Effectiveness of kangaroo mother care before clinical stabilisation versus standard care among neonates at five hospitals in Uganda (OMWaNA): a parallel-group, individually randomised controlled trial and economic evaluation.

BACKGROUND: Preterm birth is the leading cause of death in children younger than 5 years worldwide. WHO recommends kangaroo mother care (KMC); however, its effects on mortality in sub-Saharan Africa and its relative costs remain unclear. We aimed to compare the effectiveness, safety, costs, and cost-effectiveness of KMC initiated before clinical stabilisation versus standard care in neonates weighing up to 2000 g. METHODS: We conducted a parallel-group, individually randomised controlled trial in five hospitals across Uganda. Singleton or twin neonates aged younger than 48 h weighing 700-2000 g without life-threatening clinical instability were eligible for inclusion. We randomly assigned (1:1) neonates to either KMC initiated before stabilisation (intervention group) or standard care (control group) via a computer-generated random allocation sequence with permuted blocks of varying sizes, stratified by birthweight and recruitment site. Parents, caregivers, and health-care workers were unmasked to treatment allocation; however, the independent statistician who conducted the analyses was masked. After randomisation, neonates in the intervention group were placed prone and skin-to-skin on the caregiver's chest, secured with a KMC wrap. Neonates in the control group were cared for in an incubator or radiant heater, as per hospital practice; KMC was not initiated until stability criteria were met. The primary outcome was all-cause neonatal mortality at 7 days, analysed by intention to treat. The economic evaluation assessed incremental costs and cost-effectiveness from a disaggregated societal perspective. This trial is registered with ClinicalTrials.gov, NCT02811432. FINDINGS: Between Oct 9, 2019, and July 31, 2022, 2221 neonates were randomly assigned: 1110 (50·0%) neonates to the intervention group and 1111 (50·0%) neonates to the control group. From randomisation to age 7 days, 81 (7·5%) of 1083 neonates in the intervention group and 83 (7·5%) of 1102 neonates in the control group died (adjusted relative risk [RR] 0·97 [95% CI 0·74-1·28]; p=0·85). From randomisation to 28 days, 119 (11·3%) of 1051 neonates in the intervention group and 134 (12·8%) of 1049 neonates in the control group died (RR 0·88 [0·71-1·09]; p=0·23). Even if policy makers place no value on averting neonatal deaths, the intervention would have 97% probability from the provider perspective and 84% probability from the societal perspective of being more cost-effective than standard care. INTERPRETATION: KMC initiated before stabilisation did not reduce early neonatal mortality; however, it was cost-effective from the societal and provider perspectives compared with standard care. Additional investment in neonatal care is needed for increased impact, particularly in sub-Saharan Africa. FUNDING: Joint Global Health Trials scheme of the Department of Health and Social Care, Foreign, Commonwealth and Development Office, UKRI Medical Research Council, and Wellcome Trust; Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Assessing a digital technology-supported community child health programme in India using the Social Return on Investment framework.

An estimated 5.0 million children aged under 5 years died in 2020, with 82% of these deaths occurring in sub-Saharan Africa and southern Asia. Over one-third of Mumbai's population has limited access to healthcare, and child health outcomes are particularly grave among the urban poor. We describe the implementation of a digital technology-based child health programme in Mumbai and evaluate its holistic impact. Using an artificial intelligence (AI)-powered mobile health platform, we developed a programme for community-based management of child health. Leveraging an existing workforce, community health workers (CHW), the programme was designed to strengthen triage and referral, improve access to healthcare in the community, and reduce dependence on hospitals. A Social Return on Investment (SROI) framework is used to evaluate holistic impact. The programme increased the proportion of illness episodes treated in the community from 4% to 76%, subsequently reducing hospitalisations and out-of-pocket expenditure on private healthcare providers. For the total investment of Indian Rupee (INR) 2,632,271, the social return was INR 34,435,827, delivering an SROI ratio of 13. The annual cost of the programme per child was INR 625. Upskilling an existing workforce such as CHWs, with the help of AI-driven decision- support tools, has the potential to extend capacity for critical health services into community settings. This study provides a blueprint for evaluating the holistic impact of health technologies using evidence-based tools like SROI. These findings have applicability across income settings, offering clear rationale for the promotion of technology-supported interventions that strengthen healthcare delivery.

