Distribution of under-5 deaths in the neonatal, postneonatal, and childhood periods: a multicountry analysis in 64 low- and middle-income countries

A digital health algorithm to guide antibiotic prescription in pediatric outpatient care: a cluster randomized controlled trial

Excessive antibiotic use and antimicrobial resistance are major global public health threats. We developed ePOCT+, a digital clinical decision support algorithm in combination with C-reactive protein test, hemoglobin test, pulse oximeter and mentorship, to guide health-care providers in managing acutely sick children under 15 years old. To evaluate the impact of ePOCT+ compared to usual care, we conducted a cluster randomized controlled trial in Tanzanian primary care facilities. Over 11 months, 23,593 consultations were included from 20 ePOCT+ health facilities and 20,713 from 20 usual care facilities. The use of ePOCT+ in intervention facilities resulted in a reduction in the coprimary outcome of antibiotic prescription compared to usual care (23.2% versus 70.1%, adjusted difference -46.4%, 95% confidence interval (CI) -57.6 to -35.2). The coprimary outcome of day 7 clinical failure was noninferior in ePOCT+ facilities compared to usual care facilities (adjusted relative risk 0.97, 95% CI 0.85 to 1.10). There was no difference in the secondary safety outcomes of death and nonreferred secondary hospitalizations by day 7. Using ePOCT+ could help address the urgent problem of antimicrobial resistance by safely reducing antibiotic prescribing. Clinicaltrials.gov Identifier: NCT05144763.

Effects of Food-Based Approaches on Vitamin A Status of Women and Children: A Systematic Review

Vitamin A deficiency (VAD) increases risk for morbidity and mortality. Food-based approaches offer one strategy to improve vitamin A status. This systematic review assessed evidence of the effects of food-based approaches on the vitamin A status of women and children under 5 y. VAD was defined as clinical ocular symptoms, such as loss of vision, and/or retinol plasma or serum concentration <0.70 μmol/L. Searches on food-based approaches to improve vitamin A status were conducted for the period 2011-2022 on PubMed, CINHAL, Web of Science, and Google Scholar using PRISMA guidelines. English-language publications were included. Case studies, unpublished dissertations, and non-peer-reviewed studies were excluded. This review comprises 24 of 27,322 identified studies; 23 included studies focused on provitamin A carotenoids. There were 17,214 participants across the 24 studies with sample sizes ranging from 8 to 3571 individuals. Intervention studies spanned from 3 wk to 2 y. Fifteen (63%) studies were randomized control trials, 7 were cross-sectional, and 2 were longitudinal studies. Most studies (N = 21) used biochemical measurements, for example, serum retinol, to assess vitamin A status; other studies used clinical symptoms (for example, xerophtalmia) or dietary intake. Thirteen (54%) studies reported a statistically significant effect of food-based interventions (N = 8) or an association of diet (N = 5) on vitamin A status. This systematic review indicated that some food-based interventions improved vitamin A status, thus offering a safe and effective delivery mechanism for vitamin A. There appeared to be significant association between vitamin A status and consumption of foods with high concentrations of preformed vitamin A and provitamin A carotenoids. Differences across studies in regard to the period of evaluation, food approaches used, and statistical power may explain the lack of effectiveness of food-based approaches on vitamin A status in some studies.

Infant Mortality Trends and Determinants in Kazakhstan

Infant mortality rate (IMR) is a crucial indicator of healthcare performance and a reflection of a country's socioeconomic development. We analyzed the trends of IMR in Central Asia (CA) countries and its determinants in Kazakhstan, which is a middle-income country. Linear regression was used for IMR trend analysis in CA countries from 2000 to 2020 and for exploring associations between IMR and socioeconomic factors, health service-related factors, and population health indicators-related factors. A gamma generalized linear model was applied to define associations with various determinants. Our analysis revealed that IMR has decreased in all CA countries, with Kazakhstan having the lowest rate in 2000 and 2020. Our results suggest that socioeconomic indicators, such as total unemployment, Gini index, current health expenditure, gross domestic product (GDP), proportion of people living in poverty, and births by 15-19-year-old mothers, were associated with increased infant mortality rates. Improving socioeconomic conditions, investing in healthcare systems, reducing poverty and income inequality, and improving access to education, are all potential issues for further development. Addressing these factors may be critical for improving maternal and child health outcomes in the region.

