Astrid Domesle

Universität Hamburg

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W. Rehpenning

Universität Hamburg

K. Harm

Florida College

K. D. Voigt

University of Veterinary Medicine Hannover, Foundation

Katrin Harm

Universität Hamburg

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Universität Hamburg

University Medical Center Hamburg-Eppendorf

Eppendorf (Germany)

Klinik und Poliklinik für Neurologie

Institute of Mathematics and Computer Science

Hautklinik Heidelberg

Gesellschaft Fur Mathematik Und Datenverarbeitung

Florida College

Allgemeines Krankenhaus Celle

University of Veterinary Medicine Hannover, Foundation

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Falsch positive Werte bei der Vielfachanalyse: Eine Erhebung an Referenz- und Patientenkollektiven

Clinical Chemistry and Laboratory Medicine (CCLM) (1979)

K. Harm W. Rehpenning Astrid Domesle K. D. Voigt

The number of falsely positive values occurring in 12-channel analysis was determined in two groups of patients and reference individuals. It revealed that the portion of falsely positive values actually found was statistically significant beyond that calculated on the assumption of a binomial distribution. Partly distinct correlations of the parameters combined to a profile as well as clear deviations from the normal distribution have to be taken into consideration as reasons for this discrepancy between theory and reality. The results show that the application of the binomial distribution leads to statements which significantly differ from the conditions actually present.

10.1515/cclm.1979.17.8.517

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Falsch positive Werte bei der Vielfachanalyse: Die Abschätzung ihrer Häufigkeit mit der Sylvesterschen Formel und ihre Reduktion durch eine multivariate Testgröße

Clinical Chemistry and Laboratory Medicine (CCLM) (1979)

W. Rehpenning K. Harm Astrid Domesle K. D. Voigt

The application of the binomial distribution for determining the number of "falsely positive values" is not suitable because of the partly strong correlations between the clinical chemical parameters. We have therefore tried to obtain more precise estimations for the number of falsely positive values by using a generalisation from Sylvester's formula and taking into account the correlations. We use multivariate statistics for testing a patient's value" when several laboratory parameters are simultaneously considered. The multivariate technique leads firstly to a significant reduction of the erroneously interpreted "falsely positive values" and secondly allows the detection of hidden implausible constellations of values.

Binomial (polynomial)

10.1515/cclm.1979.17.9.565

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Mathematische Analyse der Fehlerverteilungen bei Flow-Systemen und Konsequenzen für die Bestimmung neuer methodenspezifischer Kontrollgrenzen

Clinical Chemistry and Laboratory Medicine (CCLM) (1977)

Astrid Domesle Katrin Harm W. Rehpenning

In connection with the determination of method adapted control limits for the Technicon Autoanalyzer SMA 12/60 (Na+, K+, C1-, Total Protein, Albumin, P, Cholesterol, Urea Nitrogen, Calcium, Creatinine, Bilirubin, Uric Acid) we have investigated the representation of the control variable error distributions by mathematical formulae. The application of orthogonal functions (Gram-Charlier's series type A) proved to be not practicable because of the oscillations occuring at the ends of the distributions. Considerably improved results were obtained by a modified expression of a Gram-Charlier's series of type C, although the tails of the distributions (which are particularly important for the calculation of the fractiles) could not be optimally approximated. However, a very satisfactory approximation of the empirical density functions was obtained when we interpreted the control variables as non-additive superposition of two or three normally distributed quantities with different variances. This enables us to calculate channel specific alarm and control limits, thereby replacing the conventional quality control parameters previously checked and based on the assumption of normal distributions. Thus, an adequate monitoring of the reliability of flow-systems can be achieved.

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10.1515/cclm.1977.15.1-12.691

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