Mortality in the first 24h of very low birth weight preterm infants in the Northeast of Brazil

Incidence and predictors of mortality among low birth weight neonates in the first week of life admitted to the neonatal intensive care unit in Northwestern Ethiopia comprehensive specialized hospitals, 2022. Multi-center institution-based retrospective follow-up study

BACKGROUND

Globally, a high number of neonatal mortalities occurs in the first week of life, particularly among low birth weight neonates in low-income countries, including Ethiopia. However, there is limited evidence on the early neonatal mortality of low-birth-weight neonates in Ethiopia. Therefore, this study aimed to assess incidence and predictors of mortality among low-birth-weight neonates in their first week of life admitted to the neonatal intensive care unit in Northwestern Ethiopia Comprehensive Specialized Hospitals, 2022.

METHODS

A multi-center retrospective follow-up study was conducted from March 21, 2020 to March 1, 2022, among 761 early neonates with low birth weight admitted in Northwestern Ethiopia Comprehensive Specialized Hospitals. The study participants were selected using simple random sampling technique. Data were collected using a data abstraction checklist ,and checked for completeness and entered into EPI data version 4.6, then exported to STATA 14 for analysis. Kaplan Meier failure curve and log-rank test were used to estimate and compare the probability of death. Both bivariable and multivariable Weibull regression models were fitted to identify predictors of mortality. Finally, a hazard ratio with 95% CI was computed, and variables having a p-value < 0.05 were considered as a significant predictor of mortality.

RESULTS

The incidence of mortality among low birth weight neonates in their first week of life was 75.63 per 1000 neonate day observation (95% CI: 66.76-85.67), preeclampsia (AHR = 1.77;95% CI:1.32-2.36s), perinatal asphyxia (AHR = 1.64; 95% CI:1.14-2.36), respiratory distress syndrome (AHR = 1.76 95% CI;1.31-2.34), necrotizing enterocolitis (AHR = 2.78 95% CI;1.79-4.32), prematurity (AHR = 1.86; 95% CI:1.30-2.67), and birth weight < 1000gram (AHR = 3.13;95% CI: 1.91-5.12) and 1000-1499 gram (AHR = 1.99; 95% CI:1.47-2.68) were predictors.

CONCLUSION

The incidence of early neonatal mortality in low birth weight neonates was incredibly higher than the overall early neonatal mortality in Northwest Ethiopia (Amhara region). Preeclampsia, perinatal asphyxia, respiratory distress syndrome, necrotizing enterocolitis, prematurity, and birth weight were predictors of mortality. Therefore, stakeholders shall give early identification and emphasis on preventable and treatable predictors. Furthermore, the health care provider shall give education about the importance of breastfeeding, and Antenatal and postnatal care.

Maternal factors and child health conditions at birth associated with preterm deaths in a tertiary health facility in Ghana: A retrospective analysis

Background

Preterm birth continues to be a leading cause of death for children under the age of 5 globally. This issue carries significant economic, psychological, and social costs for the families affected. Therefore, it is important to utilize available data to further research and understand the risk factors for preterm death.

Objective

The objective of this study was to determine maternal and infant complications that influence preterm deaths in a tertiary health facility in Ghana.

Methods

A retrospective analysis of data on preterm newborns was conducted at the neonatal intensive care unit of Korle Bu Teaching Hospital (KBTH NICU) in Ghana, covering the period January 2017 to May 2019. Pearson's Chi-square test of association was used to identify factors that were significantly associated with preterm death after admission at the NICU. The Poisson regression model was used to determine the risk factors of preterm death before discharge after admission to the NICU.

Results

Of the 1,203 preterm newborns admitted to the NICU in about two and half years, 355 (29.5%) died before discharge, 7.0% (n = 84) had normal birth weight (>2.5 kg), 3.3% (n = 40) had congenital anomalies and 30.5% (n = 367) were born between 34 and 37 gestational week. All 29 preterm newborns between the 18-25 gestational week died. None of the maternal conditions were significant risk factors of preterm death in the multivariable analysis. The risk of death at discharge was higher among preterm newborns with complications including hemorrhagic/hematological disorders of fetus (aRRR: 4.20, 95% CI: [1.70-10.35], p = 0.002), fetus/newborn infections (aRRR: 3.04, 95% CI: [1.02-9.04], p = 0.046), respiratory disorders (aRRR: 13.08, 95% CI: [5.50-31.10], p < 0.001), fetal growth disorders/restrictons (aRRR: 8.62, 95% CI: [3.64-20.43], p < 0.001) and other complications (aRRR: 14.57, 95% CI: [5.93-35.77], p < 0.001).

