Accuracy of clinical diagnosis of cirrhosis among alcohol-abusing men.
There is a considerable variation among specialists in the use of liver biopsy for the diagnosis of alcoholic cirrhosis, which is often based solely on clinical findings, sometimes supplemented with blood tests. To assess the diagnostic accuracy that may be achieved by this approach, we related items of the history, symptoms and signs, and routine blood tests to the presence/absence of cirrhosis in a unique, previously established, consecutive series of 303 alcohol-abusing men, in whom liver biopsy was performed irrespective of the clinical and biochemical findings. Using logistic regression analyses, we created a clinical, a combined clinical and biochemical, and a pure biochemical diagnostic model. The probability of cirrhosis in patients with the specified characteristics was estimated, the diagnostic accuracy was assessed as functions of diagnostic thresholds for cirrhosis defined by the probability of cirrhosis varying between 0 and 1,and confidence intervals were estimated by bootstrap sampling. The clinical model, including facial teleangiectasia, vascular spiders, white nails, abdominal veins, fatness, and peripheral edema, could be used with high diagnostic accuracy and it was clearly superior to the biochemical model. Adding biochemical findings to the clinical model improved the accuracy of the clinical model only slightly. We conclude that cirrhosis may be diagnosed in alcohol-abusing men with a high accuracy using selected, properly weighted clinical observations only.
Department of Medicine 261, Hvidovre Hospital, University of Copenhagen, Denmark.
K J
KJ
Hamberg
B
B
Carstensen
T I
TI
Sørensen
K
K
Eghøje
D000328:Adult; D000368:Aged; D000437:Alcoholism / Q000150:complications*; D000465:Algorithms; D001706:Biopsy; D006801:Humans; D008104:Liver Cirrhosis, Alcoholic / Q000175:diagnosis* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011237:Predictive Value of Tests; D011336:Probability; D012044:Regression Analysis; D012680:Sensitivity and Specificity