Simplified models to assess newborn gestational age in low-middle income countries: findings from a multicountry, prospective cohort study.

INTRODUCTION: Preterm birth is the leading cause of child mortality. This study aimed to develop and validate programmatically feasible and accurate approaches to estimate newborn gestational age (GA) in low resource settings. METHODS: The WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) study recruited pregnant women from population-based cohorts in five countries (Bangladesh, Ghana, Pakistan, Tanzania and Zambia). Women <20 weeks gestation by ultrasound-based dating were enrolled. Research staff assessed newborns for: (1) anthropometry, (2) neuromuscular/physical signs and (3) feeding maturity. Machine-learning techniques were used to construct ensemble models. Diagnostic accuracy was assessed by areas under the receiver operating curve (AUC) and Bland-Altman analysis. RESULTS: 7428 liveborn infants were included (n=536 preterm, <37 weeks). The Ballard examination was biased compared with ultrasound dating (mean difference: +9 days) with 95% limits of agreement (LOA) -15.3 to 33.6 days (precision ±24.5 days). A model including 10 newborn characteristics (birth weight, head circumference, chest circumference, foot length, breast bud diameter, breast development, plantar creases, skin texture, ankle dorsiflexion and infant sex) estimated GA with no bias, 95% LOA ±17.3 days and an AUC=0.88 for classifying the preterm infant. A model that included last menstrual period (LMP) with the 10 characteristics had 95% LOA ±15.7 days and high diagnostic accuracy (AUC 0.91). An alternative simpler model including birth weight and LMP had 95% LOA of ±16.7 and an AUC of 0.88. CONCLUSION: The best machine-learning model (10 neonatal characteristics and LMP) estimated GA within ±15.7 days of early ultrasound dating. Simpler models performed reasonably well with marginal increases in prediction error. These models hold promise for newborn GA estimation when ultrasound dating is unavailable

Population-based rates, timing, and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa: a multi-country prospective cohort study.

BACKGROUND: Modelled mortality estimates have been useful for health programmes in low-income and middle-income countries. However, these estimates are often based on sparse and low-quality data. We aimed to generate high quality data about the burden, timing, and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa. METHODS: In this prospective cohort study done in 11 community-based research sites in south Asia and sub-Saharan Africa, between July, 2012, and February, 2016, we conducted population-based surveillance of women of reproductive age (15-49 years) to identify pregnancies, which were followed up to birth and 42 days post partum. We used standard operating procedures, data collection instruments, training, and standardisation to harmonise study implementation across sites. Verbal autopsies were done for deaths of all women of reproductive age, neonatal deaths, and stillbirths. Physicians used standardised methods for cause of death assignment. Site-specific rates and proportions were pooled at the regional level using a meta-analysis approach. FINDINGS: We identified 278 186 pregnancies and 263 563 births across the study sites, with outcomes ascertained for 269 630 (96·9%) pregnancies, including 8761 (3·2%) that ended in miscarriage or abortion. Maternal mortality ratios in sub-Saharan Africa (351 per 100 000 livebirths, 95% CI 168-732) were similar to those in south Asia (336 per 100 000 livebirths, 247-458), with far greater variability within sites in sub-Saharan Africa. Stillbirth and neonatal mortality rates were approximately two times higher in sites in south Asia than in sub-Saharan Africa (stillbirths: 35·1 per 1000 births, 95% CI 28·5-43·1 vs 17·1 per 1000 births, 12·5-25·8; neonatal mortality: 43·0 per 1000 livebirths, 39·0-47·3 vs 20·1 per 1000 livebirths, 14·6-27·6). 40-45% of pregnancy-related deaths, stillbirths, and neonatal deaths occurred during labour, delivery, and the 24 h postpartum period in both regions. Obstetric haemorrhage, non-obstetric complications, hypertensive disorders of pregnancy, and pregnancy-related infections accounted for more than three-quarters of maternal deaths and stillbirths. The most common causes of neonatal deaths were perinatal asphyxia (40%, 95% CI 39-42, in south Asia; 34%, 32-36, in sub-Saharan Africa) and severe neonatal infections (35%, 34-36, in south Asia; 37%, 34-39 in sub-Saharan Africa), followed by complications of preterm birth (19%, 18-20, in south Asia; 24%, 22-26 in sub-Saharan Africa). INTERPRETATION: These results will contribute to improved global estimates of rates, timing, and causes of maternal and newborn deaths and stillbirths. Our findings imply that programmes in sub-Saharan Africa and south Asia need to further intensify their efforts to reduce mortality rates, which continue to be high. The focus on improving the quality of maternal intrapartum care and immediate newborn care must be further enhanced. Efforts to address perinatal asphyxia and newborn infections, as well as preterm birth, are critical to achieving survival goals in the Sustainable Development Goals era. FUNDING: Bill & Melinda Gates Foundation

