超早产儿纵向宫外生长迟缓现状调查及预测模型的建立  

Longitudinal extrauterine growth restriction in extremely preterm infants:current status and prediction model

作　　者：黄晓芳[1] 冯琪[1] 李帅军 田秀英[3] 冀湧[4] 周颖[5] 田渤 李月梅[7] 郭玮[8] 翟淑芬[9] 何海英 刘霞[11] 郑荣秀[12] 樊沙沙 马莉[14] 王红云 王晓颖[16] 黄山雅美[17] 李巾宇 谢华 李晓香 张平平[21] 梅花[22] 胡艳菊 杨明[24] 陈璐[25] 李亚静 谷晓虹 阙生顺 闫小仙 王海娟[30] 孙丽霞 张亮[32] 郭九叶[33] Huang Xiaofang;Feng Qi;Li Shuaijun;Tian Xiuying;Ji Yong;Zhou Ying;Tian Bo;Li Yuemei;Guo Wei;Zhai Shufen;He Haiying;Liu Xia;Zheng Rongxiu;Fan Shasha;Ma Li;Wang Hongyun;Wang Xiaoying;Huang Shanyamei;Li Jinyu;Xie Hua;Li Xiaoxiang;Zhang Pingping;Mei Hua;Hu Yanju;Yang Ming;Chen Lu;Li Yajing;Gu Xiaohong;Que Shengshun;Yan Xiaoxian;Wang Haijuan;Sun Lixia;Zhang Liang;Guo Jiuye(Department of Pediatrics,Peking University First Hospital,Beijing 100034,China;Department of Maternal and Child Health,School of Public Health,Peking University,Beijing 100191,China;Department of Neonatology,Tianjin Central Hospital of Obstetrics and Gynecology,Tianjin 300100,China;Department of Pediatrics,Shanxi Children's Hospital,Taiyuan 030013,China;Department of Pediatrics,Peking University Third Hospital,Beijing 100191,China;Department of Pediatrics,Tangshan Maternal and Child Health Hospital,Tangshan 063000,China;Department of Pediatrics,the Second Hospital of Hebei Medical University,Shijiazhuang 050000,China;Department of Pediatrics,Xingtai People's Hospital,Xingtai 054031,China;Department of Pediatrics,Handan Central Hospital,Handan 056000,China;Department of Pediatrics,Baogang Third Hospital of Hongci Group,Baotou 014010,China;Department of Pediatrics,Affiliated Hospital of Chengde Medical College,Chengde 067000,China;Department of Pediatrics,Tianjin Medical University General Hospital,Tianjin 300052,China;Department of Pediatrics,the First Hospital of Tsinghua University,Beijing 100016,China;Department of Pediatrics,Hebei Children's Hospital,Shijiazhuang 050031,China;Department of Pediatrics,Inner Mongolia Maternal and Child Health Hospital,Hohhot 010020,China;Department of Neonatology,Children's Hospital,Capital Institute of Pediatrics,Beijing 100020,China;Department of Pediatrics,Peking University People's Hospital,Beijing 100044,China;Department of Pediatrics,Peking Union Medical College Hospital,Beijing 100730,China;Department of Pediatrics,Affiliated Hospital of Chifeng University,Chifeng 024000,China;Department of Pediatrics,Beijin

机构地区：[1]北京大学第一医院儿科,北京100034 [2]北京大学公共卫生学院妇幼卫生学系,北京100191 [3]天津市中心妇产科医院新生儿科,天津300100 [4]山西省儿童医院儿科,太原030013 [5]北京大学第三医院儿科,北京100191 [6]唐山市妇幼保健院儿科,唐山063000 [7]河北医科大学第二医院儿科,石家庄050000 [8]河北省邢台市人民医院儿科,邢台054031 [9]河北省邯郸市中心医院儿科,邯郸056000 [10]弘慈医疗集团包钢三医院儿科,包头014010 [11]承德医学院附属医院儿科,承德067000 [12]天津医科大学总医院儿科,天津300052 [13]清华大学第一附属医院儿科,北京100016 [14]河北省儿童医院儿科,石家庄050031 [15]内蒙古自治区妇幼保健院儿科,呼和浩特010020 [16]首都儿科研究所附属儿童医院新生儿内科,北京100020 [17]北京大学人民医院儿科,北京100044 [18]中国医学科学院北京协和医院儿科,北京100730 [19]赤峰学院附属医院儿科,赤峰024000 [20]首都医科大学附属北京潞河医院儿科,北京101100 [21]天津市第一中心医院新生儿科,天津300190 [22]内蒙古医科大学附属医院儿科,呼和浩特010050 [23]内蒙古兴安盟人民医院儿科,乌兰浩特137400 [24]北京和睦家医院儿科,北京100015 [25]首都医科大学附属北京儿童医院新生儿科,北京100045 [26]首都医科大学附属北京友谊医院儿科,北京100050 [27]张家口市妇幼保健院儿科,张家口075000 [28]天津医科大学第二医院儿科,天津300211 [29]山西省汾阳医院儿科,汾阳032200 [30]保定市妇幼保健院儿科,保定071000 [31]山西省太原市妇幼保健医院儿科,太原030012 [32]赤峰市医院儿科,赤峰024000 [33]北京市朝阳区妇幼保健院儿科,北京100020