Process and costs for readiness to safely implement immediate kangaroo mother care: a mixed methods evaluation from the OMWaNA trial at five hospitals in Uganda.

BACKGROUND: Preterm birth complications result in > 1 million child deaths annually, mostly in low- and middle-income countries. A World Health Organisation (WHO)-led trial in hospitals with intensive care reported reduced mortality within 28 days among newborns weighing 1000-1799 g who received immediate kangaroo mother care (iKMC) compared to those who received standard care. Evidence is needed regarding the process and costs of implementing iKMC, particularly in non-intensive care settings. METHODS: We describe actions undertaken to implement iKMC, estimate financial and economic costs of essential resources and infrastructure improvements, and assess readiness for newborn care after these improvements at five Ugandan hospitals participating in the OMWaNA trial. We estimated costs from a health service provider perspective and explored cost drivers and cost variation across hospitals. We assessed readiness to deliver small and sick newborn care (WHO level-2) using a tool developed by Newborn Essential Solutions and Technologies and the United Nations Children's Fund. RESULTS: Following the addition of space to accommodate beds for iKMC, floor space in the neonatal units ranged from 58 m2 to 212 m2. Costs of improvements were lowest at the national referral hospital (financial: $31,354; economic: $45,051; 2020 USD) and varied across the four smaller hospitals (financial: $68,330-$95,796; economic: $99,430-$113,881). In a standardised 20-bed neonatal unit offering a level of care comparable to the four smaller hospitals, the total financial cost could be in the range of $70,000 to $80,000 if an existing space could be repurposed or remodelled, or $95,000 if a new unit needed to be constructed. Even after improvements, the facility assessments demonstrated broad variability in laboratory and pharmacy capacity as well as the availability of essential equipment and supplies. CONCLUSIONS: These five Ugandan hospitals required substantial resource inputs to allow safe implementation of iKMC. Before widespread scale-up of iKMC, the affordability and efficiency of this investment must be assessed, considering variation in costs across hospitals and levels of care. These findings should help inform planning and budgeting as well as decisions about if, where, and how to implement iKMC, particularly in settings where space, devices, and specialised staff for newborn care are unavailable. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02811432 . Registered: 23 June 2016.

Infant mortality and growth failure after oral azithromycin among low birthweight and underweight neonates: A subgroup analysis of a randomized controlled trial.

BACKGROUND: Low birthweight (birthweight <2500 grams, g) and underweight (weight-for-age Z-score, WAZ, < -2) infants have higher risk of poor outcomes compared to their well-nourished peers. We evaluated the role of azithromycin for reducing mortality and improving growth outcomes in low birthweight and/or underweight infants. METHODS: Infants aged 8-27 days of age weighing ≥2500 g at enrollment in Burkina Faso were randomized 1:1 to a single, oral dose of azithromycin (20 mg/kg) or matching placebo. We evaluated mortality and anthropometric outcomes in four subgroups: 1) both low birthweight and underweight at enrollment; 2) low birthweight-only; 3) underweight-only; 4) neither low birthweight nor underweight. FINDINGS: Of 21,832 enrolled infants, 21,320 (98%) had birthweight measurements and included in this analysis. Of these, 747 (3%) were both low birthweight and underweight, 972 (5%) were low birthweight-only, 825 (4%) were underweight-only, and 18,776 (88%) were neither low birthweight nor underweight. Infants who were both low birthweight and underweight receiving azithromycin had lower odds of underweight at 6 months compared to placebo (OR 0.65, 95% CI 0.44 to 0.95), but the treatment group by subgroup interaction was not statistically significant (P = 0.06). We did not find evidence of a difference between groups for other outcomes in any subgroup. INTERPRETATION: Azithromycin may have some growth-promoting benefits for the highest risk infants, but we were unable to demonstrate a difference in most outcomes in low birthweight and underweight infants. As a secondary analysis of a trial, this study was underpowered for rare outcomes such as mortality. TRIAL REGISTRATION: ClinicalTrials.gov NCT03682653.

