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Prevention of neonatal bilirubin injury exemplifies success of systems approach to avert adverse neonatal and childhood outcomes that rely on strategies including prenatal identification of Rhesus sensitization, universal maternal blood typing, risk assessment for neonatal extreme hyperbilirubinemia (EHB), unfettered access to safe, effective phototherapy, and application of patient safety principles. India's diverse landscape suggests varied real-time experiences of neonatal hyperbilirubinemia and consequent infant mortality rates (IMR). Utilizing Global Burden of Disease (GBD) database, the authors examined national and subnational trends, infant mortality timing, and the disease burden from hemolytic and perinatal jaundice over 30 y (1999 to 2019). They also assessed the correlation of EHB-IMR with socio-demographic index and health expenditure per capita, estimating economic losses from EHB-related infant mortality to guide policy decisions at national and state domains. From 1990 to 2019, India delivered 811,078,415 livebirths of which, 1,189,856 infant deaths were due to EHB. EHB-related deaths decreased from 57,773 in 1990 to 19,664 in 2019, a 60% reduction vs. 40% in overall IMR. Early (0–6 d), late (7–27 d), and post-neonatal (28–364 d) deaths accounted for 61%, 34%, and 5% of mortality, respectively. Uttar Pradesh and Bihar contributed to 38% of all EHB deaths. Economic analysis estimate losses between US $7.2 and 11.7 billion for the year 2019 secondary to EHB-related mortality. The present analysis reveals consistent declines across all states to reach current EHB-IMR of 0.8 per 1,000 live-births in India by 2019. Significant economic impact of lost human productivity highlight ongoing need for targeted life-saving public health strategies.

Background Neonatal mortality is a major issue in global health and is included in the Sustainable Development Goals (SDGs). Early neonatal deaths account for 47% of under-five mortality. Developing a dependable model to predict early neonatal mortality and recognise its related risk factors is essential for child survival and enhancing children’s health outcomes. We utilised various machine learning models to predict early and late neonatal mortality using a comprehensive secondary dataset from Oman. Methods Ten different machine learning (ML) models were used to predict early and late neonatal mortality in three distinct setups: using the original local dataset, applying the data-driven approach represented by Synthetic Minority Over-Sampling Technique (SMOTE) to address the imbalanced distribution, and implementing an algorithm-driven approach via cost-sensitive classification. A total of 2,940 de-identified local records on newborn deaths were categorised into early deaths (0–6 days) and late deaths (7–27 days) for model training and testing using a 10-fold cross-validation. Various calibration and discrimination metrics were utilised to assess the models’ performance due to the issue of an imbalanced dataset. Results The analysis revealed that 71.6% of the deaths occurred during the early neonatal period (0–6 days). Logistic Regression (LR), Linear Discriminant Analysis (LDA), and Random Forest (RF) were the top performers across the three scenarios, with AUC-PR (Area Under Precision and Recall Curves) above 0.85 and an exemplary Brier score. However, RF Brier score was more stable across the three setups, especially with SMOTE (Brier = 0.1864), compared to the Brier score of LDA (0.2211) and LR (0.2164) indicating an effective calibration. The APGAR (Appearance, Pulse, Grimace, Activity, and Respiration) score at 5 min was identified as the most significant predictor of early and late neonatal mortality. Conclusion This study is one of the first to train and evaluate multiple ML algorithms under three different scenarios to predict early and late neonatal mortality and to identify associated risk factors using real data from Oman. The results indicate that RF, LDA and LR performed the best based on their discrimination and calibration performance. The findings have the potential to inform clinical decision-making and prompt timely interventions to enhance survival rates.

Background To determine the gender differences in neonatal mortality, stillbirths, and perinatal mortality in south Asia using the Global Network data from the Maternal Newborn Health Registry. Methods This study is a secondary analysis of prospectively collected data from the three south Asian sites of the Global Network. The maternal and neonatal demographic, clinical characteristics, rates of stillbirths, early neonatal mortality (1–7 days), late neonatal mortality (8–28 days), mortality between 29–42 days and the number of infants hospitalized after birth were compared between the male and female infants. Results Between 2010 and 2018, 297,509 births [154,790 males (52.03%) and 142,719 females (47.97%)] from two Indian sites and one Pakistani site were included in the analysis [288,859 live births (97.1%) and 8,648 stillbirths (2.9%)]. The neonatal mortality rate was significantly higher in male infants (33.2/1,000 live births) compared to their female counterparts (27.4/1,000, p < 0.001). The rates of stillbirths (31.0 vs. 26.9/1000 births) and early neonatal mortality (27.1 vs 21.6/1000 live births) were also higher in males. However, there were no significant differences in late neonatal mortality (6.3 vs. 5.9/1000 live births) and mortality between 29–42 days (2.1 vs. 1.9/1000 live births) between the two groups. More male infants were hospitalized within 42 days after birth (1.8/1000 vs. 1.3/1000 live births, p < 0.001) than females. Conclusion The risks of stillbirths, and early neonatal mortality were higher among male infants than their female counterparts. However, there was no gender difference in mortality after 7 days of age. Our results highlight the importance of stratifying neonatal mortality into early and late neonatal period to better understand the impact of gender on neonatal mortality. The information from this study will help in developing strategies and identifying measures that can reduce differences in sex-specific mortality.

