Simple clinical score and laboratory-based method to predict bacterial etiology of acute diarrhea in childhood

Fontana, Massimo; Decorti, Giuliana; Paccagnini, S.; Ceriani, R.; Quaranta, Santina; Villa, M.; Principi, Nicola

doi:10.1097/00006454-198706120-00004

Cited by 23 publications

(9 citation statements)

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“…These include age, blood in stool, vomiting, breastfeeding status, and mid-upper arm circumference (MUAC), an indicator of nutritional status. We note that while variables such as fever and diarrhea duration were shown to be important in previous studies ( Fontana et al, 1987 ), adding these variables did not improve performance. Additionally, we excluded 'Season', since variables representing it are included in the climate predictive model (discussed below), as well as 'Height-for-age Z-score', another indicator of nutritional status, which would require a less feasible calculation than measurement of MUAC.…”

Section: Methodscontrasting

confidence: 49%

A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

Brintz

Haaland

Howard

et al. 2021

eLife

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Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where 'pre-test’ epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.

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Section: Methodscontrasting

confidence: 49%

A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

Brintz

Haaland

Howard

et al. 2021

eLife

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“…Use of such an index was necessary given the lack of a standardized measure of severity for childhood gastroenteritis and our dependence on retrospective data collection. This limitation is minimized, however, in that the components of this measure are based on current published data, and closely reflect the approach used in recent national guidelines for the assessment and treatment of this disorder [14][15][16][17][18][19][20]. Moreover, we did find that our measure had construct validity, i.e.…”

Section: Discussionmentioning

confidence: 86%

“…The overall dehydration score was dichotomized into minor (0-1 points) versus moderate to severe (2-3 points). Criteria to establish these scores were obtained from literature [14][15][16][17][18][19][20]. Our overall marker of severity is the number of these clinical characteristics-blood in the stool, fever > 38.…”

Section: Methodsmentioning

confidence: 99%

Social Disparities in the Use of Diagnostic Tests for Children with Gastroenteritis

Quintana¹,

Goldmann²,

Homer³

1997

Int J Qual Health Care

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“…Previous studies predicting etiology of diarrheal illness [14][15][16][17] , have been limited by the low number of participants, amount of clinical data collected, pathogen variety, number of pathogens detected, method of detection, lack of controls without diarrhea, single center design, and the need for stool testing. Etiological prediction is particularly challenging in LMIC settings, where multi-pathogen detection is common in children with diarrhea, and presumed pathogens can be isolated from asymptomatic individuals in up to 50% of study controls 18 .…”

Section: Discussionmentioning

confidence: 99%

“…The predictors we identified are consistent with those of previous studies. Bloody diarrhea as a predictor of a bacterial cause of diarrhea, especially for shigellosis, has been well established [14][15][16][17][21][22][23] and informs the IMCI guidelines that dysentery be treated with antibiotics. Vomiting as a predictor of a viral process has similarly been shown in previous studies 14,16 .…”

Section: Discussionmentioning

confidence: 99%

Clinical predictors for etiology of acute diarrhea in children in resource-limited settings

Brintz

Howard

Haaland

et al. 2020

Preprint

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Background. Diarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory method to more accurately assess diarrheal etiology, the knowledge of which could improve management of pediatric diarrhea. Methods. We used clinical and quantitative molecular etiologic data from the Global Enteric Multicenter Study (GEMS), a prospective, case-control study, to develop predictive models for the etiology of diarrhea. Using random forests, we screened the available variables and then assessed the performance of predictions from random forest regression models and logistic regression models using 5-fold cross-validation. Results. We identified 1049 cases where a virus was the only etiology, and developed predictive models against 2317 cases where the etiology was known but non-viral (bacterial, protozoal, or mixed). Variables predictive of a viral etiology included age, season, height-for-age z-score (HAZ), bloody diarrhea, and vomiting. Cross-validation suggests an AUC of 0.825 can be achieved with a parsimonious model of 5 variables, achieving a specificity of 0.85, a sensitivity of 0.59, a NPV of 0.82 and a PPV of 0.64. Conclusion. Predictors of the etiology of pediatric diarrhea can be used by providers in low-resources setting to inform clinical decision-making. The use of non-laboratory methods to diagnose viral causes of diarrhea could reduce inappropriate antibiotic prescription worldwide.

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Simple clinical score and laboratory-based method to predict bacterial etiology of acute diarrhea in childhood

Cited by 23 publications

References 0 publications

A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

Social Disparities in the Use of Diagnostic Tests for Children with Gastroenteritis

Clinical predictors for etiology of acute diarrhea in children in resource-limited settings

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