Strengths and limitations
This validation was performed in a very large, prospective cohort in a clinically relevant, broad ambulatory setting. It is the first validation study of these models to include GP and paediatric outpatient practices, representing a low-prevalence setting for SBI. However, the vast majority of SI were diagnosed in the ED, making separate analyses for those settings unreliable.The CPMs were developed in different countries with distinct healthcare systems, vaccination policy and vaccination uptake. Further heterogeneity is introduced by the different variables and the differences between the derivation and validation cohorts. For the Feverkidstool, the most accurate external validation could be performed, since all variables were present in the validation dataset and the derivation and validation cohort had similar age and sex distributions. The proportion of SBI was clearly higher (12% vs. 3%), reflecting the difference in setting. The Craig model had the lowest proportion of variables available, yet still showed good diagnostic performance. It was derived in younger children from 0 to 5 years, while we applied it to children from 1 month to 16 years. For the SBI score, four good-quality proxies were used on a total of eight variables. Children in the derivation cohort were on average slightly younger (median 1.58 years vs. 1.96 years), and had a similar proportion of SBI (3.8% vs. 3.4%). For PAWS two moderate-quality proxies were available on seven variables, mildly reducing the accuracy of our external validation.Inevitably, as in any large study in daily clinical practice, not all data were registered completely. We performed single imputation of the missing values and considered them non-deviant, from the assumption that normal parameters are less frequently registered in a child in good clinical condition with a low probability of SI, especially by GPs. Further research focussing on developing more appropriate methodology to perform multiple imputation for multinomial models could facilitate future analyses for similar research questions [