Interventions to reduce post-acute consequences of diarrheal disease in children: a systematic review

Lactoferrin and lysozyme to promote nutritional, clinical and enteric recovery: a protocol for a factorial, blinded, placebo-controlled randomised trial among children with diarrhoea and malnutrition (the Boresha Afya trial)

INTRODUCTION

Children with moderate or severe wasting are at particularly high risk of recurrent or persistent diarrhoea, nutritional deterioration and death following a diarrhoeal episode. Lactoferrin and lysozyme are nutritional supplements that may reduce the risk of recurrent diarrhoeal episodes and accelerate nutritional recovery by treating or preventing underlying enteric infections and/or improving enteric function.

METHODS AND ANALYSIS

In this factorial, blinded, placebo-controlled randomised trial, we aim to determine the efficacy of lactoferrin and lysozyme supplementation in decreasing diarrhoea incidence and improving nutritional recovery in Kenyan children convalescing from comorbid diarrhoea and wasting. Six hundred children aged 6-24 months with mid-upper arm circumference <12.5 cm who are returning home after an outpatient visit or inpatient hospital stay for diarrhoea will be enrolled. Children will be randomised to 16 weeks of lactoferrin, lysozyme, a combination of the two, or placebo and followed for 24 weeks, with biweekly home visits by community health workers and clinic visits at 4, 10, 16 and 24 weeks. The primary analysis will compare the incidence of moderate-to-severe diarrhoea and time to nutritional recovery between each intervention arm and placebo. The trial will also test whether these interventions reduce enteric pathogen carriage, decrease enteric permeability and/or increase haemoglobin concentration in enrolled children. Finally, we will evaluate the acceptability, adherence and cost-effectiveness of lactoferrin and/or lysozyme.

ETHICS AND DISSEMINATION

The trial has been approved by the institutional review boards of the Kenya Medical Research Institute, the University of Washington, the Kenyan Pharmacy and Poisons Board, and the Kenyan National Commission on Science, Technology and Innovation. The results of this trial will be shared with local and international stakeholders and published in peer-reviewed journals, and the key findings will be presented at relevant conferences.

TRIAL REGISTRATION NUMBER

NCT05519254, PACTR202108480098476.

Predictive modeling for infectious diarrheal disease in pediatric populations: A systematic review

Introduction

Diarrhea is still a significant global public health problem. There are currently no systematic evaluation of the modeling areas and approaches to predict diarrheal illness outcomes. This paper reviews existing research efforts in predictive modeling of infectious diarrheal illness in pediatric populations.

Methods

We conducted a systematic review via a PubMed search for the period 1990-2021. A comprehensive search query was developed through an iterative process and literature on predictive modeling of diarrhea was retrieved. The following filters were applied to the search results: human subjects, English language, and children (birth to 18 years). We carried out a narrative synthesis of the included publications.

Results

Our literature search returned 2671 articles. After manual evaluation, 38 of these articles were included in this review. The most common research topic among the studies were disease forecasts 14 (36.8%), vaccine-related predictions 9 (23.7%), and disease/pathogen detection 5 (13.2%). Majority of these studies were published between 2011 and 2020, 28 (73.7%). The most common technique used in the modeling was machine learning 12 (31.6%) with various algorithms used for the prediction tasks. With change in the landscape of diarrheal etiology after rotavirus vaccine introduction, many open areas (disease forecasts, disease detection, and strain dynamics) remain for pathogen-specific predictive models among etiological agents that have emerged as important. Additionally, the outcomes of diarrheal illness remain under researched. We also observed lack of consistency in the reporting of results of prediction models despite the available guidelines highlighting the need for common data standards and adherence to guidelines on reporting of predictive models for biomedical research.

Conclusions

Our review identified knowledge gaps and opportunities in predictive modeling for diarrheal illness, and limitations in existing attempts whilst advancing some precursory thoughts on how to address them, aiming to invigorate future research efforts in this sphere.

