Background

An estimated 2.8 million neonatal deaths occur each year globally, which accounts for at least 45% of deaths in children aged less than 5 years. Birthweight and gestational age-specific mortality estimates are limited in low-resource countries like Uganda. A deeper analysis of mortality by birthweight and gestational age is critical in identifying the cause and potential solutions to decrease neonatal mortality.

Objectives

We studied mortality before discharge in relation to birthweight and gestational age using a large sample size from selected tertiary care facilities in Uganda.

Methods

We used secondary data from the East Africa Preterm Birth Initiative study conducted in six tertiary care facilities. Birth records of infants born between October 2016 and March 2019 with a gestational age greater than or equal to 24 weeks and/or birthweight greater than or equal to 500 g were reviewed for inclusion in the analysis. Newborn death before discharge was the outcome variable of interest. Multivariable Poisson regression modeling was used to explore birthweight and gestational age-specific mortality rate.

Results

We analysed 50 278 birth records. Among these 95.3% (47 913) were live births and 4.8% (2365) were stillbirths. Of the 47 913 live births, 50% (24 147) were males. Overall, pre-discharge mortality was 13.0 per 1000 live births. For each 1 kg increase in birthweight, mortality before discharge decreased by -0.016. As birthweight increases, the mortality before discharge decreased from 336 per 1000 live births among infants born between 500 and 999 g, to 4.7 per 1000 live births among infants born weighing 3500 to 3999 g, and increased again to 11.2 per 1000 live births among infants weighing more than 4500 g.

Conclusions

Our study highlights the need for further research to understand newborn survival across different birthweight and gestational categories.

BACKGROUND:Preterm birth (birth before 37 weeks of gestation) and its complications are the leading contributors to neonatal and under-5 mortality. The majority of neonatal deaths in Kenya and Uganda occur during the intrapartum and immediate postnatal period. This paper describes our study protocol for implementing and evaluating a package of facility-based interventions to improve care during this critical window. METHODS/DESIGN:This is a pair-matched, cluster randomized controlled trial across 20 facilities in Eastern Uganda and Western Kenya. The intervention facilities receive four components: (1) strengthening of routine data collection and data use activities; (2) implementation of the WHO Safe Childbirth Checklist modified for preterm birth; (3) PRONTO simulation training and mentoring to strengthen intrapartum and immediate newborn care; and (4) support of quality improvement teams. The control facilities receive both data strengthening and introduction of the modified checklist. The primary outcome for this study is 28-day mortality rate among preterm infants. The denominator will include all live births and fresh stillbirths weighing greater than 1000 g and less than 2500 g; all live births and fresh stillbirths weighing between 2501 and 3000 g with a documented gestational age less than 37 weeks. DISCUSSION:The results of this study will inform interventions to improve personnel and facility capacity to respond to preterm labor and delivery, as well as care for the preterm infant. TRIAL REGISTRATION:ClinicalTrials.gov, ID: NCT03112018 . Registered on 13 April 2017.

Background

Quality of care during the intrapartum and immediate postnatal period for maternal and newborn health remains a major challenge due to the multiple health system bottlenecks in low-income countries. Reports of complex interventions that have been effective in reducing maternal and newborn mortality in these settings are usually limited in description, which inhibits learning and replication. We present a detailed account of the Preterm Birth Initiative (PTBi) implementation process, experiences and lessons learnt to inform scale-up and replication.

Methods

Using the TiDieR framework, we detail how the PTBi implemented an integrated package of interventions through a pair-matched cluster randomized control trial in 20 health facilities in Migori County, Kenya, and the Busoga region in east central Uganda from 2016 to 2019. The package aimed to improve quality of care during the intrapartum and immediate postnatal period with a focus on preterm birth. The package included data strengthening (DS) and introduction of a modified WHO Safe Childbirth Checklist (mSCC), simulation-based training and mentoring (PRONTO), and a Quality Improvement (QI) Collaborative.

Results

In 2016, DS and mSCC were introduced to improve existing data processes and increase the quality of data for measures needed to evaluate study impact. PRONTO and QI interventions were then rolled out sequentially. While package components were implemented with fidelity, some implementation processes required contextual adaptation to allow alignment with national priorities and guidelines, and flexibility to optimize uptake.

Conclusion

Lessons learned included the importance of synergy between interventions, the need for local leadership engagement, and the value of strengthening local systems and resources. Adaptations of individual elements of the package to suit the local context were important for effective implementation, and the TIDieR framework provides the guidance needed in detailed description to replicate such a complex intervention in other settings. Detailed documentation of the implementation process of a complex intervention with mutually synergistic components can help contextualize trial results and potential for scale-up. The trial is registered at ClinicalTrials.gov NCT03112018 , registered December 2016, posted April 2017.

