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Development and Validation of a Mortality Prediction Model in Extremely Low Gestational Age Neonates

Moreira, Alvaro ; Benvenuto, Domenico ; Fox-Good, Christopher ; Alayli, Yasmeen ; Evans, Mary ; Jonsson, Baldvin ; Hakansson, Stellan ; Harper, Nathan ; Kim, Jennifer and Norman, Mikael , et al. (2022) In Neonatology 119(4). p.418-427
Abstract

Introduction: Understanding factors that associate with neonatal death may lead to strategies or interventions that can aid clinicians and inform families. Objective: The aim of the study was to develop an early prediction model of neonatal death in extremely low gestational age (ELGA, <28 weeks) neonates. Methods: A predictive cohort study of ELGA neonates was derived from the Swedish Neonatal Quality Register between the years 2011 to May 2021. The goal was to use readily available clinical variables, collected within the first hour of birth, to predict in-hospital death. Data were split into a train cohort (80%) to build the model and tested in 20% of randomly selected neonates. Model performance was assessed via area under the... (More)

Introduction: Understanding factors that associate with neonatal death may lead to strategies or interventions that can aid clinicians and inform families. Objective: The aim of the study was to develop an early prediction model of neonatal death in extremely low gestational age (ELGA, <28 weeks) neonates. Methods: A predictive cohort study of ELGA neonates was derived from the Swedish Neonatal Quality Register between the years 2011 to May 2021. The goal was to use readily available clinical variables, collected within the first hour of birth, to predict in-hospital death. Data were split into a train cohort (80%) to build the model and tested in 20% of randomly selected neonates. Model performance was assessed via area under the receiver operating characteristic curve (AUC) and compared to validated mortality prediction models and an external cohort of neonates. Results: Among 3,752 live-born extremely preterm infants (46% girls), in-hospital mortality was 18% (n = 685). The median gestational age and birth weight were 25.0 weeks (interquartile range [IQR] 24.0, 27.0) and 780 g (IQR 620, 940), respectively. The proposed model consisted of three variables: birth weight (grams), Apgar score at 5 min of age, and gestational age (weeks). The BAG model had an AUC of 76.9% with a 95% confidence interval (CI) (72.6%, 81.3%), while birth weight and gestational age had an AUC of 73.1% (95% CI: 68.4%,77.9%) and 71.3% (66.3%, 76.2%). In the validation cohort, the BAG model had an AUC of 68.9%. Conclusion: The BAG model is a new mortality prediction model in ELGA neonates that was developed using readily available information.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Mortality, Neonate, Prediction, Preterm
in
Neonatology
volume
119
issue
4
pages
10 pages
publisher
Karger
external identifiers
  • scopus:85131526431
  • pmid:35598593
ISSN
1661-7800
DOI
10.1159/000524729
language
English
LU publication?
yes
id
53ceddc6-b362-4167-b361-f9df2efbc6d1
date added to LUP
2022-12-30 10:28:23
date last changed
2024-09-16 14:38:23
@article{53ceddc6-b362-4167-b361-f9df2efbc6d1,
  abstract     = {{<p>Introduction: Understanding factors that associate with neonatal death may lead to strategies or interventions that can aid clinicians and inform families. Objective: The aim of the study was to develop an early prediction model of neonatal death in extremely low gestational age (ELGA, &lt;28 weeks) neonates. Methods: A predictive cohort study of ELGA neonates was derived from the Swedish Neonatal Quality Register between the years 2011 to May 2021. The goal was to use readily available clinical variables, collected within the first hour of birth, to predict in-hospital death. Data were split into a train cohort (80%) to build the model and tested in 20% of randomly selected neonates. Model performance was assessed via area under the receiver operating characteristic curve (AUC) and compared to validated mortality prediction models and an external cohort of neonates. Results: Among 3,752 live-born extremely preterm infants (46% girls), in-hospital mortality was 18% (n = 685). The median gestational age and birth weight were 25.0 weeks (interquartile range [IQR] 24.0, 27.0) and 780 g (IQR 620, 940), respectively. The proposed model consisted of three variables: birth weight (grams), Apgar score at 5 min of age, and gestational age (weeks). The BAG model had an AUC of 76.9% with a 95% confidence interval (CI) (72.6%, 81.3%), while birth weight and gestational age had an AUC of 73.1% (95% CI: 68.4%,77.9%) and 71.3% (66.3%, 76.2%). In the validation cohort, the BAG model had an AUC of 68.9%. Conclusion: The BAG model is a new mortality prediction model in ELGA neonates that was developed using readily available information.</p>}},
  author       = {{Moreira, Alvaro and Benvenuto, Domenico and Fox-Good, Christopher and Alayli, Yasmeen and Evans, Mary and Jonsson, Baldvin and Hakansson, Stellan and Harper, Nathan and Kim, Jennifer and Norman, Mikael and Bruschettini, Matteo}},
  issn         = {{1661-7800}},
  keywords     = {{Mortality; Neonate; Prediction; Preterm}},
  language     = {{eng}},
  month        = {{07}},
  number       = {{4}},
  pages        = {{418--427}},
  publisher    = {{Karger}},
  series       = {{Neonatology}},
  title        = {{Development and Validation of a Mortality Prediction Model in Extremely Low Gestational Age Neonates}},
  url          = {{http://dx.doi.org/10.1159/000524729}},
  doi          = {{10.1159/000524729}},
  volume       = {{119}},
  year         = {{2022}},
}