ePOCT+ and the medAL-suite: Development of an electronic clinical decision support algorithm and digital platform for pediatric outpatients in low- and middle-income countries

Electronic clinical decision support algorithms (CDSAs) have been developed to address high childhood mortality and inappropriate antibiotic prescription by helping clinicians adhere to guidelines. Previously identified challenges of CDSAs include their limited scope, usability, and outdated clinical content. To address these challenges we developed ePOCT+, a CDSA for the care of pediatric outpatients in low- and middle-income settings, and the medical algorithm suite (medAL-suite), a software for the creation and execution of CDSAs. Following the principles of digital development, we aim to describe the process and lessons learnt from the development of ePOCT+ and the medAL-suite. In particular, this work outlines the systematic integrative development process in the design and implementation of these tools required to meet the needs of clinicians to improve uptake and quality of care. We considered the feasibility, acceptability and reliability of clinical signs and symptoms, as well as the diagnostic and prognostic performance of predictors. To assure clinical validity, and appropriateness for the country of implementation the algorithm underwent numerous reviews by clinical experts and health authorities from the implementing countries. The digitalization process involved the creation of medAL-creator, a digital platform which allows clinicians without IT programming skills to easily create the algorithms, and medAL-reader the mobile health (mHealth) application used by clinicians during the consultation. Extensive feasibility tests were done with feedback from end-users of multiple countries to improve the clinical algorithm and medAL-reader software. We hope that the development framework used for developing ePOCT+ will help support the development of other CDSAs, and that the open-source medAL-suite will enable others to easily and independently implement them. Further clinical validation studies are underway in Tanzania, Rwanda, Kenya, Senegal, and India.

Challenges and solutions for transforming health ecosystems in low- and middle-income countries through artificial intelligence

BACKGROUND

Recent studies demonstrate the potential of Artificial Intelligence to support diagnosis, mortality assessment, and clinical decisions in low-and-middle-income countries (LMICs). However, explicit evidence of strategies to overcome the particular challenges for transformed health systems in these countries does not exist.

OBJECTIVE

The present study undertakes a review of research on the current status of artificial intelligence (AI) to identify requirements, gaps, challenges, and possible strategies to strengthen the large, complex, and heterogeneous health systems in LMICs.

DESIGN

After introducing the general challenges developing countries face, the methodology of systematic reviews and the meta-analyses extension for scoping reviews (PRISMA-ScR) is introduced according to the preferred reporting items. Scopus and Web of Science databases were used to identify papers published between 2011-2022, from which we selected 151 eligible publications. Moreover, a narrative review was conducted to analyze the evidence in the literature about explicit evidence of strategies to overcome particular AI challenges in LMICs.

RESULTS

The analysis of results was divided into two groups: primary studies, which include experimental studies or case studies using or deploying a specific AI solution (n = 129), and secondary studies, including opinion papers, systematic reviews, and papers with strategies or guidelines (n = 22). For both study groups, a descriptive statistical analysis was performed describing their technological contribution, data used, health context, and type of health interventions. For the secondary studies group, an in-deep narrative review was performed, identifying a set of 40 challenges gathered in eight different categories: data quality, context awareness; regulation and legal frameworks; education and change resistance; financial resources; methodology; infrastructure and connectivity; and scalability. A total of 89 recommendations (at least one per challenge) were identified.

CONCLUSION

Research on applying AI and ML to healthcare interventions in LMICs is growing; however, apart from very well-described ML methods and algorithms, there are several challenges to be addressed to scale and mainstream experimental and pilot studies. The main challenges include improving the quality of existing data sources, training and modeling AI solutions based on contextual data; and implementing privacy, security, informed consent, ethical, liability, confidentiality, trust, equity, and accountability policies. Also, robust eHealth environments with trained stakeholders, methodological standards for data creation, research reporting, product certification, sustained investment in data sharing, infrastructures, and connectivity are necessary.

SYSTEMATIC REVIEW REGISTRATION

[https://rb.gy/frn2rz].

Long Non-Coding RNAs ANRIL and HOTAIR Upregulation is Associated with Survival in Neonates with Sepsis in a Neonatal Intensive Care Unit

Background

Recently, long non-coding RNAs (lncRNAs) have emerged as potential molecular biomarkers for sepsis. We aimed to profile the expression signature of three inflammation-related lncRNAs, MALAT1, ANRIL, and HHOTAIR, in the plasma of neonates with sepsis and correlate these signatures with the phenotype.

