Background: Antibiotics are commonly prescribed for children with lower respiratory tract infections (LRTIs), fuelling antibiotic resistance, and there are few prognostic tools available to inform management.
Aim: To externally validate an existing prognostic model (STARWAVe) to identify children at low risk of illness progression, and if model performance was limited to develop a new internally validated prognostic model.
Design and setting: Prospective cohort study with a nested trial in a primary care setting.
Method: Children aged 6 months to 12 years presenting with uncomplicated LRTI were included in the cohort. Children were randomised to receive amoxicillin 50 mg/kg per day for 7 days or placebo, or if not randomised they participated in a parallel observational study to maximise generalisability. Baseline clinical data were used to predict adverse outcome (illness progression requiring hospital assessment).
Results: A total of 758 children participated (n = 432 trial, n = 326 observational). For predicting illness progression the STARWAVe prognostic model had moderate performance (area under the receiver operating characteristic [AUROC] 0.66, 95% confidence interval [CI] = 0.50 to 0.77), but a new, internally validated model (seven items: baseline severity; respiratory rate; duration of prior illness; oxygen saturation; sputum or a rattly chest; passing urine less often; and diarrhoea) had good discrimination (bootstrapped AUROC 0.83, 95% CI = 0.74 to 0.92) and calibration. A three-item model (respiratory rate; oxygen saturation; and sputum or a rattly chest) also performed well (AUROC 0.81, 95% CI = 0.70 to 0.91), as did a score (ranging from 19 to 102) derived from coefficients of the model (AUROC 0.78, 95% CI = 0.67 to 0.88): a score of <70 classified 89% (n = 600/674) of children having a low risk (<5%) of progression of illness.
Conclusion: A simple three-item prognostic score could be useful as a tool to identify children with LRTI who are at low risk of an adverse outcome and to guide clinical management.
Keywords: antibiotic resistance; antibiotics; children; primary health care; respiratory tract infections.
© The Authors.