Construction and Verification of A Prediction Model of Neonatal Pulmonary Hyaline Membrane Disease Complicated by Bronchopulmonary Dysplasia

Jian YANG; Ping LI; Hongchao JIANG

doi:10.12259/j.issn.2095-610X.S20250611

Volume 46 Issue 6

Jun. 2025

Turn off MathJax

Article Contents

Article Navigation > Journal of Kunming Medical University > 2025 > 46(6): 89-95

Jian YANG, Ping LI, Hongchao JIANG. Construction and Verification of A Prediction Model of Neonatal Pulmonary Hyaline Membrane Disease Complicated by Bronchopulmonary Dysplasia[J]. Journal of Kunming Medical University, 2025, 46(6): 89-95. doi: 10.12259/j.issn.2095-610X.S20250611

Citation:

Jian YANG, Ping LI, Hongchao JIANG. Construction and Verification of A Prediction Model of Neonatal Pulmonary Hyaline Membrane Disease Complicated by Bronchopulmonary Dysplasia[J]. Journal of Kunming Medical University, 2025, 46(6): 89-95. doi: 10.12259/j.issn.2095-610X.S20250611

Citation:

Jian YANG, Ping LI, Hongchao JIANG. Construction and Verification of A Prediction Model of Neonatal Pulmonary Hyaline Membrane Disease Complicated by Bronchopulmonary Dysplasia[J]. Journal of Kunming Medical University, 2025, 46(6): 89-95. doi: 10.12259/j.issn.2095-610X.S20250611

PDF( 812 KB)

Construction and Verification of A Prediction Model of Neonatal Pulmonary Hyaline Membrane Disease Complicated by Bronchopulmonary Dysplasia

doi: 10.12259/j.issn.2095-610X.S20250611

Jian YANG¹,
Ping LI^{1
,
,},
Hongchao JIANG^{2
,
,}

1.
Department of Pediatrics，Kunming First People’s Hospital，Kunming Yunnan 650100
2.
Department of Scientific Research and Education，The Kunming Children’s Hospital，Kunming Yunnan 650228，China

Received Date: 2024-11-16
Publish Date: 2025-06-25

Abstract

Abstract

Objective To investigate the risk factors for bronchopulmonary dysplasia （BPD） in infants with hyaline membrane disease （HMD） and establish a predictive model. Methods A retrospective analysis was conducted on 551 hospitalized HMD infants at Kunming First People’ s Hospital from January 2018 to December 2022. Patients were randomly divided into a training set （n = 413） and a validation set （138） at a 3∶1 ratio. The training set was further divided into a simple HMD group （n = 339） and an HMD with BPD group （n = 74）. Univariate and multivariate Logistic regression prediction models were used to analyze the risk factors associated with HMD complicated by BPD, with subsequent validation in the validation set. Results Univariate analysis showed statistically significant differences between the two groups in birth conditions, perinatal conditions, maternal conditions, laboratory indicators, and treatment conditions （P < 0.05）. Multivariate analysis indicated that birth weight and oxygen exposure time were independent risk factors for HMD complicated by BPD （P < 0.05）. The ROC curve assessment showed an area under the curve （AUC） of 0.954, indicating a certain predictive value for the model. In the validation set, the AUC was 0.917, with a sensitivity of 92.00% and a specificity of 89.38%. Conclusion Neonatal birth weight and duration of oxygen therapy were identified as significant risk factors for bronchopulmonary dysplasia （BPD） complicating hyaline membrane disease （HMD）. The risk prediction model for HMD with BPD has good predictive performance.
- Neonatal hyaline membrane disease,
- Bronchopulmonary dysplasia,
- Risk factors,
- Prediction model

FullText(HTML)

References(22)