Population-based rates, risk factors and consequences of preterm births in South-Asia and sub-Saharan Africa: A multi-country prospective cohort study.

BACKGROUND: Preterm birth is the leading cause of neonatal deaths in low middle-income countries (LMICs), yet there exists a paucity of high-quality data from these countries. Most modelling estimates are based on studies using inaccurate methods of gestational age assessment. We aimed to fill this gap by measuring the population-based burden of preterm birth using early ultrasound dating in five countries in South-Asian and sub-Saharan Africa. METHODS: We identified women early in pregnancy (<20 weeks based on last menstrual period) by home visits every 2-3 months (except in Zambia where they were identified at antenatal care clinics) in 5 research sites in South-Asia and sub-Saharan Africa between July 2012 and September 2016. Trained sonographers performed an ultrasound scan for gestational age dating. Women were enrolled if they were 8-19 weeks pregnant on ultrasound. Women <8 weeks were rescheduled for repeat scans after 4 weeks, and identified women were followed through pregnancy until 6 weeks postpartum. Site-specific rates and proportions were calculated and a logistic regression model was used to predict the risk factors of preterm birth. RESULTS: Preterm birth rates ranged from 3.2% in Ghana to 15.7% in Pakistan. About 46% of all neonatal deaths occurred among preterm infants, 49% in South Asia and 40% in sub-Saharan Africa. Fourteen percent of all preterm infants died during the neonatal period. The mortality was 37.6% for early preterm babies (<34 weeks), 5.9% for late preterm babies (34 to <37 weeks), and 1.7% for term babies (37 to <42 weeks). Factors associated lower gestation at birth included South-Asian region (adjusted mean difference (Adj MD) = -6.2 days, 95% confidence interval (CI) = -5.5, -6.9), maternal morbidities (Adj MD = -3.4 days, 95% CI = -4.6, -2.2), multiple pregnancies (Adj MD = -17.8 days, 95% CI = -19.9,-15.8), adolescent pregnancy (Adj MD = -2.7 days, 95% CI = -3.7, -1.6) and lowest wealth quintile (Adj MD = -1.3 days, 95% CI = -2.4, -0.3). CONCLUSIONS: Preterm birth rates are higher in South Asia than in sub-Saharan Africa and contribute to 49% and 40% of all neonatal deaths in the two regions, respectively. Adolescent pregnancy and maternal morbidities are modifiable risk factors associated with preterm birth

Simplified models to assess newborn gestational age in low-middle income countries: findings from a multicountry, prospective cohort study

Introduction Preterm birth is the leading cause of child mortality. This study aimed to develop and validate programmatically feasible and accurate approaches to estimate newborn gestational age (GA) in low resource settings. Methods The WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) study recruited pregnant women from population-based cohorts in five countries (Bangladesh, Ghana, Pakistan, Tanzania and Zambia). Women <20 weeks gestation by ultrasound-based dating were enrolled. Research staff assessed newborns for: (1) anthropometry, (2) neuromuscular/physical signs and (3) feeding maturity. Machine-learning techniques were used to construct ensemble models. Diagnostic accuracy was assessed by areas under the receiver operating curve (AUC) and Bland-Altman analysis. Results 7428 liveborn infants were included (n=536 preterm, <37 weeks). The Ballard examination was biased compared with ultrasound dating (mean difference: +9 days) with 95% limits of agreement (LOA) −15.3 to 33.6 days (precision ±24.5 days). A model including 10 newborn characteristics (birth weight, head circumference, chest circumference, foot length, breast bud diameter, breast development, plantar creases, skin texture, ankle dorsiflexion and infant sex) estimated GA with no bias, 95% LOA ±17.3 days and an AUC=0.88 for classifying the preterm infant. A model that included last menstrual period (LMP) with the 10 characteristics had 95% LOA ±15.7 days and high diagnostic accuracy (AUC 0.91). An alternative simpler model including birth weight and LMP had 95% LOA of ±16.7 and an AUC of 0.88. Conclusion The best machine-learning model (10 neonatal characteristics and LMP) estimated GA within ±15.7 days of early ultrasound dating. Simpler models performed reasonably well with marginal increases in prediction error. These models hold promise for newborn GA estimation when ultrasound dating is unavailable

Development and validation of a simplified algorithm for neonatal gestational age assessment - protocol for the Alliance for Maternal Newborn Health Improvement (AMANHI) prospective cohort study.