BACKGROUND: Quality improvement collaboratives (QIC) are an approach to accelerate the spread and impact of evidence-based interventions across health facilities, which are found to be particularly successful when combined with other interventions such as clinical skills training. We implemented a QIC as part of a quality improvement intervention package designed to improve newborn survival in Kenya and Uganda. We use a multi-method approach to describe how a QIC was used as part of an overall improvement effort and describe specific changes measured and participant perceptions of the QIC. METHODS: We examined QIC-aggregated run charts on three shared indicators related to uptake of evidence-based practices over time and conducted key informant interviews to understand participants perceptions of quality improvement practice. Run charts were evaluated for change from baseline medians. Interviews were analysed using framework analysis. RESULTS: Run charts for all indicators reflected an increase in evidence-based practices across both countries. In Uganda, pre-QIC median gestational age (GA) recording of 44% improved to 86%, while Kangaroo Mother Care (KMC) initiation went from 51% to 96% and appropriate antenatal corticosteroid (ACS) use increased from 17% to 74%. In Kenya, these indicators went from 82% to 96%, 4% to 74% and 4% to 57%, respectively. Qualitative results indicate that participants appreciated the experience of working with data, and the friendly competition of the QIC was motivating. The participants reported integration of the QIC with other interventions of the package as a benefit. CONCLUSIONS: In a QIC that demonstrated increased evidence-based practices, QIC participants point to data use, friendly competition and package integration as the drivers of success, despite challenges common to these settings such as health worker and resource shortages. TRIAL REGISTRATION NUMBER: NCT03112018.

Background

The WHO Safe Childbirth Checklist (SCC) contains 29 evidence-based practices (EBPs) across four pause points spanning admission to discharge. It has been shown to increase EBP uptake and has been tailored to specific contexts. However, little research has been conducted in East Africa on use of the SCC to improve intrapartum care, particularly for preterm birth despite its burden. We describe checklist adaptation, user acceptability, implementation and lessons learned.

Methods

The East Africa Preterm Birth Initiative (PTBi EA) modified the SCC for use in 23 facilities in Western Kenya and Eastern Uganda as part of a cluster randomized controlled trial evaluating a package of facility-based interventions to improve preterm birth outcomes. The modified SCC (mSCC) for prematurity included: addition of a triage pause point before admission; focus on gestational age assessment, identification and management of preterm labour; and alignment with national guidelines. Following introduction, implementation lasted 24 and 34 months in Uganda and Kenya respectively and was supported through complementary mentoring and data strengthening at all sites. PRONTO® simulation training and quality improvement (QI) activities further supported mSCC use at intervention facilities only. A mixed methods approach, including checklist monitoring, provider surveys and in-depth interviews, was used in this analysis.

Results

A total of 19,443 and 2229 checklists were assessed in Kenya and Uganda, respectively. In both countries, triage and admission pause points had the highest rates of completion. Kenya's completion was greater than 70% for all pause points; Uganda ranged from 39 to 75%. Intervention facilities exposed to PRONTO and QI had higher completion rates than control sites. Provider perceptions cited clinical utility of the checklist, particularly when integrated into patient charts. However, some felt it repeated information in other documentation tools. Completion was hindered by workload and staffing issues.

Conclusion

This study highlights the feasibility and importance of adaptation, iterative modification and complementary activities to reinforce SCC use. There are important opportunities to improve its clinical utility by the addition of prompts specific to the needs of different contexts. The trial assessing the PTBi EA intervention package was registered at ClinicalTrials.gov NCT03112018 Registered December 2016, retrospectively registered.

Background

Globally, there were 2.7 million neonatal deaths in 2015. Significant mortality reduction could be achieved by improving care in low- and middle-income countries (LMIC), where the majority of deaths occur. Determining the physical readiness of facilities to identify and manage complications is an essential component of strategies to reduce neonatal mortality.

Methods

We developed clinical cascades for 6 common neonatal conditions then utilized these to assess 23 health facilities in Kenya and Uganda at 2 time-points in 2016 and 2017. We calculated changes in resource availability over time by facility using McNemar's test. We estimated mean readiness and loss of readiness for the 6 conditions and 3 stages of care (identification, treatment, monitoring-modifying treatment). We estimated overall mean readiness and readiness loss across all conditions and stages. Finally, we compared readiness of facilities with a newborn special care unit (NSCU) to those without using the two-sample test of proportions.

Results

The cascade model estimated mean readiness of 26.3-26.6% across the 3 stages for all conditions. Mean readiness ranged from 11.6% (respiratory distress-apnea) to 47.8% (essential newborn care) across both time-points. The model estimated overall mean readiness loss of 30.4-31.9%. There was mild to moderate variability in the timing of readiness loss, with the majority occurring in the identification stage. Overall mean readiness was higher among facilities with a NSCU (36.8%) compared to those without (20.0%).

