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Reference Intervals Generated by Electronic Medical Record Data Mining with Clinical Exclusions: Age-Specific Intervals for Thyroid-Stimulating Hormone from 33038 Euthyroid Patients
Author(s) -
Julia C. Drees,
Karl Huang,
Matthew S. Petrie,
Thomas Lorey,
Richard Dlott
Publication year - 2018
Publication title -
the journal of applied laboratory medicine
Language(s) - English
Resource type - Journals
eISSN - 2576-9456
pISSN - 2475-7241
DOI - 10.1373/jalm.2017.025445
Subject(s) - euthyroid , medicine , thyroid stimulating hormone , population , thyroid disease , thyroid , percentile , hormone , endocrinology , pediatrics , environmental health , statistics , mathematics
Background Serum thyroid-stimulating hormone (TSH) reference intervals are dependent on population characteristics, including prevalent thyroid disease and iodine status. Studies in the US have demonstrated increasing TSH levels with age, and the American Thyroid Association recommends higher TSH goals for older patients taking thyroid supplementation, but few laboratories offer age-specific reference intervals for TSH. Our objective was to establish TSH reference ranges in our racially diverse population in northern California. Methods Data mining of electronic medical records was used with the a posteriori approach to select a euthyroid reference population for TSH reference intervals. A report gathered all TSH results from 2 weeks from >1 year in the past, excluding results from patients with thyroid-related disease or medication use at any time before or after the TSH test. Results The reference population numbered 33038 and consisted of approximately 44% of the total TSH results reported in the selected time periods. The population identified as 46.5% white, 18.3% Asian, 17.0% Hispanic/Latino, 8.0% black/African American, and 10.3% other or unknown. These data demonstrate an increase in the median and 97.5 percentile of TSH levels with increasing age in adults. No clinically significant difference was seen between female and male individuals or between the self-identified races, except for lower TSH levels in the black/African American population. Conclusions The a posteriori approach using data mining for disease-specific criteria proved to be an efficient method for obtaining a large healthy reference population. Age-specific TSH reference ranges could prevent inappropriate diagnoses of subclinical hypothyroidism in older patients.

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