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

被引:2
作者
Ahmed, Sharia M. [1 ]
Brintz, Ben J. [2 ]
Pavlinac, Patricia B. [3 ]
Shahrin, Lubaba [4 ]
Huq, Sayeeda [4 ]
Levine, Adam C. [5 ]
Nelson, Eric J. [6 ]
Platts-Mills, James A. [7 ]
Kotloff, Karen L. [8 ]
Leung, Daniel T. [1 ,9 ]
机构
[1] Univ Utah, Div Infect Dis, Sch Med, Salt Lake City, UT 84132 USA
[2] Univ Utah, Div Epidemiol, Sch Med, Salt Lake City, UT USA
[3] Univ Washington, Global Ctr Integrated Hlth Women Adolescents & Chi, Dept Global Hlth, Seattle, WA USA
[4] Int Ctr Diarrhoeal Dis Res, Dhaka, Bangladesh
[5] Brown Univ, Dept Emergency Med, Warren Alpert Med Sch, Providence, RI USA
[6] Univ Florida, Emerging Pathogens Inst, Dept Pediat & Environm & Global Hlth, Gainesville, FL USA
[7] Univ Virginia, Div Infect Dis & Int Hlth, Charlottesville, VA USA
[8] Univ Maryland, Ctr Vaccine Dev, Dept Pediat, Sch Med, Baltimore, MD USA
[9] Univ Utah, Div Microbiol & Immunol, Sch Med, Salt Lake City, UT 84132 USA
基金
美国国家卫生研究院;
关键词
diarrhea; growth faltering; stunting; clinical prediction; Human; GLOBAL ENTERIC MULTICENTER; DEVELOPING-COUNTRIES; CHRONIC MALNUTRITION; DIARRHEAL DISEASE; YOUNG-CHILDREN; INFANTS; INFECTION; HEALTH; IMPACT; UNDERNUTRITION;
D O I
10.7554/eLife.78491
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 & GE;0.5 or & GE;1.0 in height-for-age z-score [HAZ] at 60-day follow-up) in children & LE;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 (& GE;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).
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页数:18
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