Prognostic risk score development to predict birth asphyxia using maternal and fetal characteristics in South Gondar zone hospitals, north West Ethiopia

Abstract

Background Birth asphyxia leads to profound systemic and neurological sequela to decrease blood flow or oxygen to the fetus followed by lethal progressive or irreversible life-long pathologies. In low resource setting countries, birth asphyxia remains a critical condition. This study aimed to develop and validate prognostic risk scores to forecast birth asphyxia using maternal and neonatal characteristics in south Gondar zone hospitals. Methods Prospective cohorts of 404 pregnant women were included in the model in south Gondar Zone Hospitals, Northwest Ethiopia. To recognize potential prognostic determinants for birth asphyxia, multivariable logistic regression was applied. The model discrimination probability was checked using the receiver operating characteristic curve (AUROC) and the model calibration plot was assessed using the ‘givitiR’ R-package. To check the clinical importance of the model, a cost-benefit analysis was done through a decision curve and the model was internally validated using bootstrapping. Lastly, a risk score prediction measurement was established for simple application. Results Of 404, 108 (26.73%) (95% CI: 22.6–31.3) newborns were exposed to birth asphyxia during the follow-up time. Premature rupture of membrane, meconium aspiration syndrome, malpresentation, prolonged labor, Preterm, and tight nuchal was the significant prognostic predictors of birth asphyxia. The AUROC curve for birth asphyxia was 88.6% (95% CI: 84.6-92.2%), which indicated that the tool identified the newborns at risk for birth asphyxia very well. The AUROC of the simplified risk score algorithm, was 87.9 (95% CI, 84.0– 91.7%) and the risk score value of 2 was selected as the optimal cut-off value, with a sensitivity of 78.87%, a specificity of 83.26%, a positive predictive value of 63.23%, and a negative predictive value of 91.52%. Conclusions We established birth asphyxia prediction tools by applying non-sophisticated maternal and neonatal characteristics for resource scares countries. The driven score has very good discriminative ability and prediction performance. This risk score tool would allow reducing neonatal morbidity and mortality related to birth asphyxia. Consequently, it will improve the overall neonatal health / under-five child health in low-income countries.

Neonatal asphyxia – predicting its occurrence and neurodevelopment of children after hypothermia treatment in the context of machine learning models – literature review

“…Types of asphyxia [13][14][15] develop a tool to predict perinatal asphyxia based on maternal and neonatal characteristics, i.e. premature rupture of the membrane, meconium aspiration, malpresentation, prolonged labour, preterm and tight nuchal cord in hospitals in the southern Gondar zone of northwestern Ethiopia [21]. The study developed and validated a clinically simplified prognostic risk assessment system for birth asphyxia without the need for advanced laboratory or imaging tests, and included 404 newborns born between June 2020 -June 2021, with a prevalence of perinatal asphyxia of 26.7% (108 newborns).…”

“…To identify potential prognostic determinants, bivariate and multivariate logistic regression and simple logistic regression were performed on a derived data set to investigate the relationship between each predictor and birth asphyxia. The probability of birth asphyxia was determined using each prognostic value determining the risk score [21]. In the cited study, premature membrane rupture, meconium aspiration syndrome (MAS), and a mother experiencing prolonged labour in the second stage had a high predictive value for neonatal asphyxia [21].…”

“…The probability of birth asphyxia was determined using each prognostic value determining the risk score [21]. In the cited study, premature membrane rupture, meconium aspiration syndrome (MAS), and a mother experiencing prolonged labour in the second stage had a high predictive value for neonatal asphyxia [21]. In the case of premature rupture of membranes, the fact that the interval between membrane rupture and birth is prolonged, increases the risk of amniotic membrane inflammation and early-onset neonatal sepsis [22].…”