Speaker:
Cody W Lewis. Assistant Professor Clinical Biochemist. University of Saskatchewan / Saskatchewan Health Authority.
Cody Lewis is currently a Clinical Biochemist working for the Saskatchewan Health Authority with an academic appointment at the University of Saskatchewan. He oversees the general chemistry laboratory at St Paul’s Hospital and co-leads point of care testing in Saskatoon. Additionally, Cody has interests in testing associated with endocrine disorders. Prior to joining the team in Saskatoon, Cody completed his fellowship training 2021 in Calgary Alberta. Before that, he obtained a PhD in Cancer Sciences from the University of Alberta and an MSc from the University of Lethbridge.
Overview:
Physicians use reference intervals (RIs) to interpret laboratory results. Lab oratorie s and analytical platforms often have different RIs. Alberta laboratories are striving to standardize RIs across the province, which includes thyroid hormones. To estimate RIs and to develop a reflex TSH testing algorithm, indirect sampling of “big data” was utilized. Data was analyzed by three statistical models: Bhattacharya, refineR, and non-parametric. TSH upper limits were highly variable depending on the model, ranging from 4.70 to 6.50 mIU /L. To refine estimated limits, a panel of adult and pediatric endocrinologists was engaged. The final decision took into account the percentage of normal matched free-T4 results. The standardization of thyroid RIs and the development of a new testing algorithm were achieved by this approach.
Objectives:
At the conclusion of this session, participants will be able to:
- Discuss the impact of implementing a sub-optimal reference intervals (RIs)
- Define big data and appreciate how it can be used to estimate RIs
- Recognize the limitation of deriving RIs via indirect sampling methods and discuss options for refining estimated limits