Conclusion

The cascade model provides a novel approach to quantitatively assess physical readiness for neonatal care. Among 23 facilities in Kenya and Uganda, we identified a consistent pattern of 30-32% readiness loss across cascades and stages. This aggregate measure could be used to monitor and compare readiness at the facility-, health system-, or national-level. Estimates of readiness and loss of readiness may help guide strategies to improve care, prioritize resources, and promote neonatal survival in LMICs.

Background

Although gains in newborn survival have been achieved in many low-income and middle-income countries, reductions in stillbirth and neonatal mortality have been slow. Prematurity complications are a major driver of stillbirth and neonatal mortality. We aimed to assess the effect of a quality improvement package for intrapartum and immediate newborn care on stillbirth and preterm neonatal survival in Kenya and Uganda, where evidence-based practices are often underutilised.

Methods

This unblinded cluster-randomised controlled trial was done in western Kenya and eastern Uganda at facilities that provide 24-h maternity care with at least 200 births per year. The study assessed outcomes of low-birthweight and preterm babies. Eligible facilities were pair-matched and randomly assigned (1:1) into either the intervention group or the control group. All facilities received maternity register data strengthening and a modified WHO Safe Childbirth Checklist; facilities in the intervention group additionally received provider mentoring using PRONTO simulation and team training as well as quality improvement collaboratives. Liveborn or fresh stillborn babies who weighed between 1000 g and 2500 g, or less than 3000 g with a recorded gestational age of less than 37 weeks, were included in the analysis. We abstracted data from maternity registers for maternal and birth outcomes. Follow-up was done by phone or in person to identify the status of the infant at 28 days. The primary outcome was fresh stillbirth and 28-day neonatal mortality. This trial is registered with ClinicalTrials.gov, NCT03112018.

Findings

Between Oct 1, 2016, and April 30, 2019, 20 facilities were randomly assigned to either the intervention group (n=10) or the control group (n=10). Among 5343 eligible babies in these facilities, we assessed outcomes of 2938 newborn and fresh stillborn babies (1447 in the intervention and 1491 in the control group). 347 (23%) of 1491 infants in the control group were stillborn or died in the neonatal period compared with 221 (15%) of 1447 infants in the intervention group at 28 days (odds ratio 0·66, 95% CI 0·54-0·81). No harm or adverse effects were found.

Interpretation

Fresh stillbirth and neonatal mortality among low-birthweight and preterm babies can be decreased using a package of interventions that reinforces evidence-based practices and invests in health system strengthening.

Funding

Bill & Melinda Gates Foundation.

In Africa, antiretroviral therapy (ART) is delivered with limited laboratory monitoring, often none. In 2003-2004, investigators in the Development of Antiretroviral Therapy in Africa (DART) Trial randomized persons initiating ART in Uganda and Zimbabwe to either laboratory and clinical monitoring (LCM) or clinically driven monitoring (CDM). CD4 cell counts were measured every 12 weeks in both groups but were only returned to treating clinicians for management in the LCM group. Follow-up continued through 2008. In observational analyses, dynamic marginal structural models on pooled randomized groups were used to estimate survival under different monitoring-frequency and clinical/immunological switching strategies. Assumptions included no direct effect of randomized group on mortality or confounders and no unmeasured confounders which influenced treatment switch and mortality or treatment switch and time-dependent covariates. After 48 weeks of first-line ART, 2,946 individuals contributed 11,351 person-years of follow-up, 625 switches, and 179 deaths. The estimated survival probability after a further 240 weeks for post-48-week switch at the first CD4 cell count less than 100 cells/mm(3) or non-Candida World Health Organization stage 4 event (with CD4 count <250) was 0.96 (95% confidence interval (CI): 0.94, 0.97) with 12-weekly CD4 testing, 0.96 (95% CI: 0.95, 0.97) with 24-weekly CD4 testing, 0.95 (95% CI: 0.93, 0.96) with a single CD4 test at 48 weeks (baseline), and 0.92 (95% CI: 0.91, 0.94) with no CD4 testing. Comparing randomized groups by 48-week CD4 count, the mortality risk associated with CDM versus LCM was greater in persons with CD4 counts of <100 (hazard ratio = 2.4, 95% CI: 1.3, 4.3) than in those with CD4 counts of ≥100 (hazard ratio = 1.1, 95% CI: 0.8, 1.7; interaction P = 0.04). These findings support a benefit from identifying patients immunologically failing first-line ART at 48 weeks.