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Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g

INTRODUCTION: Moderate and severe bronchopulmonary dysplasia (BPD) is a common pulmonary complication in premature infants, which seriously affects their survival rate and quality of life. This study aimed to describe the mechanical ventilation characteristics and evaluate their prediction performan...

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Autores principales: Yin, Jing, Liu, Linjie, Li, Huimin, Hou, Xuewen, Chen, Jingjing, Han, Shuping, Chen, Xiaohui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666736/
https://www.ncbi.nlm.nih.gov/pubmed/36405843
http://dx.doi.org/10.3389/fped.2022.993167
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author Yin, Jing
Liu, Linjie
Li, Huimin
Hou, Xuewen
Chen, Jingjing
Han, Shuping
Chen, Xiaohui
author_facet Yin, Jing
Liu, Linjie
Li, Huimin
Hou, Xuewen
Chen, Jingjing
Han, Shuping
Chen, Xiaohui
author_sort Yin, Jing
collection PubMed
description INTRODUCTION: Moderate and severe bronchopulmonary dysplasia (BPD) is a common pulmonary complication in premature infants, which seriously affects their survival rate and quality of life. This study aimed to describe the mechanical ventilation characteristics and evaluate their prediction performance for the risk of moderate and severe BPD in infants with gestational age <30 weeks and birth weight <1,500 g on postnatal Day 14. METHODS: In this retrospective cohort study, 412 infants with gestational age <30 weeks and birth weight <1,500 g were included in the analysis, including 104 infants with moderate and severe BPD and 308 infants without moderate and severe BPD (as controls). LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomograms were developed visually using the selected variables. To validate the model, receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used. RESULTS: From the original 28 variables studied, six predictors, namely birth weight, 5 min apgar score, neonatal respiratory distress syndrome (≥Class II), neonatal pneumonia, duration of invasive mechanical ventilation (IMV) and maximum of FiO(2) (fraction of inspiration O(2)) were identified by LASSO regression analysis. The model constructed using these six predictors and a proven risk factor (gestational age) displayed good prediction performance for moderate and severe BPD, with an area under the ROC of 0.917 (sensitivity = 0.897, specificity = 0.797) in the training set and 0.931 (sensitivity = 0.885, specificity = 0.844) in the validation set, and was well calibrated (P(Hosmer-Lemeshow test )= 0.727 and 0.809 for the training and validation set, respectively). CONCLUSION: The model included gestational age, birth weight, 5 min apgar score, neonatal respiratory distress syndrome (≥Class II), neonatal pneumonia, duration of IMV and maximum of FiO(2) had good prediction performance for predicting moderate and severe BPD in infants with gestational age <30 weeks and birth weight <1,500 g on postnatal Day 14.
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spelling pubmed-96667362022-11-17 Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g Yin, Jing Liu, Linjie Li, Huimin Hou, Xuewen Chen, Jingjing Han, Shuping Chen, Xiaohui Front Pediatr Pediatrics INTRODUCTION: Moderate and severe bronchopulmonary dysplasia (BPD) is a common pulmonary complication in premature infants, which seriously affects their survival rate and quality of life. This study aimed to describe the mechanical ventilation characteristics and evaluate their prediction performance for the risk of moderate and severe BPD in infants with gestational age <30 weeks and birth weight <1,500 g on postnatal Day 14. METHODS: In this retrospective cohort study, 412 infants with gestational age <30 weeks and birth weight <1,500 g were included in the analysis, including 104 infants with moderate and severe BPD and 308 infants without moderate and severe BPD (as controls). LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomograms were developed visually using the selected variables. To validate the model, receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used. RESULTS: From the original 28 variables studied, six predictors, namely birth weight, 5 min apgar score, neonatal respiratory distress syndrome (≥Class II), neonatal pneumonia, duration of invasive mechanical ventilation (IMV) and maximum of FiO(2) (fraction of inspiration O(2)) were identified by LASSO regression analysis. The model constructed using these six predictors and a proven risk factor (gestational age) displayed good prediction performance for moderate and severe BPD, with an area under the ROC of 0.917 (sensitivity = 0.897, specificity = 0.797) in the training set and 0.931 (sensitivity = 0.885, specificity = 0.844) in the validation set, and was well calibrated (P(Hosmer-Lemeshow test )= 0.727 and 0.809 for the training and validation set, respectively). CONCLUSION: The model included gestational age, birth weight, 5 min apgar score, neonatal respiratory distress syndrome (≥Class II), neonatal pneumonia, duration of IMV and maximum of FiO(2) had good prediction performance for predicting moderate and severe BPD in infants with gestational age <30 weeks and birth weight <1,500 g on postnatal Day 14. Frontiers Media S.A. 2022-11-02 /pmc/articles/PMC9666736/ /pubmed/36405843 http://dx.doi.org/10.3389/fped.2022.993167 Text en © 2022 Yin, Liu, Li, Hou, Chen, Han and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pediatrics
Yin, Jing
Liu, Linjie
Li, Huimin
Hou, Xuewen
Chen, Jingjing
Han, Shuping
Chen, Xiaohui
Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
title Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
title_full Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
title_fullStr Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
title_full_unstemmed Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
title_short Mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
title_sort mechanical ventilation characteristics and their prediction performance for the risk of moderate and severe bronchopulmonary dysplasia in infants with gestational age <30 weeks and birth weight <1,500 g
topic Pediatrics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666736/
https://www.ncbi.nlm.nih.gov/pubmed/36405843
http://dx.doi.org/10.3389/fped.2022.993167
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