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Prognostic prediction models for adverse birth outcomes: A systematic review
Achenef Asmamaw Muche1,2, Likelesh Lemma Baruda1,3, Clara Pons-Duran4
1Health System and Reproductive Health Research Directorate, Ethiopian Public Health Institute, Addis Ababa, Ethiopia.
Journal of Global Health
|October 25, 2024
Summary
This review found varied factors and high risk of bias in models predicting adverse birth outcomes like preterm birth and low birth weight. Consistent factors and external validation are recommended for future prediction models.
Area of Science:
- Maternal and child health
- Clinical prediction modeling
- Global public health
Background:
- Adverse birth outcomes remain a significant global health challenge despite progress in reducing maternal and child mortality.
- Developing accurate prediction models is crucial for early risk detection and implementing preventive strategies.
- This systematic review focuses on the performance of existing prediction models for adverse birth outcomes.
Conclusions:
- Heterogeneity in prognostic factors and study methodologies complicates the prediction of adverse birth outcomes.
- There is a need for prediction models that utilize consistent prognostic factors and undergo external validation.
- Future models should be adapted for diverse settings to improve the prediction of adverse birth outcomes globally.
