Diagnosis of severe acute infections, like sepsis, requires timely identification of etiological agent to select correct treatment and improve patient outcomes. As culture-based diagnostic methods are too slow for such situations, faster molecular tools are increasingly being developed. However, the lack of reference methods and materials (collectively termed reference measurement system) hinders determination of accuracy of molecular approaches. This means tests may be performed with limited knowledge of their accuracy, potentially resulting in patient misdiagnosis leading to poorer patient prognosis.

This project investigated the performance of techniques as reference methods for the measurement of pathogen materials, with the aim to build on existing reference measurement systems via the development of a live cell reference material. The Escherichia coli model showed that molecular methods were capable of more precise quantification than conventional approaches. Use of materials was assessed in the evaluation of host DNA depletion, essential as part of metagenomic analysis of patient samples. The use of accurately quantified materials demonstrated that host depletion methods increased the relative bacterial DNA content, but that bacterial DNA loss precluded their use for sepsis where pathogen concentrations are low.

In an alternative model (COVID-19) a reference measurement system was used to determine clinical reference ranges of pathogen nucleic acids targeted by molecular diagnostic methods. This work also described when to use different units and discovered the novel concept of differential sensitivity where clinical diagnostic performance may differ with incidence.

This work demonstrated the application of different reference measurement systems for molecular testing of infectious disease. Accurate reference methods can be applied to value assign control materials that can be used to evaluate protocol performance or define reference ranges and guide test requirements. Such reference measurements can aid in evaluating accuracy when exploring improvements to pathogen identification in conditions like sepsis.