Predicting the risk of 7-day readmission in late preterm infants in California: A population-based cohort study.

Background and aims: The American Academy of Pediatrics describes late preterm infants, born at 34 to 36 completed weeks' gestation, as at-risk for rehospitalization and severe morbidity as compared to term infants. While there are prediction models that focus on specific morbidities, there is limited research on risk prediction for early readmission in late preterm infants. The aim of this study is to derive and validate a model to predict 7-day readmission. Methods: This is a population-based retrospective cohort study of liveborn infants in California between January 2007 to December 2011. Birth certificates, maintained by California Vital Statistics, were linked to a hospital discharge, emergency department, and ambulatory surgery records maintained by the California Office of Statewide Health Planning and Development. Random forest and logistic regression were used to identify maternal and infant variables of importance, test for association, and develop and validate a predictive model. The predictive model was evaluated for discrimination and calibration. Results: We restricted the sample to healthy late preterm infants (n = 122,014), of which 4.1% were readmitted to hospital within 7-day after birth discharge. The random forest model with 24 variables had better predictive ability than the 8 variable logistic model with c-statistic of 0.644 (95% confidence interval 0.629, 0.659) in the validation data set and Brier score of 0.0408. The eight predictors of importance length of stay, delivery method, parity, gestational age, birthweight, race/ethnicity, phototherapy at birth hospitalization, and pre-existing or gestational diabetes were used to drive individual risk scores. The risk stratification had the ability to identify an estimated 19% of infants at greatest risk of readmission. Conclusions: Our 7-day readmission predictive model had moderate performance in differentiating at risk late preterm infants. Future studies might benefit from inclusion of more variables and focus on hospital practices that minimize risk.

Incidence, Risk Factors, and Reasons for 30-Day Hospital Readmission Among Healthy Late Preterm Infants.

OBJECTIVE: Late preterm infants have an increased risk of morbidity relative to term infants. We sought to determine the rate, temporal trend, risk factors, and reasons for 30-day readmission. METHODS: This is a retrospective cohort study of infants born at 34 to 42 weeks' gestation in California between January 1, 2011, and December 31, 2017. Birth certificates maintained by California Vital Statistics were linked to discharge records maintained by the California Office of Statewide Health Planning and Development. Multivariable logistic regression was used to identify risk factors and derive a predictive model. RESULTS: Late preterm infants represented 4.3% (n = 122 014) of the study cohort (n = 2 824 963), of which 5.9% (n = 7243) were readmitted within 30 days. Compared to term infants, late preterm infants had greater odds of readmission (odds ratio [OR]: 2.34 [95% confidence interval (CI): 2.28-2.40]). The temporal trend indicated increases in all-cause and jaundice-specific readmission infants (P < .001). The common diagnoses at readmission were jaundice (58.9%), infections (10.8%), and respiratory complications (3.5%). In the adjusted model, factors that were associated with greater odds of readmission included assisted vaginal birth, maternal age ≥34 years, diabetes, chorioamnionitis, and primiparity. The model had predictive ability of 60% (c-statistic 0.603 [95% CI: 0.596-0.610]) in late preterm infants who had <5 days length of stay at birth. CONCLUSION: The findings contribute important information on what factors increase or decrease the risk of readmission. Longitudinal studies are needed to examine promising hospital predischarge and follow-up care practices.

Preterm care during the COVID-19 pandemic: A comparative risk analysis of neonatal deaths averted by kangaroo mother care versus mortality due to SARS-CoV-2 infection.

