Dataset Information

Pathogens Associated With Linear Growth Faltering in Children With Diarrhea and Impact of Antibiotic Treatment: The Global Enteric Multicenter Study.

ABSTRACT:

Background

The association between childhood diarrheal disease and linear growth faltering in developing countries is well described. However, the impact attributed to specific pathogens has not been elucidated, nor has the impact of recommended antibiotic treatment.

Methods

The Global Enteric Multicenter Study enrolled children with moderate to severe diarrhea (MSD) seeking healthcare at 7 sites in sub-Saharan Africa and South Asia. At enrollment, we collected stool samples to identify enteropathogens. Length/height was measured at enrollment and follow-up, approximately 60 days later, to calculate change in height-for-age z scores (ΔHAZ). The association of pathogens with ΔHAZ was tested using linear mixed effects regression models.

Results

Among 8077 MSD cases analyzed, the proportion with stunting (HAZ below -1) increased from 59% at enrollment to 65% at follow-up (P < .0001). Pathogens significantly associated with linear growth decline included Cryptosporidium (P < .001), typical enteropathogenic Escherichia coli (P = .01), and untreated Shigella (P = .009) among infants (aged 0-11 months) and enterotoxigenic E. coli encoding heat-stable toxin (P < .001) and Cryptosporidium (P = .03) among toddlers (aged 12-23 months). Shigella-infected toddlers given antibiotics had improved linear growth (P = .02).

Conclusions

Linear growth faltering among children aged 0-23 months with MSD is associated with specific pathogens and can be mitigated with targeted treatment strategies, as demonstrated for Shigella.

SUBMITTER: Nasrin D

PROVIDER: S-EPMC8958895 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Pathogens Associated With Linear Growth Faltering in Children With Diarrhea and Impact of Antibiotic Treatment: The Global Enteric Multicenter Study.

Nasrin Dilruba D Blackwelder William C WC Sommerfelt Halvor H Wu Yukun Y Farag Tamer H TH Panchalingam Sandra S Biswas Kousick K Saha Debasish D Jahangir Hossain M M Sow Samba O SO Reiman Robert F B RFB Sur Dipika D Faruque Abu S G ASG Zaidi Anita K M AKM Sanogo Doh D Tamboura Boubou B Onwuchekwa Uma U Manna Byomkesh B Ramamurthy Thandavarayan T Kanungo Suman S Omore Richard R Ochieng John B JB Oundo Joseph O JO Das Sumon K SK Ahmed Shahnawaz S Qureshi Shahida S Quadri Farheen F Adegbola Richard A RA Antonio Martin M Mandomando Inacio I Nhampossa Tacilta T Bassat Quique Q Roose Anna A O'Reilly Ciara E CE Mintz Eric D ED Ramakrishnan Usha U Powell Helen H Liang Yuanyuan Y Nataro James P JP Levine Myron M MM Kotloff Karen L KL

The Journal of infectious diseases 20211201 12 Suppl 2

<h4>Background</h4>The association between childhood diarrheal disease and linear growth faltering in developing countries is well described. However, the impact attributed to specific pathogens has not been elucidated, nor has the impact of recommended antibiotic treatment.<h4>Methods</h4>The Global Enteric Multicenter Study enrolled children with moderate to severe diarrhea (MSD) seeking healthcare at 7 sites in sub-Saharan Africa and South Asia. At enrollment, we collected stool samples to id ...[more]

PMID: 34528677

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Project description: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.

Project description:BackgroundAlthough rotavirus is the leading cause of severe diarrhea among children in sub-Saharan Africa, better knowledge of circulating enteric pathogenic bacteria and their antimicrobial resistance is crucial for prevention and treatment strategies.Methodology/principal findingsAs a part of rotavirus gastroenteritis surveillance in Maradi, Niger, we performed stool culture on a sub-population of children under 5 with moderate-to-severe diarrhea between April 2010 and March 2012. Campylobacter, Shigella and Salmonella were sought with conventional culture and biochemical methods. Shigella and Salmonella were serotyped by slide agglutination. Enteropathogenic Escherichia coli (EPEC) were screened by slide agglutination with EPEC O-typing antisera and confirmed by detection of virulence genes. Antimicrobial susceptibility was determined by disk diffusion. We enrolled 4020 children, including 230 with bloody diarrhea. At least one pathogenic bacterium was found in 28.0% of children with watery diarrhea and 42.2% with bloody diarrhea. Mixed infections were found in 10.3% of children. EPEC, Salmonella and Campylobacter spp. were similarly frequent in children with watery diarrhea (11.1%, 9.2% and 11.4% respectively) and Shigella spp. were the most frequent among children with bloody diarrhea (22.1%). The most frequent Shigella serogroup was S. flexneri (69/122, 56.5%). The most frequent Salmonella serotypes were Typhimurimum (71/355, 20.0%), Enteritidis (56/355, 15.8%) and Corvallis (46/355, 13.0%). The majority of putative EPEC isolates was confirmed to be EPEC (90/111, 81.1%). More than half of all Enterobacteriaceae were resistant to amoxicillin and co-trimoxazole. Around 13% (46/360) Salmonella exhibited an extended-spectrum beta-lactamase phenotype.ConclusionsThis study provides updated information on enteric bacteria diversity and antibiotic resistance in the Sahel region, where such data are scarce. Whether they are or not the causative agent of diarrhea, bacterial infections and their antibiotic resistance profiles should be closely monitored in countries like Niger where childhood malnutrition pre-disposes to severe and invasive infections.