References

[1]	李克伟. 新生儿肺透明膜病发病相关因素及临床治疗效果研究[D]. 洛阳: 河南科技大学,2016.
[2]	叶美娜. 新生儿肺透明膜病发生的危险因素及临床治疗效果分析[J]. 当代医药论丛,2023,21(5):46-48. doi: 10.3969/j.issn.2095-7629.2023.05.014
[3]	陈淑珍. 探讨肺表面活性物质联合辅助通气治疗新生儿肺透明膜病的疗效[J]. 中国现代药物应用,2025,19(4):111-114.
[4]	孙文思,张春菊,侯静. 极低出生体质量早产儿肺透明膜病并发支气管肺发育不良的高危因素及相关预防干预措施的研究[J]. 中国妇幼保健,2019,34(11):2537-2539.
[5]	Hintz S R,Van Meurs K P,Perritt R,et al. Neurodevelopmental outcomes of premature infants with severe respiratory failure enrolled in a randomized controlled trial of inhaled nitric oxide[J]. J Pediatr,2007,151(1): 16-22.e223.
[6]	Rutkowska M,Hozejowski R,Helwich E,et al. Severe bronchopulmonary dysplasia - incidence and predictive factors in a prospective,multicenter study in very preterm infants with respiratory distress syndrome[J]. J Matern Fetal Neonatal Med,2019,32(12):1958-1964. doi: 10.1080/14767058.2017.1422711
[7]	许淑静,余增渊. 早产儿支气管肺发育不良与早产儿脑病相关性研究[J]. 中华全科医学,2020,18(5):787-789+793.
[8]	张远方,岳志光. 流量连续气道正压通气呼吸机治疗新生儿肺透明膜病的临床效果[J]. 妇儿健康导刊,2023,2(13):61-63. doi: 10.3969/j.issn.2097-115X.2023.13.whbb202313020
[9]	邵肖梅,叶鸿瑁. "实用新生儿学"第四版出版[J]. 中国实用儿科杂志,2011,(6):458.
[10]	Thebaud B,Goss K N,Laughon M,et al. Bronchopulmonary dysplasia[J]. Nat Rev Dis Primers,2019,5(1):78. doi: 10.1038/s41572-019-0127-7
[11]	赵一品,崔清洋. 超早产儿/超低出生体重儿支气管肺发育不良危险因素分析[J]. 临床荟萃,2025,40(1):60-64. doi: 10.3969/j.issn.1004-583X.2025.01.009
[12]	刘怡波,颜崇兵,张媛洋,等. 早产儿支气管肺发育不良的高危因素临床分析及预测模型构建[J]. 中国当代儿科杂志,2024,26(11):1148-1154. doi: 10.7499/j.issn.1008-8830.2404065
[13]	Jensen E A ,Schmidt B. Epidemiology of bronchopulmonary dysplasia[J]. Birth Defects Res A Clin Mol Teratol,2014,100(3): 145-157.
[14]	El Faleh I,Faouzi M,Adams M,et al. Bronchopulmonary dysplasia: A predictive scoring system for very low birth weight infants. A diagnostic accuracy study with prospective data collection[J]. Eur J Pediatr,2021,180(8):2453-2461. doi: 10.1007/s00431-021-04045-8
[15]	叶柳清,陈广明,李明耀. 肺透明膜病患儿发生支气管肺发育不良的影响因素分析[J]. 临床医学工程,2022,29(2):279-280. doi: 10.3969/j.issn.1674-4659.2022.02.0279
[16]	彭磊,乐功芳,陈绪萍,等. 早产儿支气管肺发育不良的高危因素及防治对策[J]. 临床肺科杂志,2015,(1):92-95.
[17]	李俊峰. 早产极低出生体重儿支气管肺发育不良的危险因素分析探讨[D]. 苏州: 苏州大学,2015.
[18]	Wang J,Dong W. Oxidative stress and bronchopulmonary dysplasia[J]. Gene,2018,678:177-183. doi: 10.1016/j.gene.2018.08.031
[19]	郑壹. 超早产儿支气管肺发育不良的危险因素分析[D]. 温州: 温州医科大学,2023.
[20]	Novitsky A,Tuttle D,Locke R G,et al. Prolonged early antibiotic use and bronchopulmonary dysplasia in very low birth weight infants[J]. Am J Perinatol,2015,32(1):43-48.
[21]	高洁锦,戴欢,凌雅,等. 早产儿肺透明膜病并发支气管肺发育不良的高危因素及预防[J]. 临床儿科杂志,2010,28:1162-1165. doi: 10.3969/j.issn.1000-3606.2010.12.017
[22]	Hernandez-Ronquillo L,Tellez-Zenteno J F,Weder-Cisneros N,et al. Risk factors for the development of bronchopulmonary dysplasia: A case-control study[J]. Arch Med Res,2004,35(6):549-553. doi: 10.1016/j.arcmed.2004.07.001