Patients and Methods

This case–control study included 124 neonates with sepsis (88 survivors/36 non-survivors) admitted to the neonatal ICU and 17 healthy neonates. The relative expressions were quantified by real-time PCR and correlated to the clinic-laboratory data.

Results

The three circulating lncRNAs were upregulated in the cases; the median levels were MALAT1 (median = 1.71, IQR: −0.5 to 3.27), ANRIL (median = 1.09, IQR: 0.89 to 1.30), and HOTAIR (median = 1.83, IQR: 1.44 to 2.41). Co-expression analysis showed that the three studied lncRNAs were directly correlated (all p-values <0.001). Overall and stratification by sex analyses revealed significantly higher levels of the three lncRNAs in non-survivors compared to the survivor group (all p-values <0.001). Principal component analysis showed a clear demarcation between the two study cohorts in males and females. Cohorts with upregulated ANRIL (hazard ratio; HR = 4.21, 95% CI = 1.15–10.4, p=0.030) and HOTAIR (HR = 2.49, 95% CI = 1.02–6.05, p=0.044) were at a higher risk of mortality.

Conclusion

Circulatory MALAT1, ANRIL, and HOTAIR were upregulated in neonatal sepsis, and the latter two may have the potential as prognostic biomarkers for survival in neonatal sepsis.

Scarring and selection effects on children surviving elevated rates of postneonatal mortality in sub-Saharan Africa

Infants in sub-Saharan Africa face adversity: Infections and undernutrition are major causes of infant deaths and can cause physiological damage with long-lasting adverse scarring effects on the human development of the survivors, for example, in terms of health and education. However, selective mortality of more vulnerable children at very high levels of adversity in early life can leave the surviving population to appear on average healthier. This paper estimated the nonlinear effects of postneonatal mortality rate—a proxy for adversity, particularly infections and undernutrition—in a 50 km radius, occurring over the period of infancy, on the subsequent height-for-age and school attendance of the surviving children. The results indicated that an adverse environment in infancy negatively affected height-for-age at age 1–4 years: At relatively low levels of adversity (at the 10th percentile of postneonatal mortality rate), an additional postneonatal death per 100 person-years decreased height-for-age of the survivors by almost 2% of the mean deficit in height (relative to a common growth standard) when comparing siblings born into different levels of adversity. At high levels of adversity, no effect was found for height-for-age while a small positive association was observed for school attendance at age 7–16 years. The results indicated that selective mortality may have canceled out (or even dominated in the case of school attendance) observable scarring effects following high levels of postneonatal mortality rate in sub-Saharan Africa.

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Adversity in early life negatively affects human development in sub-Saharan Africa.

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The postneonatal mortality rate over infancy was used as a proxy for adversity.

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Elevated adversity in infancy negatively affected height-for-age at age 1–4 years.

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At high adversity, selective mortality may cancel out observable scarring effects.

Essential components of postnatal care - a systematic literature review and development of signal functions to guide monitoring and evaluation

BACKGROUND

Postnatal Care (PNC) is one of the healthcare-packages in the continuum of care for mothers and children that needs to be in place to reduce global maternal and perinatal mortality and morbidity. We sought to identify the essential components of PNC and develop signal functions to reflect these which can be used for the monitoring and evaluation of availability and quality of PNC.

METHODS

Systematic review of the literature using MESH headings for databases (Cinahl, Cochrane, Global Health, Medline, PubMed, and Web of Science). Papers and reports on content of PNC published from 2000-2020 were included. Narrative synthesis of data and development of signal function through 7 consensus-building workshops with 184 stakeholders.

RESULTS

Forty-Eight papers and reports are included in the systematic review from which 22 essential components of PNC were extracted and used to develop 14 signal functions. Signal functions are used in obstetrics to denote a list of interventions that address major causes of maternal and perinatal morbidity or mortality. For each signal function we identified the equipment, medication and consumables required for implementation. The prevention and management of infectious diseases (malaria, HIV, tuberculosis) are considered essential components of routine PNC depending on population disease burden or whether the population is considered at risk. Screening and management of pre-eclampsia, maternal anaemia and mental health are recommended universally. Promotion of and support of exclusive breastfeeding and uptake of a modern contraceptive method are also considered essential components of PNC. For the new-born baby, cord care, monitoring of growth and development, screening for congenital disease and commencing vaccinations are considered essential signal functions. Screening for gender-based violence (GBV) including intimate partner- violence (IPV) is recommended when counselling can be provided and/or a referral pathway is in place. Debriefing following birth (complicated or un-complicated) was agreed through consensus-building as an important component of PNC.