BACKGROUND: COVID-19 is disrupting health services for mothers and newborns, particularly in low- and middle-income countries (LMIC). Preterm newborns are particularly vulnerable. We undertook analyses of the benefits of kangaroo mother care (KMC) on survival among neonates weighing ≤2000 g compared with the risk of SARS-CoV-2 acquired from infected mothers/caregivers. METHODS: We modelled two scenarios over 12 months. Scenario 1 compared the survival benefits of KMC with universal coverage (99%) and mortality risk due to COVID-19. Scenario 2 estimated incremental deaths from reduced coverage and complete disruption of KMC. Projections were based on the most recent data for 127 LMICs (~90% of global births), with results aggregated into five regions. FINDINGS: Our worst-case scenario (100% transmission) could result in 1,950 neonatal deaths from COVID-19. Conversely, 125,680 neonatal lives could be saved with universal KMC coverage. Hence, the benefit of KMC is 65-fold higher than the mortality risk of COVID-19. If recent evidence of 10% transmission was applied, the ratio would be 630-fold. We estimated a 50% reduction in KMC coverage could result in 12,570 incremental deaths and full disruption could result in 25,140 incremental deaths, representing a 2·3-4·6% increase in neonatal mortality across the 127 countries. INTERPRETATION: The survival benefit of KMC far outweighs the small risk of death due to COVID-19. Preterm newborns are at risk, especially in LMICs where the consequences of disruptions are substantial. Policymakers and healthcare professionals need to protect services and ensure clearer messaging to keep mothers and newborns together, even if the mother is SARS-CoV-2-positive. FUNDING: Eunice Kennedy Shriver National Institute of Child Health & Human Development; Bill & Melinda Gates Foundation; Elma Philanthropies; Wellcome Trust; and Joint Global Health Trials scheme of Department of Health and Social Care, Department for International Development, Medical Research Council, and Wellcome Trust.

Small and sick newborn care during the COVID-19 pandemic: global survey and thematic analysis of healthcare providers' voices and experiences.

INTRODUCTION: The COVID-19 pandemic is disrupting health systems globally. Maternity care disruptions have been surveyed, but not those related to vulnerable small newborns. We aimed to survey reported disruptions to small and sick newborn care worldwide and undertake thematic analysis of healthcare providers' experiences and proposed mitigation strategies. METHODS: Using a widely disseminated online survey in three languages, we reached out to neonatal healthcare providers. We collected data on COVID-19 preparedness, effects on health personnel and on newborn care services, including kangaroo mother care (KMC), as well as disruptors and solutions. RESULTS: We analysed 1120 responses from 62 countries, mainly low and middle-income countries (LMICs). Preparedness for COVID-19 was suboptimal in terms of guidelines and availability of personal protective equipment. One-third reported routine testing of all pregnant women, but 13% had no testing capacity at all. More than 85% of health personnel feared for their own health and 89% had increased stress. Newborn care practices were disrupted both due to reduced care-seeking and a compromised workforce. More than half reported that evidence-based interventions such as KMC were discontinued or discouraged. Separation of the mother-baby dyad was reported for both COVID-positive mothers (50%) and those with unknown status (16%). Follow-up care was disrupted primarily due to families' fear of visiting hospitals (~73%). CONCLUSION: Newborn care providers are stressed and there is lack clarity and guidelines regarding care of small newborns during the pandemic. There is an urgent need to protect life-saving interventions, such as KMC, threatened by the pandemic, and to be ready to recover and build back better.

Cohort study of neonatal resuscitation skill retention in frontline healthcare facilities in Bihar, India, after PRONTO simulation training.

BACKGROUND: Use of simulation in neonatal resuscitation (NR) training programmes has increased throughout low-income and middle-income countries. Many of such programmes have demonstrated a positive impact on NR knowledge and skill acquisition along with reduction of early neonatal mortality and fresh stillbirth rates. However, NR skill retention after simulation programmes remains a challenge. METHODS: This study assessed facility level NR skill retention after PRONTO International's simulation training in Bihar, India. Training was conducted within CARE India's statewide in-job, on-site Apatkaleen Matritva evam Navjat Tatparta mentoring programme as part of a larger quality improvement and health systems strengthening initiative. Public sector facilities were initially offered training, facilitated by trained nursing graduates, during 8-month phases between September 2015 and January 2017. Repeat training began in February 2018 and was facilitated by peers. NR skills in simulated resuscitations were assessed at the facility level at the midpoint and endpoint of initial training and prior to and at the midpoint of repeat training. RESULTS: Facilities administering effective positive pressure ventilation and assessing infant heart rate increased (31.1% and 13.1%, respectively, both p=0.03) from midinitial to postinitial training (n=64 primary health centres (PHCs) and 192 simulations). This was followed by a 26.2% and 20.9% decline in these skills respectively over the training gap (p≤0.01). A significant increase (16.1%, p=0.04) in heart rate assessment was observed by the midpoint of repeat training with peer facilitators (n=45 PHCs and 90 simulations). No significant change was observed in other skills assessed. CONCLUSIONS: Despite initial improvement in select NR skills, deterioration was observed at a facility-level post-training. Given the technical nature of NR skills and the departure these skills represent from traditional practices in Bihar, refresher trainings at shorter intervals are likely necessary. Very limited evidence suggests peer simulation facilitators may enable such increased training frequency, but further study is required.