Relative Articles(20)

Relative Articles

[1]	Jun DENG, Jun WANG, Xi WANG, Change GAO, Xiao CHEN, Mingxia SHI. Prediction Model and Its Value of IrAEs Based on Peripheral Blood Markers. Journal of Kunming Medical University, 2025, 46(4): 57-66. doi: 10.12259/j.issn.2095-610X.S20250408
[2]	Yuanzhen WANG, Hongyan WEI, Renhai TIAN, Yongzhen Chen, Danqing XU, Yingyuan ZHANG, Lixian CHANG, Chunyun LIU, Li LIU. Establishment and Evaluation of a Risk Prediction Model for Chronic Liver Failure Complicated by Primary Hepatocellular Carcinoma Before Intervention. Journal of Kunming Medical University, 2025, 46(3): 139-147. doi: 10.12259/j.issn.2095-610X.S20250321
[3]	Shengxia ZHAO, Peipei LU, Yuan CHEN, Jinping SONG. Risk Factors of Cardiomyopathy in Patients with Diabetes and Their Correlations with the Levels of Serum FOXO1，GDF11 and MMP3. Journal of Kunming Medical University, 2025, 46(8): 78-85. doi: 10.12259/j.issn.2095-610X.S20250811
[4]	Dongyan LIU, Yan LIU, Zhiming REN, Feng WANG, Yong WANG. Analysis of Risk Factors for Chemotherapy Induced Myelosuppression and Construction of Prediction Models for Myelosuppression Based on Logistic Regression Analysis in Cancer Patients. Journal of Kunming Medical University, 2025, 46(8): 108-114. doi: 10.12259/j.issn.2095-610X.S20250815
[5]	Taishan WANG, Guiyang JIA, Guoyue LIU, Erqin SONG, Guizhen YIN. Research Progress on Early Risk Prediction Model of Acute Respiratory Distress Syndrome. Journal of Kunming Medical University, 2025, 46(5): 141-148. doi: 10.12259/j.issn.2095-610X.S20250517
[6]	Enxian ZHU, Ben NIU, Lina TIAN, Yajuan XIE. Risk Factor Analysis of Type 2 Diabetic Peripheral Neuropathy Complicated with Microangiopathy. Journal of Kunming Medical University, 2024, 45(8): 44-51. doi: 10.12259/j.issn.2095-610X.S20240807
[7]	Yanmei JI, Wenjun LI, Qingyun LI, Ni GUO, Ni MENG, Dan ZHOU, Qiuyu LI, Xingfang JIN. The Analysis of Related Factors of Cognitive Impairment after the Acute Ischemic Stroke and Construction of Nomogram Model. Journal of Kunming Medical University, 2024, 45(5): 73-81. doi: 10.12259/j.issn.2095-610X.S20240511
[8]	Huijuan ZENG, Bo TIAN, Hongling YUAN, Jie HE, Guanxi LI, Guojia RU, Min XU, Dong ZHAN. Predictive Modeling of Chronic Kidney Disease with Hypertension or Diabetes Based on Machine Learning Algorithms. Journal of Kunming Medical University, 2024, 45(3): 99-105. doi: 10.12259/j.issn.2095-610X.S20240315
[9]	Qitang LI, Xingfei DAI, Qingdong ZHANG, Rongshuang YAN, Cheng PAN, Derui FEI, Yujian MA, Shixin XU, Ying ZHANG. Histological and Ultrastructural Studies of Lung Tissues in A Piglet Model of Early Onset Scoliosis with Combination of the Thoracic Insufficiency Syndrome. Journal of Kunming Medical University, 2024, 45(5): 23-28. doi: 10.12259/j.issn.2095-610X.S20240504
