title: Bayesian analysis using continuous likelihood ratios for identifying pleural exudates.
abstract: OBJECTIVE
  To ascertain if equations that calculate continuous likelihood ratios (CLRs) for pleural exudates improve pleural fluid categorization, especially when false positive or false negative test results are obtained by using Light's criteria.
  
  
  METHODS
  Retrospective review of the clinical and pleural fluid data from a consecutive series of patients with pleural effusion who underwent thoracentesis at the University Hospital Arnau de Vilanova (Lleida, Spain) over an 11-year period.
  
  
  METHODS
  A total of 1490 patients with pleural effusion (298 transudates and 1192 exudates) were recruited into the study. The presence of a transudate or exudate was established by clinical judgment. We examined the comparative diagnostic accuracy of 4 tests (i.e. pleural fluid protein and lactate dehydrogenase (LDH), and pleural fluid to serum protein and LDH ratios) for discriminating between transudates and exudates. Decision thresholds were determined by receiver operating characteristics (ROC) analysis. Equations for calculating CLRs derived from a logistic regression analysis based on a previously described method.
  
  
  RESULTS
  Individual pleural fluid tests did not differ in their diagnostic accuracies according to ROC analysis. We calculated CLRs for the elements of Light's criteria and pleural fluid protein, and also illustrated the sequential use of CLRs for determining posttest probabilities. Overall, CLR formulas had marginal performance for the correct categorization of pleural fluid.
  
  
  CONCLUSIONS
  CLRs provide a probabilistic statement as to the likelihood an effusion is a transudate or exudate. However, clinical judgment is little changed by the application of CLRs, and in doubtful cases a great amount of uncertainty remains. This Bayesian approach is likely to have no major impact on the clinical practice.
authors.affiliation: Pleural Diseases Unit, Department of Internal Medicine, Arnau de Vilanova University Hospital, Avda Alcalde Rovira Roure 80, 25198 Lleida, Spain. jporcelp@yahoo.es
authors.forename: J M
authors.initials: JM
authors.lastname: Porcel
authors.forename: J M
authors.initials: JM
authors.lastname: Peña
authors.forename: C
authors.initials: C
authors.lastname: Vicente de Vera
authors.forename: A
authors.initials: A
authors.lastname: Esquerda
authors.forename: M
authors.initials: M
authors.lastname: Vives
authors.forename: Richard W
authors.initials: RW
authors.lastname: Light
mesh_terms: D001499:Bayes Theorem; D001798:Blood Proteins / Q000032:analysis; D005122:Exudates and Transudates / Q000502:physiology*; D005260:Female; D006801:Humans; D007770:L-Lactate Dehydrogenase / Q000032:analysis; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D019152:Paracentesis; D010994:Pleura / Q000503:physiopathology*; D010996:Pleural Effusion / Q000503:physiopathology*; D011237:Predictive Value of Tests; D011506:Proteins / Q000032:analysis; D012372:ROC Curve; D012189:Retrospective Studies
chemical_list: D001798:Blood Proteins; D011506:Proteins; D007770:L-Lactate Dehydrogenase