title: Case-control diagnosis and Bayesian inference in common viral infections.
abstract: The predictive values of symptoms and signs for given diseases are often unknown. The fact that a high proportion of individuals with a certain disease may have a specific group of symptoms (the case-control approach) does not necessarily mean that the specific group of symptoms will allow one reliably to diagnose the disease. This study, utilizing a population based data set for common acute infections, shows that descriptions of common viral illnesses found in medical textbooks that associate illnesses with symptoms do not allow one to predict reliably isolation of the supposed causal organism. Positive predictive value of groups of symptoms for specific viral infections did not exceed 11 percent in this study. However, the data closely fitted the Bayesian statistical model often proposed for such decision making by physicians.
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D003625:Data Collection; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008137:Longitudinal Studies; D008297:Male; D008722:Methods; D008875:Middle Aged; D014777:Virus Diseases / Q000175:diagnosis*; D014861:Washington