Algorithmic diagnosis of jaundice

Axel Malchow-Møller*, Carsten Thomsen

*Corresponding author af dette arbejde

    Publikation: Bidrag til tidsskriftArtikelForskningpeer review


    Extensive clinical and clinical chemical information was collected from 1002 jaundiced patients. By applying Bayes' theorem and logistic discriminant analysis, a diagnostic algorithm was developed based upon 21 of the 107 variables collected. This algorithm permitted a probabilistic classification of jaundiced patients into four diagnostic categories: acute non-obstructive, chronic non-obstructive, benign obstructive and malignant obstructive jaundice. Of the 985 patients with a final diagnosis a correct probabilistic diagnosis (obstruction vs. non-obstruction) was suggested by the algorithm in 867 patients (88% Adopting a probability limit of 0.80, 683 patients (69% were correctly classified, 34 patients (3.5% were wrongly so, and 268 patients (27% could not be classified with a probability above 0.80 (doubtful cases). The algorithm was also tested in a further series of 110 jaundiced patients and found to perform equally well: 88 patients classified, 22 patients remaining doubtful. Patients with doubtful diagnoses should be referred to a non-invasive test such as ultrasound examination, whereas patients with definite diagnoses can be referred to invasive tests (liverbiopsy, direct cholangiography) as appropriate. The diagnostic algorithm seems to be a valuable aid for the preliminary differential diagnosis of the jaundiced patient and can be used in the planning of a diagnostic strategy for the individual patient.

    Sider (fra-til)162-168
    Antal sider7
    TidsskriftScandinavian journal of gastroenterology
    Udgave nummerS128
    StatusUdgivet - 1 jan. 1987


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