Background The current neonatal mortality rate in Uganda is high at 22 deaths per 1000 live births, while it had been stagnant at 27 deaths per 1000 live births in the past decade. This is still more than double the World Health Organization target of < 12 deaths per 1,000 live births. Three-quarters of new born deaths occur within the first week of life, which is a very vulnerable period and the causes reflect the quality of obstetric and neonatal care. At Mbarara Regional Referral Hospital (MRRH), the modifiable contributors and predictors of mortality remain undocumented, yet neonates make the bulk of admissions and contribute significantly to the overall infant mortality rate. We therefore examined the clinical profiles, incidence and predictors of early neonatal mortality of neonates admitted at MRRH in south-western Uganda. Methods We conducted a prospective cohort study at the Neonatal Unit of MRRH between August – November, 2022 among neonates. We consecutively included all live neonates aged < 7 days admitted to neonatal unit and excluded those whose outcomes could not be ascertained at day 7 of life. We obtained baseline data including; maternal social-demographic and obstetric information, and performed neonatal physical examinations for clinical profiles. We followed up neonates at 24 and 72 h of life, and at 7 days of life for mortality. We summarized the clinical profiles and incidence of mortality as frequencies and percentages and performed modified Poisson regression analysis to identify the predictors of early neonatal mortality. Results We enrolled 384 neonates. The majority of neonates were in-born (68.5%, n  = 263) and were admitted within 24 h after birth (54.7%, n  = 210). The most common clinical profiles at admission were prematurity (46%, n  = 178), low birth weight (LBW) (44%, n  = 170), sepsis (36%, n  = 139), hypothermia (35%, n  = 133), and birth asphyxia (32%, n  = 124). The incidence of early neonatal mortality was at 12.0%, 46 out of the 384 neonates died. The predictors of early neonatal mortality were hypothermia, [adjusted Risk Ratio: 4.10; 95% C.I (1.15–14.56)], birth asphyxia, [adjusted Risk Ratio: 3.6; 95% C.I (1.23–10.73)] and delayed initiation of breastfeeding, [adjusted Risk Ratio: 7.20; 95% C.I (1.01–51.30)]. Conclusion Prematurity, LBW, sepsis, birth asphyxia and hypothermia are the commonest admission diagnoses. The incidence of early neonatal mortality was high, 12.0%. We recommend targeted interventions by the clinical care team at MRRH to enable timely identification of neonates with or at risk of hypothermia to reduce incidence of adverse outcomes. Intrapartum care should be improved in order to mitigate the risk of birth asphyxia. Breastfeeding within the first hour of birth should be strengthened were possible, as this is associated with vast benefits for the baby and may reduce the incidence of complications like hypothermia.

Our study aim was to identify high-risk areas of neonatal mortality associated with bacterial sepsis in the state of São Paulo, Southeast Brazil. We used a population-based study applying retrospective spatial scan statistics with data extracted from birth certificates linked to death certificates. All live births from mothers residing in São Paulo State from 2004 to 2020 were included. Spatial analysis using the Poisson model was adopted to scan high-rate clusters of neonatal mortality associated with bacterial sepsis (WHO-ICD10 A32.7, A40, A41, P36, P37.2 in any line of the death certificate). We found a prevalence of neonatal death associated with bacterial sepsis of 2.3/1000 live births. Clusters of high neonatal mortality associated with bacterial sepsis were identified mainly in the southeast region of the state, with four of them appearing as cluster areas for all birth weight categories (<1500 g, 1500 to <2500 g and ≥ 2500 g). The spatial analysis according to the birth weight showed some overlapping in the detected clusters, suggesting shared risk factors that need to be explored. Our study highlights the ongoing challenge of neonatal sepsis in the most developed state of a middle-income country and the importance of employing statistical techniques, including spatial methods, for enhancing surveillance and intervention strategies.

