Histamine and the stomach: chemical histamine assays

Histamine assays in gastroduodenal tissues and body fluids are not an absolute objective of scientific interest but are related to the role of histamine in health and disease. Hence, the reliability of histamine assays has to be assessed in relation to this aim. Sensitivity and specificity of the chemical histamine assays are similar in tissues and body fluids. The modern developments in a fluorometric-fluoroenzymatic assay guarantee the highest sensitivity and specificity, especially by tests that monitor specificity in each single run of histamine determinations. Precision and accuracy of histamine measurement were especially investigated for the fluorometric assay. They included tests on the coefficient of variation over the whole concentration range, long-term precision with double-sample standard control charts, comparison of several methods for histamine assay including bioassay, and long-term accuracy with the use of Cusum charts. Finally, appropriate sample preparation, sample-taking, relevant body fluids and tissues, and the right time for sample-taking were evaluated in extended methodologic studies. Histamine assays are not just methods for a normal routine laboratory. Extended knowledge about histamine release and metabolism will be necessary to analyse data in this particular field with reasonable validity

Upper gastrointestinal tract bleeding: assessing the diagnostic contributions of the history and clinical findings

Various strategies can be used in the diagnosis of upper gastrointestinal tract bleeding. This study investigates the relevance of anamnestic and clinical findings for the diagnosis of the bleeding source. The authors introduced a computer-aided diagnostic system using Bayes' theorem and compared it with clinicians' predictions using anamnestic and clinical findings only. There was no difference in the overall accuracy rates, but a difference was observed in the diagnostic behaviors of the two "systems." In addition, the discriminatory ability of the computer-aided system, the sharpness of the predictions obtained, and the reliability of the posterior probabilities were analyzed. It is concluded that the clinician and the computer-aided system are not able to discriminate well between the disease categories. Derived classification matrices and probability-based measures show the reasons for the inadequacy of diagnostic information obtainable from the clinical history and physical findings