出　　处：《中华新生儿科杂志（中英文）》2024年第3期136-144,共9页Chinese Journal of Neonatology

摘　　要：目的基于新生儿重症监护室(neonatal intensive care unit,NICU)的多中心数据,进行胎龄<28周超早产儿(extremely preterm infants,EPIs)纵向宫外生长迟缓(extrauterine growth restriction,EUGR)现状调查,并建立预测模型。方法回顾性研究2017年1月至2018年12月华北地区32个NICU收治的EPIs一般情况、营养支持、住院期间并发症及体重增长情况等临床资料。出院体重Z评分较入院时下降>1定义为纵向EUGR,将EPIs分为纵向EUGR组及非纵向EUGR组,总结EPIs营养支持及体重增长现状。将EPIs按7∶3的比例随机分为训练集和验证集。在训练集中采用单因素和多因素回归分析筛选纵向EUGR的独立危险因素,利用赤池信息准则决定最优Nomogram模型并绘制列线图。对模型进行区分度、校准度和临床决策曲线评价。结果共纳入436例EPIs,胎龄(26.9±0.9)周,出生体重(989±171)g,纵向RUGR发生率82.3%(359/436)。最终纳入出生体重Z评分、体重下降程度、体重增长速率、出院前3 d母乳喂养比例≥75%、机械通气≥7 d、母亲完成产前促肺治疗、支气管肺发育不良7个变量构建列线图。训练集和验证集的受试者工作特征曲线下面积分别为0.870(95%CI 0.820~0.920)和0.879(95%CI 0.815~0.942),提示模型区分度良好。校准曲线提示模型存在较好的拟合度(P>0.05)。临床决策曲线分析表明模型在所有阈值下均有正向获益。结论目前EPIs纵向ERGR发生率较高,本研究构建并验证了EPIs出院时纵向EUGR的预测模型,有助于尽早识别纵向EUGR高危的EPIs并进行干预。未来研究有必要扩大样本量和进行前瞻性研究来优化和验证该预测模型。Objective To study the current status of longitudinal extrauterine growth restriction(EUGR)in extremely preterm infants(EPIs)and to develop a prediction model based on clinical data from multiple NICUs.Methods From January 2017 to December 2018,EPIs admitted to 32 NICUs in North China were retrospectively studied.Their general conditions,nutritional support,complications during hospitalization and weight changes were reviewed.Weight loss between birth and discharge>1SD was defined as longitudinal EUGR.The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared.The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3.Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors.The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion.The model was evaluated for discrimination efficacy,calibration and clinical decision curve analysis.Results A total of 436 EPIs were included in this study,with a mean gestational age of(26.9±0.9)weeks and a birth weight of(989±171)g.The incidence of longitudinal EUGR was 82.3%(359/436).Seven variables(birth weight Z-score,weight loss,weight growth velocity,the proportion of breast milk≥75%within 3 d before discharge,invasive mechanical ventilation≥7 d,maternal antenatal corticosteroids use and bronchopulmonary dysplasia)were selected to establish the prediction model.The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870(95%CI 0.820-0.920)and 0.879(95%CI 0.815-0.942),suggesting good discrimination efficacy.The calibration curve indicated a good fit of the model(P>0.05).The decision curve analysis showed positive net benefits at all thresholds.Conclusions Currently,EPIs have a high incidence of longitudinal EUGR.The prediction model is helpful for ear

关 键 词：纵向 宫外生长迟缓 现状 预测模型 超早产儿 

分 类 号：R722.6[医药卫生—儿科]