Harnessing the Power of Big Data Analytics-Estimation of Reference Intervals for Neonatal Serum TSH in Pakistan Using RefineR Algorithm.

Abstract

To estimate the population-specific reference intervals (RIs) for neonatal thyroid stimulating hormone (TSH) in Pakistani neonates, utilising the refineR algorithm. Observational study. Place and Duration of the Study: Department of Pathology and Laboratory Medicine, The Aga Khan University Hospital, Karachi, Pakistan, from 17th May to 30th November 2023. A data mining analysis was conducted on serum TSH results of neonates (≤1 month) over a period of six years, following approval from the Institutional Ethical Review Committee. Two subgroups were assessed based on the age as 0 - 5 days and 6 - 30 days. The refineR algorithm was implemented using refineR package (version 1.0.0), ensuring accurate analysis and insights. A total of non-duplicate 82,299 neonatal serum TSH tests were retrieved, including 70,788 (88%) aged 0 - 5 days and 11,511 (12%) aged ranging from 6 - 30 days. The estimated RI was from 0.67 µIU/mL (90% CI 0.641 - 0.72) to 15.0 µIU/mL (90% CI 13.2 - 17.3) for the first age group and 0.65 µIU/mL (90% CI 0.6 - 0.84) to 8.6 µIU/mL (90% CI 8.05 - 9.71) for the second age group. Reference intervals for neonatal serum TSH of the Pakistani population were estimated, considering the genetic differences of this demographic in comparison to the Western population. Results aligned with global literature, validating the refineR indirect approach's applicability. Reference intervals, Neonatal, Thyroid stimulating hormone, RefineR algorithm, Big data, Pakistan.