Project description:Diarrhea is a leading cause of antibiotic consumption among children in low- and middle-income countries. While vaccines may prevent diarrhea infections for which children often receive antibiotics, the contribution of individual enteropathogens to antibiotic use is minimally understood. We used data from the Global Enteric Multicenter Study (GEMS) to estimate pathogen-specific incidence of antibiotic-treated diarrhea among children under five years old residing in six countries of sub-Saharan Africa and South Asia before rotavirus vaccine implementation. GEMS was an age-stratified, individually-matched case-control study. Stool specimens were obtained from children presenting to sentinel health clinics with newly-onset, acute diarrhea (including moderate-to-severe and less-severe diarrhea) as well as matched community controls without diarrhea. We used data from conventional and quantitative molecular diagnostic assays applied to stool specimens to estimate the proportion of antibiotic-treated diarrhea cases attributable to each pathogen. Antibiotics were administered or prescribed to 9,606 of 12,109 moderate-to-severe cases and 1,844 of 3,174 less-severe cases. Across all sites, incidence rates of clinically-attended, antibiotic-treated diarrhea were 12.2 (95% confidence interval: 9.0-17.8), 10.2 (7.4-13.9) and 1.9 (1.3-3.0) episodes per 100 child-years at risk at ages 6 weeks to 11 months, 12-23 months, and 24-59 months, respectively. Based on the recommendation for antibiotic treatment to be reserved for cases with dysentery, we estimated a ratio of 12.6 (8.6-20.8) inappropriately-treated diarrhea cases for each appropriately-treated case. Rotavirus, adenovirus serotypes 40/41, Shigella, sapovirus, Shiga toxin-producing Escherichia coli, and Cryptosporidium were the leading antibiotic-treated diarrhea etiologies. Rotavirus caused 29.2% (24.5-35.2%) of antibiotic-treated cases, including the largest share in both the first and second years of life. Shigella caused 14.9% (11.4-18.9%) of antibiotic-treated cases, and was the leading etiology at ages 24-59 months. Our findings should inform the prioritization of vaccines with the greatest potential to reduce antibiotic exposure among children.

Project description:IntroductionStunting affects one-fifth of children globally with diarrhea accounting for an estimated 13.5% of stunting. Identifying risk factors for its precursor, linear growth faltering (LGF), is critical to designing interventions. Moreover, developing new predictive models for LGF using more recent data offers opportunity to enhance model accuracy, interpretability and capture new insights. We employed machine learning (ML) to derive and validate a predictive model for LGF among children enrolled with diarrhea in the Vaccine Impact on Diarrhea in Africa (VIDA) study and the Enterics for Global Heath (EFGH) - Shigella study in rural western Kenya.MethodsWe used 7 diverse ML algorithms to retrospectively build prognostic models for the prediction of LGF (≥ 0.5 decrease in height/length for age z-score [HAZ]) among children 6-35 months. We used de-identified data from the VIDA study (n = 1,106) combined with synthetic data (n = 8,894) in model development, which entailed split-sampling and K-fold cross-validation with over-sampling technique, and data from EFGH-Shigella study (n = 655) for temporal validation. Potential predictors (n = 65) included demographic, household-level characteristics, illness history, anthropometric and clinical data were identified using boruta feature selection with an explanatory model analysis used to enhance interpretability.ResultsThe prevalence of LGF in the development and temporal validation cohorts was 187 (16.9%) and 147 (22.4%), respectively. Feature selection identified the following 6 variables used in model development, ranked by importance: age (16.6%), temperature (6.0%), respiratory rate (4.1%), SAM (3.4%), rotavirus vaccination (3.3%), and skin turgor (2.1%). While all models showed good prediction capability, the gradient boosting model achieved the best performance (area under the curve % [95% Confidence Interval]: 83.5 [81.6-85.4] and 65.6 [60.8-70.4]) on the development and temporal validation datasets, respectively.ConclusionOur findings accentuate the enduring relevance of established predictors of LGF whilst demonstrating the practical utility of ML algorithms for rapid identification of at-risk children.

Project description:BackgroundNearly 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.MethodsWe 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.ResultsOf 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.ConclusionsOur 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.FundingThis 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).

Dataset Information

Pathogens Associated With Linear Growth Faltering in Children With Diarrhea and Impact of Antibiotic Treatment: The Global Enteric Multicenter Study.

Background

Methods

Results

Conclusions

Publications

Pathogens Associated With Linear Growth Faltering in Children With Diarrhea and Impact of Antibiotic Treatment: The Global Enteric Multicenter Study.

Similar Datasets

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