Development and validation of a simplified score to predict neonatal mortality risk among neonates weighing 2000 g or less (NMR-2000): an analysis using data from the UK and The Gambia.

BACKGROUND: 78% of neonatal deaths occur in sub-Saharan Africa and southern Asia, among which, more than 80% are in low birthweight babies. Existing neonatal mortality risk scores have primarily been developed for high-resource settings. The aim of this study was to develop and validate a score that is practicable for low-income and middle-income countries to predict in-hospital mortality among neonates born weighing 2000 g or less using datasets from the UK and The Gambia. METHODS: This analysis used retrospective data held in the UK National Neonatal Research Database from 187 neonatal units, and data from the Edward Francis Small Teaching Hospital (EFSTH), Banjul, The Gambia. In the UK dataset, neonates were excluded if birthweight was more than 2000 g; if the neonate was admitted aged more than 6 h or following discharge; if the neonate was stillborn; if the neonate died in delivery room; or if they were moribund on admission. The Gambian dataset included all neonates weighing less than 2000 g who were admitted between May 1, 2018, and Sept 30, 2019, who were screened for but not enrolled in the Early Kangaroo Mother Care Trial. 18 studies were reviewed to generate a list of 84 potential parameters. We derived a model to score in-hospital neonatal mortality risk using data from 55 029 admissions to a random sample of neonatal units in England and Wales from Jan 1, 2010, to Dec 31, 2016. All candidate variables were included in a complete multivariable model, which was progressively simplified using reverse stepwise selection. We validated the new score (NMR-2000) on 40 329 admissions to the remaining units between the same dates and 14 818 admissions to all units from Jan 1, to Dec 31, 2017. We also validated the score on 550 neonates admitted to the EFSTH in The Gambia. FINDINGS: 18 candidate variables were selected for inclusion in the modelling process. The final model included three parameters: birthweight, admission oxygen saturation, and highest level of respiratory support within 24 h of birth. NMR-2000 had very good discrimination and goodness-of-fit across the UK samples, with a c-index of 0·8859-0·8930 and a Brier score of 0·0232-0·0271. Among Gambian neonates, the model had a c-index of 0·8170 and a Brier score of 0·1688. Predictive ability of the simplified integer score was similar to the model using regression coefficients, with c-indices of 0·8903 in the UK full validation sample and 0·8082 in the Gambian validation sample. INTERPRETATION: NMR-2000 is a validated mortality risk score for hospitalised neonates weighing 2000 g or less in settings where pulse oximetry is available. The score is accurate and simplified for bedside use. NMR-2000 requires further validation using a larger dataset from low-income and middle-income countries but has the potential to improve individual and population-level neonatal care resource allocation. FUNDING: Bill & Melinda Gates Foundation; Eunice Kennedy Shriver National Institute of Child Health & Human Development; Wellcome Trust; and Joint Global Health Trials scheme of Department of Health and Social Care, Department for International Development, Medical Research Council, and Wellcome Trust.

Operationalising kangaroo Mother care before stabilisation amongst low birth Weight Neonates in Africa (OMWaNA): protocol for a randomised controlled trial to examine mortality impact in Uganda.

