5.1. Selection of reference interval study persons

This identification of people worth of inclusion in a certain reference interval experiment necessitates definition of detailed exclusion/inclusion criteria. The inclusion criteria state the factors crucial for use in the study, whereas the exclusion criteria specify the factors that make persons inappropriate for the experiment. Selection of the right individuals facilitates the acquisition of optimal specimens that exhibit acceptable degrees of confidence. Moreover, collecting the appropriate information regarding the exclusion and inclusion criteria, like donor health status, frequently necessitates a well-documented and confidential questionnaire as well as a consent form. An additional consideration regarding the selection of the individuals encompasses additional determinants that may necessitate partitioning persons into subgroups. Such subgroups may need separate reference interval experiments.

#### 5.2. Pre-analytic and analytic considerations

After selection of individuals for a specific reference interval examination, a key consideration entails the pre-analytic and analytic variables capable of influencing certain lab tests. Control and standardization of both variables are crucial for the generation of valid reference intervals. Additionally, some approaches are damn sensitive to interferences. For instance, mass spectrometry is resistant to interferences, while chemical approaches are sometimes highly sensitive to the same. Additional consideration entails the specific reagents used since altering to a modern agent amidst a reference examination can widen the underlying reference interval or rather transform the data distribution, maybe from bimodal to normal. Universally, a valid reference interval study necessitates extensive knowledge regarding the analyte, methodology, instrumentation, and analytic parameters.

Furthermore, plotting a reference approach versus a test approach and establishing a linear regression are key for determining whether to verify or establish a new reference interval. A correlation coefficient of one, the slope of one, and y-intercept of zero assert that the two approaches concur and hence a mere reference interval verification examination is necessary. Conversely, a considerable difference between the two approaches implies the necessity for establishing a modern reference interval. Nonetheless, analysis of reference values involves four key approaches—bias, confidence interval, parametric method, and nonparametric approach. The nonparametric approach is suitable for the majority of the reference range intervals involving analytes that are not normally distributed. A parametric approach is valid for the observed values that depict a Gaussian distribution. Confidence interval involves a range of values covering a specific probability and it serves to show the estimates' variability besides quantifying the variability. Bias implies the difference between the reference mean and the observed means wherein a negative bias implies that the reference value exceeds the test values, whereas a positive bias implies that the test values are higher [5]. Nonetheless, there is a current development regarding statistical software packages like MedCalc, JMP, SAS/STAT, Minitab, EP Evaluator, and GraphPad Prism [1]. This development has made a manual determination of reference intervals rare.