OBJECTIVE: The objective of the Alliance for Maternal and Newborn Health Improvement (AMANHI) gestational age study is to develop and validate a programmatically feasible and simple approach to accurately assess gestational age of babies after they are born. The study will provide accurate, population-based rates of preterm birth in different settings and quantify the risks of neonatal mortality and morbidity by gestational age and birth weight in five South Asian and sub-Saharan African sites. METHODS: This study used on-going population-based cohort studies to recruit pregnant women early in pregnancy (<20 weeks) for a dating ultrasound scan. Implementation is harmonised across sites in Ghana, Tanzania, Zambia, Bangladesh and Pakistan with uniform protocols and standard operating procedures. Women whose pregnancies are confirmed to be between 8 to 19 completed weeks of gestation are enrolled into the study. These women are followed up to collect socio-demographic and morbidity data during the pregnancy. When they deliver, trained research assistants visit women within 72 hours to assess the baby for gestational maturity. They assess for neuromuscular and physical characteristics selected from the Ballard and Dubowitz maturation assessment scales. They also measure newborn anthropometry and assess feeding maturity of the babies. Computer machine learning techniques will be used to identify the most parsimonious group of signs that correctly predict gestational age compared to the early ultrasound date (the gold standard). This gestational age will be used to categorize babies into term, late preterm and early preterm groups. Further, the ultrasound-based gestational age will be used to calculate population-based rates of preterm birth. IMPORTANCE OF THE STUDY: The AMANHI gestational age study will make substantial contribution to improve identification of preterm babies by frontline health workers in low- and middle- income countries using simple evaluations. The study will provide accurate preterm birth estimates. This new information will be crucial to planning and delivery of interventions for improving preterm birth outcomes, particularly in South Asia and sub-Saharan Africa

Population-based rates, timing and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa: a multi-country prospective cohort study

BackgroundModelled mortality estimates have been useful for health programmes in low-income and middle-income countries. However, these estimates are often based on sparse and low-quality data. We aimed to generate high quality data about the burden, timing, and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa.MethodsIn this prospective cohort study done in 11 community-based research sites in south Asia and sub-Saharan Africa, between July, 2012, and February, 2016, we conducted population-based surveillance of women of reproductive age (15–49 years) to identify pregnancies, which were followed up to birth and 42 days post partum. We used standard operating procedures, data collection instruments, training, and standardisation to harmonise study implementation across sites. Verbal autopsies were done for deaths of all women of reproductive age, neonatal deaths, and stillbirths. Physicians used standardised methods for cause of death assignment. Site-specific rates and proportions were pooled at the regional level using a meta-analysis approach.FindingsWe identified 278 186 pregnancies and 263 563 births across the study sites, with outcomes ascertained for 269 630 (96·9%) pregnancies, including 8761 (3·2%) that ended in miscarriage or abortion. Maternal mortality ratios in sub-Saharan Africa (351 per 100 000 livebirths, 95% CI 168–732) were similar to those in south Asia (336 per 100 000 livebirths, 247–458), with far greater variability within sites in sub-Saharan Africa. Stillbirth and neonatal mortality rates were approximately two times higher in sites in south Asia than in sub-Saharan Africa (stillbirths: 35·1 per 1000 births, 95% CI 28·5–43·1 vs 17·1 per 1000 births, 12·5–25·8; neonatal mortality: 43·0 per 1000 livebirths, 39·0–47·3 vs 20·1 per 1000 livebirths, 14·6–27·6). 40–45% of pregnancy-related deaths, stillbirths, and neonatal deaths occurred during labour, delivery, and the 24 h postpartum period in both regions. Obstetric haemorrhage, non-obstetric complications, hypertensive disorders of pregnancy, and pregnancy-related infections accounted for more than three-quarters of maternal deaths and stillbirths. The most common causes of neonatal deaths were perinatal asphyxia (40%, 95% CI 39–42, in south Asia; 34%, 32–36, in sub-Saharan Africa) and severe neonatal infections (35%, 34–36, in south Asia; 37%, 34–39 in sub-Saharan Africa), followed by complications of preterm birth (19%, 18–20, in south Asia; 24%, 22–26 in sub-Saharan Africa).InterpretationThese results will contribute to improved global estimates of rates, timing, and causes of maternal and newborn deaths and stillbirths. Our findings imply that programmes in sub-Saharan Africa and south Asia need to further intensify their efforts to reduce mortality rates, which continue to be high. The focus on improving the quality of maternal intrapartum care and immediate newborn care must be further enhanced. Efforts to address perinatal asphyxia and newborn infections, as well as preterm birth, are critical to achieving survival goals in the Sustainable Development Goals era

