An improved indirect approach for determining reference limits from intra-laboratory data bases exemplified by concentrations of electrolytes

Abstract

Background: The current dogma of establishing intra-laboratory reference limits (RLs) and their periodical reviewing cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt RLs from external sources often neglecting the problems of transferability. Presently accepted validation concepts still require experimental expenses. Several attempts were undertaken to derive RLs from the large data pools stored in modern laboratory information systems. Former indirect procedures were not generally accepted, but were recently further developed and combined with direct exclusion criteria and applied to estimate RLs of the catalytic activity concentrations of enzymes. This approach was now applied to several electrolytes in serum and plasma most commonly applied in clinical chemistry. Methods: A smoothed kernel density function was estimated for the distribution of the mixed data of the sample group (combined data of non-diseased and diseased subjects). It was assumed that the "central" part of the distribution of all data represents the non-diseased ("healthy") population (non-pathological values) with high probability. The central part was defined by truncation points using an optimisation method, and was used to estimate a Gaussian distribution of the values of nondiseased subjects. This distribution was now considered as the distribution of the non-diseased subgroup. The percentiles of this parametrical distribution were calculated to obtain unimodal reference intervals. Results: The RLs obtained from different laboratories were similar to recently published values established by direct procedures. Stratification for gender was not necessary, but in some cases for age. With rising age, an increase of the upper RL and of the reference range was observed for potassium. Hospitalisation affected the RLs of sodium, potassium, calcium and magnesium, but not of phosphate. In the case of sodium, the data of at least five regional laboratories could be combined to common RLs. The presented indirect procedure was further validated with a large dataset of potassium concentrations from the NHANES III study with five groups of different health status. Conclusions: The proposed strategy of combining exclusion criteria with an indirect method led to RLs from intra-laboratory data pools for electrolytes which were plausible in comparison to published data obtained by the generally accepted direct approach. The combined concept, however, still requires further investigations. Therefore, it is presently only recommended for checking and reviewing already existing RLs.