Biomedical subjects

D J Munster

Publications and source records attributed to D J Munster.

5 recordsLinked to original sources

PubMed1978

Routine serum lipid analysis in New Zealand.

For two years pairs of serum specimens with a wide range of cholesterol and triglyceride concentrations were regularly dispatched each month to all New Zealand medical laboratories known to measure blood lipids. Four weeks after specimen dispatch each laboratory received a report which displayed all results along with the overall means, standard deviations, and results from "reference laboratories". Six-monthly summaries were prepared for each laboratory in which the previous 12 results were compared with the corresponding "target values" by regression analysis. This allowed classification of inaccuracy into one or more of three categories. Random error (imprecision) explained most of the discrepancies, but systematic errors also contributed strongly to the observed interlaboratory variation. No single class of laboratories performed significantly differently from any others. Approximately 60 percent of the 16000 cholesterol analyses done each month in New Zealand, and 40 percent of the 10000 triglyceride analyses, are performed with precision thought to be adequate for clinical usage.

Cholesterol↗

PubMed1978

Regression analysis in interlaboratory surveys: a case study with cholesterol and triglycerides.

1. A new interlaboratory survey design, that uses regression analysis to compare results from each laboratory with target values, was tested using cholesterol and triglyceride analyses. The fifty New Zealand laboratories involved showed considerable interlaboratory variation (CV = 8% to 27% for cholesterol, 13% to 113% for triglycerides), 30% and 40% of which was associated with systematic differences between laboratories. 2. End-of-period summaries using regression analysis confirmed the presence of systematic errors. These were either simple types caused apparently by incorrect standardisation (regression slope, B not equal to 1.0) or inappropriate blank correction (intercept, A not equal to zero) or complex types presumably due to nonlinearity or nonspecificity. Graphical display of results from each laboratory aided fault diagnosis and allowed the detection of between-run standardisation differences. 3. Method comparison studies were made: the only highly significant result being lower precision achieved by enzymatic cholesterol methods compared with other colorimetric methods.

Blood Chemical Analysis↗

PubMed1977

Simulation of laboratory errors and their effects on interlaboratory quality-control programs.

The random errors in an analytical method are additive and can be classified into analytical response-dependent and -independent terms. Non-random errors, caused by systematic faults in the analytical procedure, are not always distriguishable from the random errors, but some cases of non-linear assay response and unsuitable standardisation can be studied usefully in models without random error. Interlaboratory quality control programs cannot distinguish systematic and random error until the pattern of results on a number of specimens, or pairs of specimens, can be studied. In this case linear regression analysis is a powerful method for distinguishing different forms of error especially when response-dependent random errors do not predominate. The range of concentrations used for regression whould be as wide as that in which quantitative distinctions are used in clincal diagnosis and treatment. Preliminary reports, of the results on which the regression analysis is based, are most suitably presented on Youden diagrams with paired specimens.

Analysis of Variance↗

PubMed1977

A design for interlaboratory quality-control programs.

A design for interlaboratory quality-control programs is described. Speimens are despatched in pairs to participating laboratories. The results returned by laboratories are compared with each other and with reference results, but the frequent brief reports which are prepared are not regarded as the main laboratory assessments, although these reports can alert laboratories to gross imprecision and inaccuracy. When sufficient results have been returned, a linear regression analysis is carried out between results from each laboratory and the reference results. The statistics obtained from the regression data provide a concise source of information about the form of inaccuracy (imprecision and systematic error) present.

Chemistry, Clinical↗

PubMed1976

Contributions of other sterols to the estimation of cholesterol.

The responses of 5alpha-cholestan-3beta-ol, 5alpha-cholest-7-ene-3beta-ol and cholesta-5,7-dien-3beta-ol, normally found in human serum, were examined by: (1) the Liebermann-Burchard reaction, (2) the Zak (ferric chloride) reaction, (3) an enzymatic cholesterol method monitored by estimating the amount of hydrogen peroxide produced, (4) an enzymatic cholesterol method monitored by observing the change in absorbance at 240 nm, and (5) gas chromatography. The results show that none of these methods is specific for cholesterol; contributions from the sterols examined range from zero to more than 150% relative to cholesterol. For the first four methods contributions depend on the conditions under which each test is performed.

Cholestadienols↗