ArticleClinical epidemiology2021
Development and Validation of a Clinical Prognostic Risk Score to Predict Early Neonatal Mortality, Ethiopia: A Receiver Operating Characteristic Curve Analysis.
Article in Clinical epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Research advances in key genes and regulatory mechanisms of posttranslational modifications in Parkinson's disease.PloS one · 2026Article
- Construction and evaluation of a neonatal septic shock prediction model based on multimodal data.Medicine · 2025Article
- Systematic review of risk assessment tools for post-discharge mortality among children in sub-Saharan Africa.PLOS global public health · 2025Article
- Nomogram to predict risk of neonatal mortality among preterm neonates admitted with sepsis at University of Gondar Comprehensive Specialized Hospital: risk prediction model development and validation.BMC pregnancy and childbirth · 2024Article
- Development and validation of a risk prediction model for lost to follow-up among adults on active antiretroviral therapy in Ethiopia: a retrospective follow-up study.BMC infectious diseases · 2022Article
- Development of a Nomogram for Clinical Risk Prediction of Preterm Neonate Death in Ethiopia.Frontiers in pediatrics · 2022Article
- Article
- Magnitude and Predictors of Early Neonatal Mortality in Africa:- A Systematic Review and Meta-Analysis.Sage open pediatricsReview
- Neonatal Survival and Predictors of Mortality Among Neonates Admitted at Neonatal Intensive Care Unit in Ethiopia: A Prospective Cohort Study.SAGE open nursingArticle
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly neonatal death is the death of a live-born baby within the first seven days of life, which is 73% of all postnatal deaths in the globe. This study aimed to develop and validate a prognostic clinical risk tool for the prediction of early neonatal death.
methodsA prospective follow-up study was conducted among 393 neonates at Debre Tabor Referral hospital, Northwest Ethiopia. Multivariable logistic regression model was employed to identify potential prognostic determinants for early neonatal mortality. Area under receiver operating characteristics curve (AUROC) was used to check the model discrimination probability using 'pROC' R-package. Model calibration plot was checked using 'givitiR' R-package. Finally, a risk score prediction tool was developed for ease of applicability. Decision curve analysis was done for cost-benefit analysis and to check the clinical impact of the model.
resultsOverall, 15.27% (95% CI: 12.03-19.18) of neonates had the event of death during the follow-up period. Maternal undernutrition, antenatal follow-up less than four times, birth asphyxia, low birth weight, and not exclusive breastfeeding were the prognostic predictors of early neonatal mortality. The AUROC for the reduced model was 88.7% (95% CI: 83.8-93.6%), which had good discriminative probability. The AUROC of the simplified risk score algorithm was 87.8% (95% CI, 82.7-92.9%). The sensitivity and specificity of the risk score tool was 70% and 89%, respectively. The true prediction accuracy of the risk score tool to predict early neonatal mortality was 86%, and the false prediction probability was 13%.
conclusionWe developed an early neonatal death prediction tool using easily available maternal and neonatal characteristics for resource-limited settings. This risk prediction using risk score is an easily applicable tool to identify neonates at a higher risk of having early neonatal mortality. This risk score tool would offer an opportunity to reduce early neonatal mortality, thus improving the overall early neonatal death in a resource-limited setting.
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