Risk score to stratify children with suspected serious bacterial infection: observational cohort study

Andrew J Brent, Monica Lakhanpaul, Matthew Thompson, Jacqueline Collier, Samiran Ray, Nelly Ninis, Michael Levin, Roddy MacFaul, Andrew J Brent, Monica Lakhanpaul, Matthew Thompson, Jacqueline Collier, Samiran Ray, Nelly Ninis, Michael Levin, Roddy MacFaul

Abstract

Objectives: To derive and validate a clinical score to risk stratify children presenting with acute infection.

Study design and participants: Observational cohort study of children presenting with suspected infection to an emergency department in England. Detailed data were collected prospectively on presenting clinical features, laboratory investigations and outcome. Clinical predictors of serious bacterial infection (SBI) were explored in multivariate logistic regression models using part of the dataset, each model was then validated in an independent part of the dataset, and the best model was chosen for derivation of a clinical risk score for SBI. The ability of this score to risk stratify children with SBI was then assessed in the entire dataset.

Main outcome measure: Final diagnosis of SBI according to criteria defined by the Royal College of Paediatrics and Child Health working group on Recognising Acute Illness in Children.

Results: Data from 1951 children were analysed. 74 (3.8%) had SBI. The sensitivity of individual clinical signs was poor, although some were highly specific for SBI. A score was derived with reasonable ability to discriminate SBI (area under the receiver operator characteristics curve 0.77, 95% CI 0.71 to 0.83) and risk stratify children with suspected SBI.

Conclusions: This study demonstrates the potential utility of a clinical score in risk stratifying children with suspected SBI. Further work should aim to validate the score and its impact on clinical decision making in different settings, and ideally incorporate it into a broader management algorithm including additional investigations to further stratify a child's risk.

Conflict of interest statement

Competing interests None.

Figures

Figure 1
Figure 1
Receiver operator characteristics (ROC) curve of serious bacterial infection score as a predictor of serious bacterial infection in the entire dataset.

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