Direct maternal morbidity and the risk of pregnancy-related deaths, stillbirths, and neonatal deaths in South Asia and sub-Saharan Africa: A population-based prospective cohort study in 8 countries

Background Maternal morbidity occurs several times more frequently than mortality, yet data on morbidity burden and its effect on maternal, foetal, and newborn outcomes are limited in low- and middle-income countries. We aimed to generate prospective, reliable population-based data on the burden of major direct maternal morbidities in the antenatal, intrapartum, and postnatal periods and its association with maternal, foetal, and neonatal death in South Asia and sub-Saharan Africa. Methods and findings This is a prospective cohort study, conducted in 9 research sites in 8 countries of South Asia and sub-Saharan Africa. We conducted population-based surveillance of women of reproductive age (15 to 49 years) to identify pregnancies. Pregnant women who gave consent were include in the study and followed up to birth and 42 days postpartum from 2012 to 2015. We used standard operating procedures, data collection tools, and training to harmonise study implementation across sites. Three home visits during pregnancy and 2 home visits after birth were conducted to collect maternal morbidity information and maternal, foetal, and newborn outcomes. We measured blood pressure and proteinuria to define hypertensive disorders of pregnancy and woman’s self-report to identify obstetric haemorrhage, pregnancy-related infection, and prolonged or obstructed labour. Enrolled women whose pregnancy lasted at least 28 weeks or those who died during pregnancy were included in the analysis. We used meta-analysis to combine site-specific estimates of burden, and regression analysis combining all data from all sites to examine associations between the maternal morbidities and adverse outcomes. Among approximately 735,000 women of reproductive age in the study population, and 133,238 pregnancies during the study period, only 1.6% refused consent. Of these, 114,927 pregnancies had morbidity data collected at least once in both antenatal and in postnatal period, and 114,050 of them were included in the analysis. Overall, 32.7% of included pregnancies had at least one major direct maternal morbidity; South Asia had almost double the burden compared to sub-Saharan Africa (43.9%, 95% CI 27.8% to 60.0% in South Asia; 23.7%, 95% CI 19.8% to 27.6% in sub-Saharan Africa). Antepartum haemorrhage was reported in 2.2% (95% CI 1.5% to 2.9%) pregnancies and severe postpartum in 1.7% (95% CI 1.2% to 2.2%) pregnancies. Preeclampsia or eclampsia was reported in 1.4% (95% CI 0.9% to 2.0%) pregnancies, and gestational hypertension alone was reported in 7.4% (95% CI 4.6% to 10.1%) pregnancies. Prolonged or obstructed labour was reported in about 11.1% (95% CI 5.4% to 16.8%) pregnancies. Clinical features of late third trimester antepartum infection were present in 9.1% (95% CI 5.6% to 12.6%) pregnancies and those of postpartum infection in 8.6% (95% CI 4.4% to 12.8%) pregnancies. There were 187 pregnancy-related deaths per 100,000 births, 27 stillbirths per 1,000 births, and 28 neonatal deaths per 1,000 live births with variation by country and region. Direct maternal morbidities were associated with each of these outcomes. Conclusions Our findings imply that health programmes in sub-Saharan Africa and South Asia must intensify their efforts to identify and treat maternal morbidities, which affected about one-third of all pregnancies and to prevent associated maternal and neonatal deaths and stillbirths