Conclusion

This study demonstrate that maternal factors are not significant risk factors of preterm deaths. Gestational age, birth weight, presence of complications and congenital anomalies at birth are significantly associated with preterm deaths. Interventions should focus more on child health conditions at birth to reduce the death of preterm newborns.

Spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes

This is an ecological study analysing spatial patterns of the total mortality over the first 24 hours of life and that due to preventable causes using data from the mortality information system (SIM) and live birth information system (SINASC) based on the municipalities of Pernambuco State, Brazil. The total mortality rates over the first 24 hours and that due to preventable causes were calculated for each municipality for the decades of 2000 to 2009 and for 2010 to 2019 to enable a comparison of the spatial patterns with spatial scan statistic used to identify clusters. Over the first 24 hours of life, a total of 13,571 deaths were reported, out of which 10,476 (77.2%) were preventable. The total mortality rate over the first 24 hours of life decreased from 5.5 in the 2000- 2009 period to 3.7 per 1000 live births in the following decade: a reduction of 32.7%, while the mortality rate due to preventable causes decreased from 4.4 to 2.8 per 1000 live births, a reduction of 36.7%. In the first decade, spatial exploratory analysis found three mortality rate clusters encompassing 56 municipalities over the first 24 hours of life. With respect to preventable causes over the first 24 hours of life, two mortality rate clusters were identified encompassing 41 municipalities. Risk areas for mortality over the first 24 hours of life were detected through spatial scan statistic. This method, directed towards uncovering the geographical distribution of deaths of very premature infants, can act as a tool for identifying priority areas to guide healthcare interventions.

Development and Validation of a Clinical Prognostic Risk Score to Predict Early Neonatal Mortality, Ethiopia: A Receiver Operating Characteristic Curve Analysis

Background

Early 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.

Methods

A 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.

Results

Overall, 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%.

Conclusion

We 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.

Preterm Neonatal Mortality and Its Determinants at a Tertiary Hospital in Western Uganda: A Prospective Cohort Study

Background

Prematurity contributes greatly to the neonatal mortality burden in sub-Saharan Africa. This study evaluated the proportion of preterm neonatal death, medical conditions at admission, and determinants of mortality of preterm neonates in the neonatal intensive care unit (NICU) of a tertiary hospital in Western Uganda.

Materials and Methods

A prospective cohort study of 351 consecutively enrolled preterm neonates was conducted from March to June 2019. Interviewer-administered questionnaires and physical assessment of neonates were used to obtain socio-demographic and clinical data for mothers and their preterm neonates. Descriptive statistics for participants’ characteristics were generated, while bivariate and multivariate logistic regression models were fitted so as to establish the determinants of mortality outcome. A p-value <0.05 was considered statistically significant.

Results

In-hospital neonatal mortality of 31.6% (95% CI: 26.9–36.7) was noted, with 65.8% of deaths occurring within 72 hours from admission. The most common medical conditions at admission were: hypothermia (67.2%), respiratory distress syndrome (43.0%), small for gestational age (15.7%), and perinatal asphyxia (14.5%). Under multivariate regression modelling, maternal age ≥35 years (AOR: 4.5; 95% CI: 1.35–15.31), no antenatal care (AOR: 4.7; 95% CI: 1.05–21.21), >4 ANC visits (AOR: 5.3; 95% CI: 1.88–15.21), neonatal resuscitation (AOR: 3.4; 95% CI: 1.66–6.82), outborn status (AOR: 2.3; 95% CI: 1.20–4.50), singleton pregnancy (AOR: 3.7; 95% CI: 1.74–7.89), <28 weeks’ gestation (AOR: 12.0; 95% CI: 2.24–64.27), and male sex (AOR: 2.0; 95% CI: 1.04–3.74), respiratory distress syndrome (AOR: 2.6; 95% CI: 1.22–5.70), apnea (AOR: 6.2; 95.5% CI: 1.09–35.38), hypothermia (AOR: 2.3; 95% CI: 1.09–4.92), and small for gestational age (AOR: 4.7; 95% CI: 2.06–10.74) were significantly associated with mortality.

Conclusion and Recommendations

In-hospital mortality of preterm neonates was high. We identified various maternal and neonatal risk factors, indicating a need for stakeholders to enhance efforts towards prevention of preterm-associated complications and optimize facility-based continuum of care.