Building a predictive model of low birth weight in low- and middle-income countries: a prospective cohort study.

BACKGROUND: Low birth weight (LBW, < 2500 g) infants are at significant risk for death and disability. Improving outcomes for LBW infants requires access to advanced neonatal care, which is a limited resource in low- and middle-income countries (LMICs). Predictive modeling might be useful in LMICs to identify mothers at high-risk of delivering a LBW infant to facilitate referral to centers capable of treating these infants. METHODS: We developed predictive models for LBW using the NICHD Global Network for Women's and Children's Health Research Maternal and Newborn Health Registry. This registry enrolled pregnant women from research sites in the Democratic Republic of the Congo, Zambia, Kenya, Guatemala, India (2 sites: Belagavi, Nagpur), Pakistan, and Bangladesh between January 2017 - December 2020. We tested five predictive models: decision tree, random forest, logistic regression, K-nearest neighbor and support vector machine. RESULTS: We report a rate of LBW of 13.8% among the eight Global Network sites from 2017-2020, with a range of 3.8% (Kenya) and approximately 20% (in each Asian site). Of the five models tested, the logistic regression model performed best with an area under the curve of 0.72, an accuracy of 61% and a recall of 72%. All of the top performing models identified clinical site, maternal weight, hypertensive disorders, severe antepartum hemorrhage and antenatal care as key variables in predicting LBW. CONCLUSIONS: Predictive modeling can identify women at high risk for delivering a LBW infant with good sensitivity using clinical variables available prior to delivery in LMICs. Such modeling is the first step in the development of a clinical decision support tool to assist providers in decision-making regarding referral of these women prior to delivery. Consistent referral of women at high-risk for delivering a LBW infant could have extensive public health consequences in LMICs by directing limited resources for advanced neonatal care to the infants at highest risk.

Delayed and Interrupted Ventilation with Excess Suctioning after Helping Babies Breathe with Congolese Birth Attendants.

There is a substantial gap in our understanding of resuscitation practices following Helping Babies Breathe (HBB) training. We sought to address this gap through an analysis of observed resuscitations following HBB 2nd edition training in the Democratic Republic of the Congo. This is a secondary analysis of a clinical trial evaluating the effect of resuscitation training and electronic heart rate monitoring on stillbirths. We included in-born, liveborn neonates ≥28 weeks gestation whose resuscitation care was directly observed and documented. For the 2592 births observed, providers dried/stimulated before suctioning in 97% of cases and suctioned before ventilating in 100%. Only 19.7% of newborns not breathing well by 60 s (s) after birth ever received ventilation. Providers initiated ventilation at a median 347 s (>five minutes) after birth; no cases were initiated within the Golden Minute. During 81 resuscitations involving ventilation, stimulation and suction both delayed and interrupted ventilation with a median 132 s spent drying/stimulating and 98 s suctioning. This study demonstrates that HBB-trained providers followed the correct order of resuscitation steps. Providers frequently failed to initiate ventilation. When ventilation was initiated, it was delayed and interrupted by stimulation and suctioning. Innovative strategies targeting early and continuous ventilation are needed to maximize the impact of HBB.

Cost-effectiveness of low-dose aspirin for the prevention of preterm birth: a prospective study of the Global Network for Women's and Children's Health Research.

BACKGROUND: Premature birth is associated with an increased risk of mortality and morbidity, and strategies to prevent preterm birth are few in number and resource intensive. In 2020, the ASPIRIN trial showed the efficacy of low-dose aspirin (LDA) in nulliparous, singleton pregnancies for the prevention of preterm birth. We sought to investigate the cost-effectiveness of this therapy in low-income and middle-income countries. METHODS: In this post-hoc, prospective, cost-effectiveness study, we constructed a probabilistic decision tree model to compare the benefits and costs of LDA treatment compared with standard care using primary data and published results from the ASPIRIN trial. In this analysis from a health-care sector perspective, we considered the costs and effects of LDA treatment, pregnancy outcomes, and neonatal health-care use. We did sensitivity analyses to understand the effect of the price of the LDA regimen, and the effectiveness of LDA in reducing both preterm birth and perinatal death. FINDINGS: In model simulations, LDA was associated with 141 averted preterm births, 74 averted perinatal deaths, and 31 averted hospitalisations per 10 000 pregnancies. The reduction in hospitalisation resulted in a cost of US$248 per averted preterm birth, $471 per averted perinatal death, and $15·95 per disability-adjusted life year. INTERPRETATION: LDA treatment in nulliparous, singleton pregnancies is a low-cost, effective treatment to reduce preterm birth and perinatal death. The low cost per disability-adjusted life year averted strengthens the evidence in support of prioritising the implementation of LDA in publicly funded health care in low-income and middle-income countries. FUNDING: Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Perceptions and experiences of Congolese midwives implementing a low-cost battery-operated heart rate meter during newborn resuscitation.