[10]	Weijie LI, Liqin CHEN, Yaling LI, Yonghui HAN, Xiaojuan LI, Fendong YAN. Epidemiology, Clinical Characteristics and Risk Factors of 148 Severe Pertussis Cases in Yunnan. Journal of Kunming Medical University, 2022, 43(8): 145-149. doi: 10.12259/j.issn.2095-610X.S20220824
[11]	Weimin LU, Xiaotao YANG, Ying ZHU, Yi HUANG, Houyu CHEN, Haifeng JIN, Yanchun WANG. Clinical Features and Risk Factors for Critical Cases of Scrub Typhus in 175 Children. Journal of Kunming Medical University, 2022, 43(8): 72-80. doi: 10.12259/j.issn.2095-610X.S20220814
[12]	Caiying ZHANG, Zhengping KUI, Qiong WANG, Xiaolong ZHAO, Xiaomei HOU, Zhiye QI. Perinatal Risk Factors of Neonatal Hyperthyrotropinemia. Journal of Kunming Medical University, 2022, 43(9): 48-52. doi: 10.12259/j.issn.2095-610X.S20220929
[13]	Min ZHOU, Zhihui MA, Jiayan LI, Jianhua FAN, Ling LIN, Tingying YU, Huifang ZHANG, Li LIU. Predictive Model of Risk Factors for the Recurrence of Liver Cirrhosis with Pleural Effusion. Journal of Kunming Medical University, 2022, 43(5): 149-154. doi: 10.12259/j.issn.2095-610X.S20220524
[14]	Hong WANG, Dexing YANG, Qiang WANG, Weiyu ZHOU, Jiefu TANG, Zhenfang WANG, Kai FU, Shengzhe LIU, Rong LIU. Risk Factors Analysis and Prediction Model Establishment of Refeeding Syndrome in ICU Patients with Sepsis. Journal of Kunming Medical University, 2022, 43(11): 44-51. doi: 10.12259/j.issn.2095-610X.S20221102
[15]	Guimei ZHANG, Shu CHEN, Yunhua SONG, Yang WU, Hongyuan ZHOU. Risk Factors of Readmission in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease and Establishment of Risk Prediction Model. Journal of Kunming Medical University, 2022, 43(8): 184-190. doi: 10.12259/j.issn.2095-610X.S20220830
[16]	Jing WANG, Lian-fang TANG, Mei-qun GU, Xiao-yan XU, Jian-hua YU, Shan HE, Zi-wei LI, Kai BI, Li-qiao LIU, Qiong ZHAO, Hong-ying MI. Risk Factors and Early Clinical Characteristics of Neonatal Necrotizing Enterocolitis. Journal of Kunming Medical University, 2021, 42(11): 99-104. doi: 10.12259/j.issn.2095-610X.S20211118
[17]	Xing LIU, Yuan LIU, Xiang-fang LIU, Jie CHEN, Yong-gang CHEN, Hui SUN, Ling MA. Adverse Reactions Analysis and Prediction Model of Cefoperazone Sodium Sulbactam Sodium. Journal of Kunming Medical University, 2021, 42(6): 139-145. doi: 10.12259/j.issn.2095-610X.S20210622
[18]	Jing-rong DAI, Jie LI, Xu HE, Yang LI, Yan LI. Risk Factors Analysis and Risk Prediction Model Construction of Depression in Inpatients of Geriatrics Department of a Hospital in Yunnan. Journal of Kunming Medical University, 2021, 42(11): 20-26. doi: 10.12259/j.issn.2095-610X.S20211104
[19]	Li Yan Yuan . . Journal of Kunming Medical University,
[20]	Zhu Jing . The Potential Risk Factors Analysis of HIV/STD Infection in Vietnamese Cross-border Female Sex Workers. Journal of Kunming Medical University,