The use of azithromycin reduces maternal infection in women during unplanned cesarean delivery, but its effect on those with planned vaginal delivery is unknown. Data are needed on whether an intrapartum oral dose of azithromycin would reduce maternal and offspring sepsis or death. In this multicountry, placebo-controlled, randomized trial, we assigned women who were in labor at 28 weeks' gestation or more and who were planning a vaginal delivery to receive a single 2-g oral dose of azithromycin or placebo. The two primary outcomes were a composite of maternal sepsis or death and a composite of stillbirth or neonatal death or sepsis. During an interim analysis, the data and safety monitoring committee recommended stopping the trial for maternal benefit. A total of 29,278 women underwent randomization. The incidence of maternal sepsis or death was lower in the azithromycin group than in the placebo group (1.6% vs. 2.4%), with a relative risk of 0.67 (95% confidence interval [CI], 0.56 to 0.79; P<0.001), but the incidence of stillbirth or neonatal death or sepsis was similar (10.5% vs. 10.3%), with a relative risk of 1.02 (95% CI, 0.95 to 1.09; P = 0.56). The difference in the maternal primary outcome appeared to be driven mainly by the incidence of sepsis (1.5% in the azithromycin group and 2.3% in the placebo group), with a relative risk of 0.65 (95% CI, 0.55 to 0.77); the incidence of death from any cause was 0.1% in the two groups (relative risk, 1.23; 95% CI, 0.51 to 2.97). Neonatal sepsis occurred in 9.8% and 9.6% of the infants, respectively (relative risk, 1.03; 95% CI, 0.96 to 1.10). The incidence of stillbirth was 0.4% in the two groups (relative risk, 1.06; 95% CI, 0.74 to 1.53); neonatal death within 4 weeks after birth occurred in 1.5% in both groups (relative risk, 1.03; 95% CI, 0.86 to 1.24). Azithromycin was not associated with a higher incidence in adverse events. Among women planning a vaginal delivery, a single oral dose of azithromycin resulted in a significantly lower risk of maternal sepsis or death than placebo but had little effect on newborn sepsis or death. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; A-PLUS ClinicalTrials.gov number, NCT03871491.).

Background Child survival is a major concern in Nigeria, as it contributes 13% of the global under-five mortalities. Although studies have examined the determinants of under-five mortality in Nigeria, the comparative roles of social determinants of health at the different stages of early childhood development have not been concurrently investigated. This study, therefore, aimed to identify the social determinants of age-specific childhood (0–59 months) mortalities, which are disaggregated into neonatal mortality (0–27 days), post-neonatal mortality (1–11 months) and child mortality (12–59 months), and estimate the within-and between-community variations of mortality among under-five children in Nigeria. This study provides evidence to guide stakeholders in planning for effective child survival strategies in the Nigerian communities during the Sustainable Development Goals era. Methods Using the 2016/2017 Nigeria Multiple Indicator Cluster Survey, we performed multilevel multinomial logistic regression analysis on data of a nationally representative sample of 29,786 (weighted = 30,960) live births delivered 5 years before the survey to 18,497 women aged 15–49 years and nested within 16,151 households and 2227 communities. Results Determinants of under-five mortality differ across the neonatal, post-neonatal and toddler/pre-school stages in Nigeria. Unexpectedly, attendance of skilled health providers during delivery was associated with an increased neonatal mortality risk, although its effect disappeared during post-neonatal and toddler/pre-school stages. Also, our study found maternal-level factors such as maternal education, contraceptive use, maternal wealth index, parity, death of previous children, and quality of perinatal care accounted for high variation (39%) in childhood mortalities across the communities. The inclusion of other compositional and contextual factors had no significant additional effect on childhood mortality risks across the communities. Conclusion This study reinforces the importance of maternal-level factors in reducing childhood mortality, independent of the child, household, and community-level characteristics in the Nigerian communities. To tackle childhood mortalities in the communities, government-led strategies should prioritize implementation of community-based and community-specific interventions aimed at improving socioeconomic conditions of women. Training and continuous mentoring with adequate supervision of skilled health workers must be ensured to improve the quality of perinatal care in Nigeria.