Background: 900,000 newborns die from respiratory depression each year; nearly all of these deaths occur in low- and middle-income countries. Deaths from respiratory depression are reduced by evidence-based resuscitation. Electronic heart rate monitoring provides a sensitive indicator of the neonate's status to inform resuscitation care, but is infrequently used in low-resource settings. In a recent trial in the Democratic Republic of the Congo, midwives used a low-cost, battery-operated heart rate meter (NeoBeat) to continuously monitor heart rate during resuscitations. We explored midwives' perceptions of NeoBeat including its utility and barriers and facilitators to use. Methods: After a 20-month intervention in which midwives from three facilities used NeoBeat during resuscitations, we surveyed midwives and conducted focus group discussions (FGDs) regarding the incorporation of NeoBeat into clinical care. FGDs were conducted in Lingala, the native language, then transcribed and translated from Lingala to French to English. We analyzed data by: (1) coding of transcripts using Nvivo, (2) comparison of codes to identify patterns in the data, and (3) grouping of codes into categories by two independent reviewers, with final categories determined by consensus. Results: Each midwife from Facility A used NeoBeat on an estimated 373 newborns, while each midwife at facilities B and C used NeoBeat an average 24 and 47 times, respectively. From FGDs with 30 midwives, we identified five main categories of perceptions and experiences regarding the use of NeoBeat: (1) Providers' initial skepticism evolved into pride and a belief that NeoBeat was essential to resuscitation care, (2) Providers viewed NeoBeat as enabling their resuscitation and increasing their capacity, (3) NeoBeat helped providers identify flaccid newborns as liveborn, leading to hope and the perception of saving of lives, (4) Challenges of use of NeoBeat included cleaning, charging, and insufficient quantity of devices, and (5) Providers desired to continue using the device and to expand its use beyond resuscitation and their own facilities. Conclusion: Midwives perceived that NeoBeat enabled their resuscitation practices, including assisting them in identifying non-breathing newborns as liveborn. Increasing the quantity of devices per facility and developing systems to facilitate cleaning and charging may be critical for scale-up.

Limiting adverse birth outcomes in resource-limited settings (LABOR): protocol of a prospective intrapartum cohort study.

Background: Each year, nearly 300,000 women and 5 million fetuses or neonates die during childbirth or shortly thereafter, a burden concentrated disproportionately in low- and middle-income countries. Identifying women and their fetuses at risk for intrapartum-related morbidity and death could facilitate early intervention. Methods: The Limiting Adverse Birth Outcomes in Resource-Limited Settings (LABOR) Study is a multi-country, prospective, observational cohort designed to exhaustively document the course and outcomes of labor, delivery, and the immediate postpartum period in settings where adverse outcomes are frequent. The study is conducted at four hospitals across three countries in Ghana, India, and Zambia. We will enroll approximately 12,000 women at presentation to the hospital for delivery and follow them and their fetuses/newborns throughout their labor and delivery course, postpartum hospitalization, and up to 42 days thereafter. The co-primary outcomes are composites of maternal (death, hemorrhage, hypertensive disorders, infection) and fetal/neonatal adverse events (death, encephalopathy, sepsis) that may be attributed to the intrapartum period. The study collects extensive physiologic data through the use of physiologic sensors and employs medical scribes to document examination findings, diagnoses, medications, and other interventions in real time. Discussion: The goal of this research is to produce a large, sharable dataset that can be used to build statistical algorithms to prospectively stratify parturients according to their risk of adverse outcomes. We anticipate this research will inform the development of new tools to reduce peripartum morbidity and mortality in low-resource settings.

Gestational weight gain in 4 low- and middle-income countries and associations with birth outcomes: a secondary analysis of the Women First Trial.

BACKGROUND: Adequate gestational weight gain (GWG) is essential for healthy fetal growth. However, in low- and middle-income countries, where malnutrition is prevalent, little information is available about GWG and how it might be modified by nutritional status and interventions. OBJECTIVE: We describe GWG and its associations with fetal growth and birth outcomes. We also examined the extent to which prepregnancy BMI, and preconception and early weight gain modify GWG, and its effects on fetal growth. METHODS: This was a secondary analysis of the Women First Trial, including 2331 women within the Democratic Republic of Congo (DRC), Guatemala, India, and Pakistan, evaluating weight gain from enrollment to ∼12 weeks of gestation and GWG velocity (kg/wk) between ∼12 and 32 weeks of gestation. Adequacy of GWG velocity was compared with 2009 Institute of Medicine recommendations, according to maternal BMI. Early weight gain (EWG), GWG velocity, and adequacy of GWG were related to birth outcomes using linear and Poisson models. RESULTS: GWG velocity (mean ± SD) varied by site: 0.22 ± 0.15 kg/wk in DRC, 0.30 ± 0.23 in Pakistan, 0.31 ± 0.14 in Guatemala, and 0.39 ± 0.13 in India, (P <0.0001). An increase of 0.1 kg/wk in maternal GWG was associated with a 0.13 cm (95% CI: 0.07, 0.18, P <0.001) increase in birth length and a 0.032 kg (0.022, 0.042, P <0.001) increase in birth weight. Compared to women with inadequate GWG, women who had adequate GWG delivered newborns with a higher mean length and weight: 47.98 ± 2.04 cm compared with 47.40 ± 2.17 cm (P <0.001) and 2.864 ± 0.425 kg compared with 2.764 ± 0.418 kg (P <0.001). Baseline BMI, EWG, and GWG were all associated with birth length and weight. CONCLUSIONS: These results underscore the importance of adequate maternal nutrition both before and during pregnancy as a potentially modifiable factor to improve fetal growth.

