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[Prediction of mortality in premature neonates. An updated systematic review]
Ruth Del Río1, Marta Thió2, Mattia Bosio3
1Departamento de Neonatología, Hospital Sant Joan de Déu, BCNatal-Hospital Clínic-Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, España.
Insights
This systematic review identifies recent predictive models for mortality in premature infants. Developing validated models in Spain is crucial for individualized care and resource optimization.
Area of Science:
- Neonatal Medicine
- Biostatistics
- Public Health
Background:
- Extreme prematurity presents significant mortality risks.
- Accurate prediction of mortality is essential for clinical decision-making and parental counseling.
- Individualized risk assessment is a priority in neonatal intensive care.
Purpose of the Study:
- To systematically review recently published predictive models for mortality in premature infants.
- To identify and assess the characteristics and validation of new predictive models.
- To evaluate the current landscape of mortality prediction tools for preterm neonates.
Main Methods:
- Systematic literature search of PubMed for predictive models of mortality in premature neonates (gestational age ≤30 weeks or birth weight ≤1500g).
- Inclusion of studies published between June 2010 and July 2019, post-dating a previous review.
- Assessment of model populations, characteristics, variables, performance measures (e.g., Odds Ratio, Area Under the Curve), and validation methods.
Main Results:
- 31 works were selected, identifying 8 new predictive models for preterm infant mortality.
- Most models were developed in North America (5) and Europe (2).
- One sequential model allows predictions at multiple time points; logistic regression was common. Internal validation was performed on 5 models, and 3 are accessible online. No models were validated in Spain.
Conclusions:
- Predictive models can enhance individualized care and optimize resource allocation for premature infants.
- There is a critical need for the development and validation of predictive mortality models specifically for premature neonates in Spain.
- Further research is required to ensure equitable access to and application of these vital tools globally.
Introduction:
Extreme prematurity is associated with high mortality rates. The probability of death at different points in time is a priority for professionals and parents, and needs to be established on an individual basis. The aim of this study is to carry out a systematic review of predictive models of mortality in premature infants that have been published recently.
Methods:
A double search was performed for article published in PubMed on models predicting mortality in premature neonates. The population studied were premature neonates with a gestational age of ≤30 weeks and / or a weight at birth of ≤1500g. Works published with new models from June 2010 to July 2019 after a systematic review by Medlock (2011) were included. An assessment was made of the population, characteristics of the model, variables used, measurements of functioning, and validation.
Results:
Of the 7744 references (1st search) and 1435 (2nd search) found, 31 works were selected, with 8 new models finally being included. Five models (62.5%) were developed in North America and 2 (25%) in Europe. A sequential model (Ambalavanan) enables predictions of mortality to be made at birth, 7, 28 days of life, and 36 weeks post-menstrual. A multiple logistic regression analysis was performed on 87.5% of the models. The population discrimination was measured using Odds Ratio (75%) and the area under the curve (50%). "Internal Validation" had been carried out on 5 models. Three models can be accessed on-line. There are no predictive models validated in Spain.
Conclusions:
The making of decisions based on predictive models can lead to the care given to the premature infant being more individualised and with a better use of resources. Predictive models of mortality in premature neonates in Spain need to be developed.