BACKGROUND: There are 2.5 million neonatal deaths each year; the majority occur within 48 h of birth, before stabilisation. Evidence from 11 trials shows that kangaroo mother care (KMC) significantly reduces mortality in stabilised neonates; however, data on its effect among neonates before stabilisation are lacking. The OMWaNA trial aims to determine the effect of initiating KMC before stabilisation on mortality within seven days relative to standard care. Secondary objectives include exploring pathways for the intervention's effects and assessing incremental costs and cost-effectiveness between arms. METHODS: We will conduct a four-centre, open-label, individually randomised, superiority trial in Uganda with two parallel groups: an intervention arm allocated to receive KMC and a control arm receiving standard care. We will enrol 2188 neonates (1094 per arm) for whom the indication for KMC is 'uncertain', defined as receiving ≥ 1 therapy (e.g. oxygen). Admitted singleton, twin and triplet neonates (triplet if demise before admission of ≥ 1 baby) weighing ≥ 700-≤ 2000 g and aged ≥ 1-< 48 h are eligible. Treatment allocation is random in a 1:1 ratio between groups, stratified by weight and recruitment site. The primary outcome is mortality within seven days. Secondary outcomes include mortality within 28 days, hypothermia prevalence at 24 h, time from randomisation to stabilisation or death, admission duration, time from randomisation to exclusive breastmilk feeding, readmission frequency, daily weight gain, infant-caregiver attachment and women's wellbeing at 28 days. Primary analyses will be by intention-to-treat. Quantitative and qualitative data will be integrated in a process evaluation. Cost data will be collected and used in economic modelling. DISCUSSION: The OMWaNA trial aims to assess the effectiveness of KMC in reducing mortality among neonates before stabilisation, a vulnerable population for whom its benefits are uncertain. The trial will improve understanding of pathways underlying the intervention's effects and will be among the first to rigorously compare the incremental cost and cost-effectiveness of KMC relative to standard care. The findings are expected to have broad applicability to hospitals in sub-Saharan Africa and southern Asia, where three-quarters of global newborn deaths occur, as well as important policy and programme implications. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02811432. Registered on 23 June 2016.

Training and evaluating simulation debriefers in low-resource settings: lessons learned from Bihar, India.

BACKGROUND: To develop effective and sustainable simulation training programs in low-resource settings, it is critical that facilitators are thoroughly trained in debriefing, a critical component of simulation learning. However, large knowledge gaps exist regarding the best way to train and evaluate debrief facilitators in low-resource settings. METHODS: Using a mixed methods approach, this study explored the feasibility of evaluating the debriefing skills of nurse mentors in Bihar, India. Videos of obstetric and neonatal post-simulation debriefs were assessed using two known tools: the Center for Advanced Pediatric and Perinatal Education (CAPE) tool and Debriefing Assessment for Simulation in Healthcare (DASH). Video data was used to evaluate interrater reliability and changes in debriefing performance over time. Additionally, twenty semi-structured interviews with nurse mentors explored perceived barriers and enablers of debriefing in Bihar. RESULTS: A total of 73 debriefing videos, averaging 18 min each, were analyzed by two raters. The CAPE tool demonstrated higher interrater reliability than the DASH; 13 of 16 CAPE indicators and two of six DASH indicators were judged reliable (ICC > 0.6 or kappa > 0.40). All indicators remained stable or improved over time. The number of 'instructors questions,' the amount of 'trainee responses,' and the ability to 'organize the debrief' improved significantly over time (p < 0.01, p < 0.01, p = 0.04). Barriers included fear of making mistakes, time constraints, and technical challenges. Enablers included creating a safe learning environment, using contextually appropriate debriefing strategies, and team building. Overall, nurse mentors believed that debriefing was a vital aspect of simulation-based training. CONCLUSION: Simulation debriefing and evaluation was feasible among nurse mentors in Bihar. Results demonstrated that the CAPE demonstrated higher interrater reliability than the DASH and that nurse mentors were able to maintain or improve their debriefing skills overtime. Further, debriefing was considered to be critical to the success of the simulation training. However, fear of making mistakes and logistical challenges must be addressed to maximize learning. Teamwork, adaptability, and building a safe learning environment enhanced the quality enhanced the quality of simulation-based training, which could ultimately help to improve maternal and neonatal health outcomes in Bihar.