Neonatal sepsis is a significant public health challenge across the globe, particularly, in low-resource settings. While early identification of at-risk patients is a recommended approach to reduce sepsis- related deaths, there is limited evidence from low-resource settings. Therefore, this study aimed to develop prediction models to estimate neonatal mortality among neonates with sepsis. The study was conducted among 975 neonates diagnosed with sepsis in the NICUs of two large hospitals in Bahir Dar city. Data were analyzed in R software, and regression analyses were performed. Receiver operating characteristic curve (ROC) and calibration plot were used to assess model performance, and internal validation was performed using bootstrapping technique. Sepsis accounted for 27.9% of neonatal deaths. Key predictors of mortality were low birth weight, late initiation of breastfeeding, gestational age, fifth-minute Apgar score, tachycardia, respiratory distress, and convulsions. The original and nomogram models demonstrated an AUC of 81.3% and 81.2%, respectively. In conclusion, the high incidence of sepsis-attributed mortality highlights the need for effective predictive tools. The nomogram, based on key clinical predictors such as low birth weight, late initiation of breastfeeding, prematurity, fifth-minute apgar score, tachycardia, respiratory distress, and convulsions, demonstrated very good discrimination, and calibration performances, These findings support the use of the model as a practical tool for early risk stratification and clinical decision-making in neonatal intensive care settings

Background Neonatal and infant mortality rates are among the most significant indicators for assessing a country's healthcare and social development. This study examined the trends in neonatal, post-neonatal, and infant mortality in Italy from 2016 to 2020 and analysed differences between children of Italian and foreign parents based on areas of residence, as well as the leading causes of death. Special attention was given to the analysis of mortality in 2020, the first year of the Covid-19 pandemic, and its comparison with previous years. Methods Data from 2016 to 2020 were collected by the Italian National Institute of Statistics and extracted from two national databases, the Causes of Death register and Live births registered in the population register. Neonatal, post-neonatal, and infant mortality rates were calculated using conventional definitions. The main analyses were conducted by comparing Italian citizens to foreigners and contrasting residents of the North with those of the South. Group comparisons were made using mortality rate ratios. The main causes of death were examined, and Poisson log-linear regression models were employed to investigate the relationships between mortality rate ratios for each cause of death and citizenship, place of residence and calendar year. Results In Italy, in 2020, the neonatal mortality rate was 1.76 deaths per thousand live births and it was 55% higher in foreign children than in Italian children. Foreign children had a higher mortality rate than Italians for almost all significant causes of death. Children born in the South of Italy, both Italian and foreign, had an infant mortality rate about 70% higher than residents in the North. Regions with higher infant mortality were Calabria, Sicily, Campania, and Apulia. In the South, mortality from neonatal respiratory distress and prematurity was higher. In the first months of 2020, between March and June, the first Covid-19 wave, Italy experienced an increase in neonatal and infant mortality compared to the same period in 2016–2019, not directly related to SARS-CoV-19 infection. The primary cause was neonatal respiratory distress. Conclusions The neonatal and infant mortality rates indicate the persistence of profound inequalities in Italy between the North and the South and between Italian and foreign children.

Objectives To investigate socioeconomic inequalities in outcome of pregnancy and neonatal mortality associated with congenital anomalies.Design Retrospective population based registry study.Setting East Midlands and South Yorkshire regions of England (representing about 10% of births in England and Wales).Participants All registered cases of nine selected congenital anomalies with poor prognostic outcome audited as part of the United Kingdom’s fetal anomaly screening programme with an end of pregnancy date between 1 January 1998 and 31 December 2007.Main outcome measures Socioeconomic variation in the risk of selected congenital anomalies; outcome of pregnancy; incidence of live birth and neonatal mortality over time. Deprivation measured with the index of multiple deprivation 2004 at super output area level.Results There were 1579 fetuses registered with one of the nine selected congenital anomalies. There was no evidence of variation in the overall risk of these anomalies with deprivation (rate ratio for the most deprived 10th with the least deprived 10th: 1.05, 95% confidence interval 0.89 to 1.23). The rate ratio varied with type of anomaly and maternal age (deprivation rate ratio adjusted for maternal age: 1.43 (1.17 to 1.74) for non-chromosomal anomalies; 0.85 (0.63 to 1.15) for chromosomal anomalies). Of the nine anomalies, 86% were detected in the antenatal period, and there was no evidence that this varied with deprivation (rate ratio 0.99, 0.84 to 1.17). The rate of termination after antenatal diagnosis of a congenital anomaly was lower in the most deprived areas compared with the least deprived areas (63% v 79%; rate ratio 0.80, 0.65 to 0.97). Consequently there were significant socioeconomic inequalities in the rate of live birth and neonatal mortality associated with the presence of any of these nine anomalies. Compared with the least deprived areas, the most deprived areas had a 61% higher rate of live births (1.61, 1.21 to 2.15) and a 98% higher neonatal mortality rate (1.98, 1.20 to 3.27) associated with a congenital anomaly.Conclusions Antenatal screening for congenital anomalies has reduced neonatal mortality through termination of pregnancy. Socioeconomic variation in decisions regarding termination of pregnancy after antenatal detection, however, has resulted in wide socioeconomic inequalities in liveborn infants with a congenital anomaly and subsequent neonatal mortality.