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Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information

IMPORTANCE: Early assessment of the prognosis of preterm newborns is crucial for accurately informing parents and making treatment decisions. The currently available prognostic models rarely incorporate functional brain information from conventional electroencephalography (cEEG). OBJECTIVE: To exami...

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Autores principales: Routier, Laura, Querne, Laurent, Ghostine-Ramadan, Ghida, Boulesteix, Julie, Graïc, Solène, Mony, Sandrine, Wallois, Fabrice, Bourel-Ponchel, Emilie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996404/
https://www.ncbi.nlm.nih.gov/pubmed/36884252
http://dx.doi.org/10.1001/jamanetworkopen.2023.1590
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author Routier, Laura
Querne, Laurent
Ghostine-Ramadan, Ghida
Boulesteix, Julie
Graïc, Solène
Mony, Sandrine
Wallois, Fabrice
Bourel-Ponchel, Emilie
author_facet Routier, Laura
Querne, Laurent
Ghostine-Ramadan, Ghida
Boulesteix, Julie
Graïc, Solène
Mony, Sandrine
Wallois, Fabrice
Bourel-Ponchel, Emilie
author_sort Routier, Laura
collection PubMed
description IMPORTANCE: Early assessment of the prognosis of preterm newborns is crucial for accurately informing parents and making treatment decisions. The currently available prognostic models rarely incorporate functional brain information from conventional electroencephalography (cEEG). OBJECTIVE: To examine the performance of a multimodal model combining (1) brain function information with (2) brain structure information (cranial ultrasonography), and (3) perinatal and (4) postnatal risk factors for the prediction of death or neurodevelopmental impairment (NDI) in extremely preterm infants. DESIGN, SETTING, AND PARTICIPANTS: Preterm newborns (23-28 weeks’ gestational age) admitted to the neonatal intensive care unit at Amiens-Picardie University Hospital were retrospectively included (January 1, 2013, to January 1, 2018). Risk factors from the 4 categories were collected during the first 2 weeks post delivery. Neurodevelopmental impairment was assessed at age 2 years with the Denver Developmental Screening Test II. No or moderate NDI was considered a favorable outcome. Death or severe NDI was considered an adverse outcome. Data analysis was performed from August 26, 2021, to March 31, 2022. MAIN OUTCOMES AND MEASURES: After the selection of variables significantly associated with outcome, 4 unimodal prognostic models (considering each category of variable independently) and 1 multimodal model (considering all variables simultaneously) were developed. After a multivariate analysis for models built with several variables, decision-tree algorithms were run on each model. The areas under the curve for decision-tree classifications of adverse vs favorable outcomes were determined for each model, compared using bootstrap tests, and corrected for type I errors. RESULTS: A total of 109 newborns (58 [53.2% male]) born at a mean (SD) gestational age of 26.3 (1.1) weeks were included. Among them, 52 (47.7%) had a favorable outcome at age 2 years. The multimodal model area under the curve (91.7%; 95% CI, 86.4%-97.0%) was significantly higher than those of the unimodal models (P < .003): perinatal model (80.6%; 95% CI, 72.5%-88.7%), postnatal model (81.0%; 95% CI, 72.6%-89.4%), brain structure model (cranial ultrasonography) (76.6%; 95% CI, 67.8%-85.3%), and brain function model (cEEG) (78.8%; 95% CI, 69.9%-87.7%). CONCLUSIONS AND RELEVANCE: In this prognostic study of preterm newborns, the inclusion of brain information in a multimodal model was associated with significant improvement in the outcome prediction, which may have resulted from the complementarity of the risk factors and reflected the complexity of the mechanisms that interfered with brain maturation and led to death or NDI.
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spelling pubmed-99964042023-03-10 Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information Routier, Laura Querne, Laurent Ghostine-Ramadan, Ghida Boulesteix, Julie Graïc, Solène Mony, Sandrine Wallois, Fabrice Bourel-Ponchel, Emilie JAMA Netw Open Original Investigation IMPORTANCE: Early assessment of the prognosis of preterm newborns is crucial for accurately informing parents and making treatment decisions. The currently available prognostic models rarely incorporate functional brain information from conventional electroencephalography (cEEG). OBJECTIVE: To examine the performance of a multimodal model combining (1) brain function information with (2) brain structure information (cranial ultrasonography), and (3) perinatal and (4) postnatal risk factors for the prediction of death or neurodevelopmental impairment (NDI) in extremely preterm infants. DESIGN, SETTING, AND PARTICIPANTS: Preterm newborns (23-28 weeks’ gestational age) admitted to the neonatal intensive care unit at Amiens-Picardie University Hospital were retrospectively included (January 1, 2013, to January 1, 2018). Risk factors from the 4 categories were collected during the first 2 weeks post delivery. Neurodevelopmental impairment was assessed at age 2 years with the Denver Developmental Screening Test II. No or moderate NDI was considered a favorable outcome. Death or severe NDI was considered an adverse outcome. Data analysis was performed from August 26, 2021, to March 31, 2022. MAIN OUTCOMES AND MEASURES: After the selection of variables significantly associated with outcome, 4 unimodal prognostic models (considering each category of variable independently) and 1 multimodal model (considering all variables simultaneously) were developed. After a multivariate analysis for models built with several variables, decision-tree algorithms were run on each model. The areas under the curve for decision-tree classifications of adverse vs favorable outcomes were determined for each model, compared using bootstrap tests, and corrected for type I errors. RESULTS: A total of 109 newborns (58 [53.2% male]) born at a mean (SD) gestational age of 26.3 (1.1) weeks were included. Among them, 52 (47.7%) had a favorable outcome at age 2 years. The multimodal model area under the curve (91.7%; 95% CI, 86.4%-97.0%) was significantly higher than those of the unimodal models (P < .003): perinatal model (80.6%; 95% CI, 72.5%-88.7%), postnatal model (81.0%; 95% CI, 72.6%-89.4%), brain structure model (cranial ultrasonography) (76.6%; 95% CI, 67.8%-85.3%), and brain function model (cEEG) (78.8%; 95% CI, 69.9%-87.7%). CONCLUSIONS AND RELEVANCE: In this prognostic study of preterm newborns, the inclusion of brain information in a multimodal model was associated with significant improvement in the outcome prediction, which may have resulted from the complementarity of the risk factors and reflected the complexity of the mechanisms that interfered with brain maturation and led to death or NDI. American Medical Association 2023-03-08 /pmc/articles/PMC9996404/ /pubmed/36884252 http://dx.doi.org/10.1001/jamanetworkopen.2023.1590 Text en Copyright 2023 Routier L et al. JAMA Network Open. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the CC-BY License.
spellingShingle Original Investigation
Routier, Laura
Querne, Laurent
Ghostine-Ramadan, Ghida
Boulesteix, Julie
Graïc, Solène
Mony, Sandrine
Wallois, Fabrice
Bourel-Ponchel, Emilie
Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information
title Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information
title_full Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information
title_fullStr Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information
title_full_unstemmed Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information
title_short Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information
title_sort predicting the neurodevelopmental outcome in extremely preterm newborns using a multimodal prognostic model including brain function information
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996404/
https://www.ncbi.nlm.nih.gov/pubmed/36884252
http://dx.doi.org/10.1001/jamanetworkopen.2023.1590
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