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

Author:

Ahmed Sharia M1ORCID,Brintz Ben J2ORCID,Pavlinac Patricia B3,Shahrin Lubaba4,Huq Sayeeda4,Levine Adam C5,Nelson Eric J6,Platts-Mills James A7,Kotloff Karen L8,Leung Daniel T19ORCID

Affiliation:

1. Division of Infectious Diseases, University of Utah School of Medicine

2. Division of Epidemiology, University of Utah School of Medicine

3. Department of Global Health, Global Center for Integrated Health of Women, Adolescents and Children (Global WACh), University of Washington

4. International Centre for Diarrhoeal Disease Research

5. Department of Emergency Medicine, Warren Alpert Medical School of Brown University

6. Department of Pediatrics and Environmental and Global Health, Emerging Pathogens Institute, University of Florida

7. Division of Infectious Diseases and International Health, University of Virginia

8. Department of Pediatrics, Center for Vaccine Development, University of Maryland School of Medicine

9. Division of Microbiology & Immunology, University of Utah School of Medicine

Abstract

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).

Funder

National Institute of Allergy and Infectious Diseases

National Institutes of Health

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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