Biomedical subjects
Publications and source records attributed to H E Solberg.
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There is a need for selecting good combinations of laboratory tests for various medical decision situations. Multivariate statistical methods are better tools for this type of selection than multiple univariate comparisons of candidate tests. Linear discriminant analysis is a suitable method. The best selection strategies are stepwise selection and evaluation of all possible subsets. Guiding criteria in the selection process may be measures of statistical separation between the clinical groups or empirical probabilities of correct reallocation. The latter criterion has the advantage that an optimum subset size may be identified.
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Differences in female workers' finger temperatures, manual dexterity, ratings on thermal comfort, and local cooling exposure were studied in three factories in the Faroe Island fishing industry. Environmental temperatures in the factories varied from 5 to 19 degrees C with vertical gradients of 7 degrees C/m, and the mean temperatures of the flushing water varied from 2 to 15 degrees C. Finger temperature varied from 12 to 24 degrees C when measured 2 min after work was stopped, and about one-third of the women experienced thermal discomfort in the fingers during work. The fish temperature increased, on the average, less than 1 degrees C during passage through the production room, notwithstanding the thermal differences among the factories. These findings should be used in attempts to reduce the cold exposure of the workers; but also improved control should be recommended for both environmental and water temperatures in the factories.
In 430 patients with a variety of thyroid disorders, linear discriminant analysis was used to select laboratory test combinations giving optimum diagnostic efficiency in thyroid function studies. Unexpectedly, TSH was found valuable in the diagnosis of hyperthyroidism and T3 in hypothyroidism. These test combinations were found optimal for the separation of euthyroidism/hyperthyroidism: T3, TSH and T4; euthyroidism/hypothyroidism: Combined free thyroid hormone index (FTI) and TSH; and hyperthyroidism/euthyroidism/hypothyroidism: T3, TSH, T4, FTI and T3U. The latter test combination had a total efficiency of 94%. Cholesterol, achilles reflex time, PBI and radioiodine uptake measurement contributed little to the discrimination.
Discriminant analysis (DA) is a pattern recognition technique that has been widely applied in medical studies. It allows multivariate observations ("patterns" or points in multidimensional space) to be allocated to previously defined groups (diagnostic categories). The relationships between DA and other multivariate statistical techniques of interest in medical studies will be briefly discussed. The main emphasis is on linear discriminant functions (LDF). The theoretic assumptions underlying DA using LDFs will be presented, and the effect of violations to these assumptions will be reviewed in detail. Alternative methods will be presented when violations cause serious problems. It has been shown that the familiar LDF is fairly robust to departures from the assumptions. The application of the LDF in less than ideal situations therefore often does not cause much harm (if the violations are not too grotesque). Another set of problems reviewed is how to estimate the misallocation probabilities when using discriminant functions. The selection of the "best" subset of variables out of the complete set will be discussed. Practical guide lines are given based on the theoretic studies reviewed. When possible, available computer programs for various problems of DA will be indicated. The review does not aim at covering all medical studies where DA has been applied, since emphasis is on the practical conclusions of the theory of DA.
Total serum bile acids were estimated by an enzymic (3alpha-hydroxysteroid dehydrogenase) method in 173 fasting patients with different liver diseases, classified into 17 groups by morphological criteria. The results were not highly correlated with those for any of the other 24 tests included in the study, but moderate correlations were observed with bilirubin or alanine aminotransferase (positive) and with prealbumin (negative) in a few patient groups. The sensitivity of total bile acids in serum of fasting individuals as a liver-function test was rather high, comparable with that of serum enzymes. When discriminant analysis was used to identify optimal combinations of tests for the separation of different groups of liver diseases, we found that data on serum bile acids added some new information to that carried by the other 24 tests.
A general-purpose statistical program package (BMDP) has been linked by a simple program interface to the data file of a clinical chemistry laboratory's computer system. This system may be used for various types of statistical data analysis based on the laboratory's routine work.
Patients with liver diseases were classified by cluster analysis using only clinical chemical laboratory results. A strong tendency towards correspondence between this classification, based on functional criteria, and the previous diagnoses, based mainly on liver biopsy findings, was found.
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Patients with different liver diseases were studied by discriminant analysis. Groups of patients classified mainly on the basis of liver biopsy findings showed functional differences which permitted a consistent reclassification by discriminant functions using laboratory results. Optimal combinations of laboratory tests for the separation of liver diseases were defined. Different combinations were found, dependent on the subsets of liver diseases studied.