Reference Intervals

Highly sensitive immunoassays for the detection of neuro-specific biomarkers are becoming more accessible. Currently, the majority of these biomarkers are detected with the use of labour-intensive and highly skilled wet lab work. However, recent advancements have allowed for the introduction of these neuro-specific biomarkers into mainstream clinical chemistry analysers, bringing them closer to clinical care. There is a vast amount of published literature for neuro-specific biomarkers in an adult and ageing population, unfortunately, the same cannot be said for the neonatal population. From the limited available literature, clear differences are being documented in physiological levels of neuro-specific biomarkers in adults and infants. Neuro-specific biomarkers such as GFAP (Glial Fibrillary Acidic Protein) and Tau are demonstrating promise for the early detection and prediction of neuro-developmental disorders. There is a need for an understanding of physiological levels of these neuro-specific biomarkers in a neonatal population before they can be fully adopted into clinical routine. The development of a neonatal reference interval for neuro-specific biomarkers may provide a foundation for the accurate interpretation of neuro-specific biomarker elevations in neonatal brain injury, aiding in the development of biomarker-based screening tools for early diagnosis and intervention.

Reference intervals are an essential tool for the clinical interpretation of laboratory test results. Traditionally, these interval are determined using samples from healthy individuals, a process that is resource-intensive, time-consuming, and require the active recruitment of healthy volunteers. In recent years, due to the increasing availability of electronic health record (EHR) databases and the growing number of laboratory tests, it is possible to determine the reference intervals indirectly. This approach relies on the analysis of routine data acquired in clinical laboratories, eliminating the need for active recruiting healthy subjects and significantly reducing costs. Moreover, the method has the potential to eliminate the selection bias of an ultra-healthy population typical of the direct methods. The indirect methods for determining reference intervals have evolved from simple strategies of isolating the healthy population using sample metadata, to sophisticated statistical models that effectively distinguish normal from pathological distributions. One of the advanced techniques, RefineR, has reached an excellent combination of accuracy, robustness, and computational efficiency, outperforming previous methods. It has been implemented as an open-source R package, facilitating its application in real-world settings. In recognition of these advantages, the IFCC (International Federation of Clinical Chemistry and Laboratory Medicine), through its Committee on Reference Intervals and Decision Limits (C-RIDL), has promoted the adoption of indirect methods for determining reference intervals, highlighting the advantages of this strategy, including greater speed, lower costs, and the absence of a need to recruit healthy donors. Furthermore, a recent study has highlighted age-related physiological variations in hemoglobin levels in elderly population. This underscores the need for defining age-specific reference intervals which are currently absent from most laboratory reports, potentially impacting diagnostic accuracy.