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Diarrhea continues to be a leading cause of death for children under-five. Amongst children treated for acute diarrhea, mortality risk remains elevated during and after acute medical management. Identification of those at highest risk would enable better targeting of interventions, but available prognostic tools lack validation. We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build clinical prognostic models (CPMs) to predict death (in-treatment, after discharge, or either) in children aged ≤59 months presenting with moderate-to-severe diarrhea (MSD), in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using repeated cross-validation. We used data from the Kilifi Health and Demographic Surveillance System (KHDSS) and Kilifi County Hospital (KCH) in Kenya to externally validate our GEMS-derived CPM. Of 8060 MSD cases, 43 (0.5%) children died in treatment and 122 (1.5% of remaining) died after discharge. MUAC at presentation, respiratory rate, age, temperature, number of days with diarrhea at presentation, number of people living in household, number of children <60 months old living in household, and how much the child had been offered to drink since diarrhea started were predictive of death both in treatment and after discharge. Using a parsimonious 2-variable prediction model, we achieved an area under the ROC curve (AUC) of 0.84 (95% CI: 0.82, 0.86) in the derivation dataset, and an AUC = 0.74 (95% CI 0.71, 0.77) in the external dataset. Our findings suggest it is possible to identify children most likely to die after presenting to care for acute diarrhea. This could represent a novel and cost-effective way to target resources for the prevention of childhood mortality.

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Diarrhea continues to be a leading cause of death for children under-five. Amongst children treated for acute diarrhea, mortality risk remains elevated during and after acute medical management. Identification of those at highest risk would enable better targeting of interventions, but available prognostic tools lack validation. We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build predictive models for death (in-treatment, after discharge, or either) in children aged ≤59 months presenting with moderate-to-severe diarrhea (MSD), in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using repeated cross-validation. We used data from the Kilifi Health and Demographic Surveillance System (KHDSS) and Kilifi County Hospital (KCH) in Kenya to externally validate our GEMS-derived clinical prognostic model (CPM). Of 8060 MSD cases, 43 (0.5%) children died in treatment and 122 (1.5% of remaining) died after discharge. MUAC at presentation, respiratory rate, age, temperature, number of days with diarrhea at presentation, number of people living in household, number of children <60 months old living in household, and how much the child had been offered to drink since diarrhea started were predictive of death both in treatment and after discharge. Using a parsimonious 2-variable prediction model, we achieve an AUC=0.84 (95% CI: 0.82, 0.86) in the derivation dataset, and an AUC=0.74 (95% CI 0.71, 0.77) in the external dataset. Our findings suggest it is possible to identify children most likely to die after presenting to care for acute diarrhea. This could represent a novel and cost-effective way to target resources for the prevention of childhood mortality.

Derivation and external validation of clinical prediction rules identifying children at risk of linear growth faltering

Background

Nearly 150 million children under-5 years of age were stunted in 2020. We aimed to develop a clinical prediction rule (CPR) to identify children likely to experience additional stunting following acute diarrhea, to enable targeted approaches to prevent this irreversible outcome.

Methods

We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build predictive models of linear growth faltering (decrease of ≥0.5 or ≥1.0 in height-for-age z-score [HAZ] at 60-day follow-up) in children ≤59 months presenting with moderate-to-severe diarrhea, and community controls, in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using fivefold cross-validation. We used the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) study to (1) re-derive, and (2) externally validate our GEMS-derived CPR.

Results

Of 7639 children in GEMS, 1744 (22.8%) experienced severe growth faltering (≥0.5 decrease in HAZ). In MAL-ED, we analyzed 5683 diarrhea episodes from 1322 children, of which 961 (16.9%) episodes experienced severe growth faltering. Top predictors of growth faltering in GEMS were: age, HAZ at enrollment, respiratory rate, temperature, and number of people living in the household. The maximum area under the curve (AUC) was 0.75 (95% confidence interval [CI]: 0.75, 0.75) with 20 predictors, while 2 predictors yielded an AUC of 0.71 (95% CI: 0.71, 0.72). Results were similar in the MAL-ED re-derivation. A 2-variable CPR derived from children 0-23 months in GEMS had an AUC = 0.63 (95% CI: 0.62, 0.65), and AUC = 0.68 (95% CI: 0.63, 0.74) when externally validated in MAL-ED.

Conclusions

Our findings indicate that use of prediction rules could help identify children at risk of poor outcomes after an episode of diarrheal illness. They may also be generalizable to all children, regardless of diarrhea status.