Innovations in Cardiorespiratory Monitoring to Improve Resuscitation With Helping Babies Breathe.

Ninety percent of intrapartum-related neonatal deaths are attributable to respiratory depression, with the vast majority of these deaths occurring in low- and lower-middle-income countries. Neonatal resuscitation training with Helping Babies Breathe (HBB) decreases mortality from respiratory depression. Cardiorespiratory monitoring in conjunction with HBB can provide valuable resuscitation feedback for both training and bedside purposes. In this article, we discuss 3 innovations that couple cardiorespiratory monitoring with HBB: NeoNatalie Live, the Augmented Infant Resuscitator, and NeoBeat. NeoNatalie Live is a high-fidelity manikin that facilitates bag mask ventilation training through case scenarios of varying difficulty. The Augmented Infant Resuscitator is added in-line between a face mask and ventilation bag during bag mask ventilation training to provide users with real-time feedback on ventilation quality. NeoBeat is a battery-operated heart rate meter that digitally displays the newborn heart rate during bedside resuscitations. For each innovation, we review details of the device, implementation in the field, and areas for further research. Using early experience implementing these devices, we suggest building blocks for effective translation of training into improved care. We also highlight general challenges in implementation of devices in facilities in low- and lower-middle-income countries including considerations for training, adaptations to existing workflow, and integration into the ecosystem. Although the devices highlighted in this article hold promise, more data are needed to understand their impact on newborn outcomes.

Digital Health Innovations, Tools, and Resources to Support Helping Babies Survive Programs.

The Helping Babies Survive (HBS) initiative features a suite of evidence-based curricula and simulation-based training programs designed to provide health workers in low- and middle-income countries (LMICs) with the knowledge, skills, and competencies to prevent, recognize, and manage leading causes of newborn morbidity and mortality. Global scale-up of HBS initiatives has been rapid. As HBS initiatives rolled out across LMIC settings, numerous bottlenecks, gaps, and barriers to the effective, consistent dissemination and implementation of the programs, across both the pre- and in-service continuums, emerged. Within the first decade of expansive scale-up of HBS programs, mobile phone ownership and access to cellular networks have also concomitantly surged in LMICs. In this article, we describe a number of HBS digital health innovations and resources that have been developed from 2010 to 2020 to support education and training, data collection for monitoring and evaluation, clinical decision support, and quality improvement. Helping Babies Survive partners and stakeholders can potentially integrate the described digital tools with HBS dissemination and implementation efforts in a myriad of ways to support low-dose high-frequency skills practice, in-person refresher courses, continuing medical and nursing education, on-the-job training, or peer-to-peer learning, and strengthen data collection for key newborn care and quality improvement indicators and outcomes. Thoughtful integration of purpose-built digital health tools, innovations, and resources may assist HBS practitioners to more effectively disseminate and implement newborn care programs in LMICs, and facilitate progress toward the achievement of Sustainable Development Goal health goals, targets, and objectives.

Helping Babies Survive Programs as an Impetus for Quality Improvement.

Achieving the ambitious reduction in global neonatal mortality targeted in the Sustainable Development Goals and Every Newborn Action Plan will require reducing geographic disparities in newborn deaths through targeted implementation of evidence-based practices. Helping Babies Survive, a suite of educational programs targeting the 3 leading causes of neonatal mortality, has been commonly used to educate providers in evidence-based practices in low-resource settings. Quality improvement (QI) can play a pivotal role in translating this education into improved care. Measurement of key process and outcome indicators, derived from the algorithms ("Action Plans") central to these training programs, can assist health care providers in understanding the baseline quality of their care, identifying gaps, and assessing improvement. Helping Babies Survive has been the focus of QI programs in Kenya, Nepal, Honduras, and Ethiopia, with critical lessons learned regarding the challenge of measurement, necessity of facility-based QI mentorship and multidisciplinary teams, and importance of systemic commitment to improvement in promoting a culture of QI. Complementing education with QI strategies to identify and close remaining gaps in newborn care will be essential to achieving the Sustainable Development Goals and Every Newborn Action Plan targets in the coming decade.