CONCLUSIONS

Signal functions were developed which can be used for monitoring and evaluation of content and quality of PNC. Country adaptation and validation is recommended and further work is needed to examine if the proposed signal functions can serve as a useful monitoring and evaluation tool.

TRIAL REGISTRATION

The systematic review protocol was registered: PROSPERO 2018 CRD42018107054 .

Geographic and socioeconomic inequalities in the survival of children under-five in Nigeria

Despite a substantial decline in child mortality globally, the high rate of under-five mortality in Nigeria is still one of the main public health concerns. This study investigates inequalities in geographic and socioeconomic factors influencing survival time of children under-five in Nigeria. This is a retrospective cross-sectional quantitative study design that used the latest Nigeria Demographic Health Survey (2018). Kaplan–Meier survival estimates, Log-rank test statistics, and the Cox proportional hazards were used to assess the geographic and socioeconomic differences in the survival of children under-five in Nigeria. The Kaplan–Meier survival estimates show most under-five mortality occur within 12 months after birth with the poorest families most at risk of under-five mortality while the richest families are the least affected across the geographic zones and household wealth index quintiles. The Cox proportional hazard regression model results indicate that children born to fathers with no formal education (HR: 1.360; 95% CI 1.133–1.631), primary education (HR: 1.279; 95% CI 1.056–1.550) and secondary education (HR: 1.204; 95% CI 1.020–1.421) had higher risk of under-five mortality compared to children born to fathers with tertiary education. Moreover, under-five mortality was higher in children born to mothers’ age ≤ 19 at first birth (HR: 1.144; 95% CI 1.041–1.258). Of the six geopolitical zones, children born to mothers living in the North-West region of Nigeria had 63.4% (HR 1.634; 95% CI 1.238–2.156) higher risk of under-five mortality than children born to mothers in the South West region of Nigeria. There is a need to focus intervention on the critical survival time of 12 months after birth for the under-five mortality reduction. Increased formal education and target interventions in geopolitical zones especially the North West, North East and North Central are vital towards achieving reduction of under-five mortality in Nigeria.

Age Distribution of All-Cause Mortality Among Children Younger Than 5 Years in Low- and Middle-Income Countries

Importance

Coverage of essential child health and nutrition interventions in low- and middle-income countries remains suboptimal. Adverse exposures, such as undernutrition and infections, are particularly harmful during the 1000 days from conception until 2 years of age.

Objective

To investigate whether deaths in children younger than 5 years-which also reflect adverse exposures faced by children more broadly-are concentrated in the first 2 years after birth.

Design, Setting, and Participants

This cross-sectional study used a synthetic cohort probability method with Demographic and Health Surveys and Multiple Indicator Cluster Surveys from 77 low- and middle-income countries, with the earliest survey starting data collection in March 2010 and the most recent survey ending data collection in December 2019. Participants included 2 827 515 children who were younger than 5 years at any point 10 years before survey. Data were analyzed from March 11 to 21, 2022.

Main Outcomes and Measures

Share of deaths among children younger than 5 years occurring before 1 month, at 1 to 23 months, and at 24 to 59 months of age.

Results

Among the 2 827 515 children included in the analysis, 81.5% (95% CI, 81.0%-82.0%) of deaths occurred in the first 2 years after birth ranging from 63.7% (95% CI, 61.6%-65.7%) in Niger to 97.8% (95% CI, 85.9%-99.7%) in Albania. An estimated 18.5% (95% CI, 18.0%-19.0%) of child deaths occurred at 24 to 59 months of age. Countries with higher mortality rates among children younger than 5 years had a lower share of deaths occurring in the neonatal period.

Conclusions and Relevance

In this sample of 77 low- and middle-income countries, a large majority of deaths among children younger than 5 years occurred before 2 years of age in all countries among boys and girls and in households with the worst and best living standards. Research has highlighted perinatal complications, infections, and undernutrition as primary causes of death among children younger than 5 years. Therefore, coverage of interventions to reduce these adverse exposures should be ensured during pregnancy and the first 2 years after birth, which is also a crucial period for human development.