Funding

This work was supported by the National Institutes of Health under Ruth L. Kirschstein National Research Service Award NIH T32AI055434 and by the National Institute of Allergy and Infectious Diseases (R01AI135114).

Zinc Deficiency Elevates Fecal Protein, But Not Electrolyte and Short-Chain Fatty Acid, Levels in Enterotoxigenic Escherichia coli-Induced Diarrhea in Rats

PURPOSE

To determine the effect of zinc deficiency on fecal protein, electrolyte, and short-chain fatty acid levels in both heat-stable (ST) and heat-labile (LT) enterotoxigenic Escherichia coli (ETEC)-induced diarrhea in rats.

METHODS

Albino rats, weighing 100 to 150 g, were divided into 2 groups, with 15 animals each: non-zinc and zinc-deficient. These two groups were sub-divided into three sub-groups with five rats each: control (saline); LT-ETEC; and ST-ETEC. Sodium phytate (30 mmol/L) was added to the animals' water to induce zinc deficiency, while diarrhea was induced using 5×109 ETEC cells/mL. Fecal protein levels were estimated using the Bradford method, while sodium and potassium levels were determined using atomic absorption spectrophotometry. Short-chain fatty acids were measured using gas chromatography-mass spectrometry.

RESULTS

Among the non-zinc and zinc-deficient groups, there were significant increases (p=0.04), (p=0.03) in fecal protein concentrations (mg/mL) in the LT-ETEC- (4.50±0.33), (6.50±0.26) and ST-ETEC- (3.85±0.19), (5.98±0.32) induced groups compared to the control groups (2.60±0.52), (3.50±0.11) respectively. Fecal sodium and potassium levels (mg/L) were significantly (p=0.029) increased in non-zinc-deficient rats induced with LT-ETEC (9.35±0.95, 1.05±0.48), and ST-ETEC (9.96±1.02, 1.21±0.45) compared with the control group (8.07±0.44, 0.47±0.17) but the increase were not statistically significant (p=0.059) in the zinc deficient rat groups. Fecal acetate and propionate levels (mg/g) significantly (p=0.032) increased when induced with LT-ETEC and ST-ETEC in non-zinc and zinc-deficient groups compared with the control groups.

CONCLUSION

Zinc deficiency among rats with ETEC-induced diarrhea elevated fecal protein loss but may not have an effect on fecal sodium, potassium and short-chain fatty acid levels.

Factors Associated With Child Stunting, Wasting, and Underweight in 35 Low- and Middle-Income Countries

IMPORTANCE

Evidence on the relative importance of various factors associated with child anthropometric failures (ie, stunting, underweight, and wasting) and their heterogeneity across countries can inform global and national health agendas.

OBJECTIVE

To assess the relative significance of factors associated with child anthropometric failures in 35 low- and middle-income countries (LMICs).

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study of 299 353 children who were born singleton and aged 12 to 59 months with nonpregnant mothers and valid anthropometric measures assessed the strengths of associations of 26 factors with child stunting, underweight, and wasting, using Demographic and Health Surveys (2007-2018) from 35 LMICs. Data analysis was conducted from July 2019 to February 2020.

EXPOSURES

A total of 9 direct factors (ie, dietary diversity score; breastfeeding initiation; vitamin A supplements; use of iodized salt; infectious disease in past 2 weeks; oral rehydration therapy for children with diarrhea; care seeking for suspected pneumonia; full vaccination; and indoor pollution) and 17 indirect factors (household wealth; maternal and paternal education; maternal and paternal height and body mass index; maternal autonomy for health care, movement, and money; water source; sanitation facility; stool disposal; antenatal care; skilled birth attendant at delivery; family planning needs; and maternal marriage age) were assessed.

MAIN OUTCOMES AND MEASURES

Three anthropometric failure outcomes were constructed based on the 2006 World Health Organization child growth standards: stunting (height-for-age z score less than -2 standard deviations [SDs]), underweight (weight-for-age z score less than -2 SDs), and wasting (weight-for-height z score less than -2 SDs).

