galiana G, et al. Management of respiratory distress syndrome in moderate/late preterm neonates: A Delphi consensus[J]. An De Pediatría(Engl Ed), 2024, 101(5): 319-330.
[2] Xu L, Cheng J, Dong X, et al. Associations of prenatal blood pressure trajectory and variability with child neurodevelopment at 2 years old[J]. BMC Med, 2024, 22(1): 220.
[3] Necula AI, Stoiciu R, Radulescu Botica R, et al. Neurological outcomes in late preterm infants: An updated review of recent research and clinical insights[J]. Diagnostics, 2025, 15(12): 1514.
[4] Griesmaier E, Schreiner C, Winkler I, et al. Association of aEEG and brain injury severity on MRI at term-equivalent age in preterm infants[J]. Acta Paediatr, 2024, 113(2): 229-238.
[5] Chen SL, Zhao JZ, Hu XL, et al. Children neuropsychological and behavioral scale-revision 2016 in the early detection of autism spectrum disorder[J]. Front Psychiatry, 2022(13): 893226.
[6] 张沂洁, 朱燕, 陈超. 早产儿发生率及变化趋势[J].中华新生儿科杂志, 2021, 36(4): 74-77.
[7] Sharma D, Padmavathi IV,Tabatabaii SA, et al. Late preterm: A new high risk group in neonatology[J]. J Matern Fetal Neonatal Med, 2021, 34(16): 2717-2730.
[8] Gill JV, Boyle EM. Outcomes of infants born near term[J]. Arch Dis Child, 2017, 102(2): 194-198.
[9] Dewan MV, Weber PD, Felderhoff-Mueser U, et al. A simple MRI score predicts pathological general movements in very preterm infants with brain injury—Retrospective cohort study[J]. Children, 2024, 11(9): 1067.
[10] Song IG.Neurodevelopmental outcomes of preterm infants[J].Clin Exp Pediatr, 2023, 66(7): 281-287.
[11] 傅慧青, 黄为民, 陈志权, 等. 婴儿运动表现测试联合全身运动评估及头颅磁共振成像对早产儿神经运动发育结局的预测价值[J].川北医学院学报, 2024, 39(9): 1171-1175.
Fu HQ, Huang WM, Chen ZQ, et al. Analysis of the predictive value of infant motor performance tests combined with GMs and cranial MRI for neuromotor developmental outcomes in preterm infants[J].Journal of North Sichuan Medical College, 2024, 39(9): 1171-1175. (in Chinese)
[12] Ueda K, Tsuda K, Yamada T, et al. Incidence andrisk factors of white matter lesions in moderate and late preterm infants[J]. Diagnostics, 2025, 15(7): 881.
[13] Wang Y, Zhu J, Zou N, et al. Pathogenesis fromthe microbial-gut-brain axis in white matter injury in preterm infants: A review[J]. Front Integr Neurosci, 2023, 17: 1051689.
[14] Cho KHT, Xu B, Blenkiron C, et al. Emergingroles of miRNAs in brain development and perinatal brain injury[J]. Front Physiol, 2019(10): 227.
[15] Crowther CA, Ashwood P, Middleton PF, et al. Prenatalintravenous magnesium at 30 to 34 weeks' gestation and neurodevelopmental outcomes in offspring: The MAGENTA randomized clinical trial[J]. Obstet Anesth Dig, 2024, 44(2): 94.
[16] Strzalko B,Karowicz-Bilinska A,Wyka K,et al.Serum S100β protein concentrations in SGA/FGR newborns[J]. Ginekol Pol,2021. doi: 10.5603/gp.a2021.0119.
[17] Ladyman SR,Larsen CM,Taylor RS.et al. Case-control study of prolactin and placental lactogen in SGA pregnancies[J].Reprod Fertil,2021,2(4):244-250.
[18] Velipaşaoğlu M, Yurdakök M, Özyüncü Ö, et al. Neural injury markers to predict neonatal complications in intrauterine growth restriction[J]. J Obstet Gynaecol, 2015, 35(6): 555-560.
[19] Perrone S, Grassi F, Caporilli C, et al. Brain damage in preterm and full-term neonates: Serum biomarkers for the early diagnosis and intervention[J]. Antioxidants, 2023, 12(2): 309.
[20] Qian J, Zhou D, Wang YW. Umbilical artery blood S100β protein: A tool for the early identification of neonatal hypoxic-ischemic encephalopathy[J]. Eur J Pediatr, 2009, 168(1): 71-77.
[21] Pellkofer Y, Hammerl M, Griesmaier E, et al. The effect of postnatal cytomegalovirus infection on (micro)structural cerebral development in very preterm infants at term-equivalent age[J]. Neonatology, 2023, 120(6): 727-735.
[22] Yin J, Wu Y, Shi Y, et al. Relationship between the quantitative indicators of cranial MRI and the early neurodevelopment of preterm infants[J]. Comput Math Methods Med, 2021, 2021: 6486452.
[23] Badr EA, Ismail MS. Neurobehavioral outcome of multi-sensory stimulation intervention in preterm neonates: Randomised controlled trial[J]. J Neonatal Nurs, 2024, 30(6): 661-667.
基金
泉州市科技计划项目(2023NS097);泉州市科技计划项目(2023C014YR)