B-151 Estimation of the Uric Acid Reference Interval by the Indirect Method Using an Unsupervised Machine Learning Tool and R Programming Language

Abstract

Abstract Background Determining the Reference Intervals (RI) of quantitative clinical laboratory tests is crucial for patient diagnosis, treatment, and monitoring. It is also a concern for laboratories seeking to meet accreditation requirements. Our study aimed to evaluate the manufacturer’s RI for uric acid (3.7–9.2 mg/dL) through indirect methods using a programming tool in R language in a Brazilian laboratory. Methods We performed a data mining study for uric acid using the laboratory’s LIS database from January to December 2021. Outpatients >18 years old, analyzed on the Siemens® platform with results within linearity were included. Exclusion criteria were total cholesterol >200 mg/dL, triglycerides >150 mg/dL, glycemia >126 mg/dL, ferritin >300 ng/mL and creatinine >1.5 mg/dL at any time in the patient history and CRP >10 mg/dL in the same month. We used a tool that integrates different algorithms including preliminary treating, grouping, and statistical reduction of test results. The Expectation-Maximization (EM) algorithm calculates the mean, standard deviation, and weight of the distribution for each cluster. Additionally, it integrates algorithms that determine the global mean/median, modes, antimodes, kurtosis, and skewness, to find values that best represent the reference population’s distribution (Figure). Manufacturer's and estimated RI for Male and Female partitions. Results The final database included 49.489 subjects, partitioned in 26.439 women and 23.050 men. Statistically estimated RI were 2.8–6.7 mg/dL for women and 3.8–8.6 mg/dL for men. Considering the RI proposed by the manufacturer, 23.8% of women were outside the RI provided by the manufacturer, all of them below the lower reference value. Conclusions Our results confirm the importance of verification/establishment of reference intervals by clinical laboratories and suggest that estimated RI using this software is appropriate for the assisted population, demonstrating consistency with physicians’ concerns. After specialist analysis, the manufacturer´s RI has been replaced by the calculated population-specific RI.