Determination of n-dimensional reference ellipsoids using patient data.

A method is described for the calculation of n-dimensional reference ellipsoids, using patient data. The advantages and drawbacks of the use of reference ellipsoids for a set of different parameters, in contrast with the use of a reference range for every single parameter, are discussed. The use of reference ellipsoids in practice is illustrated with an example.

The use of patient data for the calculation of reference values for some haematological parameters.

We have investigated the use of patient data for the calculation of reference values for the parameters which are determined by the Hemalog. For this purpose we used the Bhattacharya plot. All the parameters, with the exception of leukocytes, appear to meet the main underlying assumption of this plot, namely that the frequency distribution is Gaussian. In the case of leukocytes, however, the frequency distribution could be resolved into two overlapping Gaussian curves, thus making it possible to calculate reference values for this parameter also. The reference values as calculated from 14,500 unselected data (excluding children) are in general agreement with the literature. Significant differences were however detected between a group of patients and a group of blood donors. When a Bhattacharya plot has to be constructed with relatively few data, smoothing of the observed frequencies is very helpful in deciding which part of the plot is linear. Smoothing was carried out using the least squares method with a quadratic equation. Since the classes are equally spaced, this involves only a simple numerical transformation of the frequencies.

Calculation of radioimmunoassay standard curves.

A method for calculating radioimmunoassay standard curves, based on the theory of Ekins et al., is described. Because a four-parameter model is used, nonlinear standard curves are the result. The calibration curve is fitted to the measured standard points by means of a weighted least-squares method. The program based on this model can be easily processed on a desk-top calculator. For all 250 runs of six different assays, very good standard curves could be obtained. The mean deviation between the concentrations of the standard points and the corresponding calculated values was about 6%. In 26% of the cases it could be shown that the model we describe gave significantly better results than did two simpler ones.