RESULTS

Among the 299 353 children aged 12 to 59 months included in the analysis, 38.8% (95% CI, 38.6%-38.9%) had stunting, 27.5% (95% CI, 27.3%-27.6%) had underweight, and 12.9% (95% CI, 12.8%-13.0%) had wasting. In the pooled sample, short maternal height was the strongest factor associated with child stunting (odds ratio [OR], 4.7; 95% CI, 4.5-5.0; P < .001), followed by lack of maternal education (OR, 1.9; 95% CI, 1.8-2.0; P < .001), poorest household wealth (OR, 1.7; 95% CI,1.6-1.8; P < .001), and low maternal body mass index (OR, 1.6; 95% CI, 1.6-1.7; P < .001). Short paternal height was also significantly associated with higher odds of stunting (OR, 1.9; 95% CI, 1.7-2.2; P < .001). Consistent results were found for underweight (eg, short maternal height: OR, 3.5; 95% CI, 3.3-3.7; P < .001; lack of maternal education: OR, 1.8; 95% CI, 1.7-2.0; P < .001) and wasting (eg, low maternal body mass index: OR, 2.3; 95% CI, 2.1-2,4; P < .001; poorest household wealth: OR, 1.2; 95% CI, 1.1-1.3; P < .001). Parental nutritional status and household socioeconomic conditions ranked the strongest (1st to 4th) for most countries, with a few exceptions (eg, lack of maternal education ranked 18th-20th in 8 countries for child wasting). Other factors were not associated with anthropometric failures in pooled analysis and had large country-level heterogeneity; for example, unsafe water was not associated with child underweight in the pooled analysis (OR, 0.97; 95% CI, 0.95-1.00; P < .001), and it ranked from 4th to 20th across countries.

CONCLUSIONS AND RELEVANCE

In this study, socioeconomic conditions and parental nutritional status were the strongest factors associated with child anthropometric failures. Poverty reduction, women's education, and nutrition programs for households could be important strategies for reducing child undernutrition; however, country-specific contexts should be considered in national policy discussions.

Determinants of linear growth faltering among children with moderate-to-severe diarrhea in the Global Enteric Multicenter Study

BACKGROUND

Moderate-to-severe diarrhea (MSD) in the first 2 years of life can impair linear growth. We sought to determine risk factors for linear growth faltering and to build a clinical prediction tool to identify children most likely to experience growth faltering following an episode of MSD.

METHODS

Using data from the Global Enteric Multicenter Study of children 0-23 months old presenting with MSD in Africa and Asia, we performed log-binomial regression to determine clinical and sociodemographic factors associated with severe linear growth faltering (loss of ≥ 0.5 length-for-age z-score [LAZ]). Linear regression was used to estimate associations with ΔLAZ. A clinical prediction tool was developed using backward elimination of potential variables, and Akaike Information Criterion to select the best fit model.

RESULTS

Of the 5902 included children, mean age was 10 months and 43.2% were female. Over the 50-90-day follow-up period, 24.2% of children had severe linear growth faltering and the mean ΔLAZ over follow-up was - 0.17 (standard deviation [SD] 0.54). After adjustment for age, baseline LAZ, and site, several factors were associated with decline in LAZ: young age, acute malnutrition, hospitalization at presentation, non-dysenteric diarrhea, unimproved sanitation, lower wealth, fever, co-morbidity, or an IMCI danger sign. Compared to children 12-23 months old, those 0-6 months were more likely to experience severe linear growth faltering (adjusted prevalence ratio [aPR] 1.97 [95% CI 1.70, 2.28]), as were children 6-12 months of age (aPR 1.72 [95% CI 1.51, 1.95]). A prediction model that included age, wasting, stunting, presentation with fever, and presentation with an IMCI danger sign had an area under the ROC (AUC) of 0.67 (95% CI 0.64, 0.69). Risk scores ranged from 0 to 37, and a cut-off of 21 maximized sensitivity (60.7%) and specificity (63.5%).

CONCLUSION

Younger age, acute malnutrition, MSD severity, and sociodemographic factors were associated with short-term linear growth deterioration following MSD. Data routinely obtained at MSD may be useful to predict children at risk for growth deterioration who would benefit from interventions.