Background: Light's criteria misclassify about 30% of cardiac effusions as exudates, possibly leading to unnecessary testing. Our purpose was to derive and validate a scoring model to effectively identify these falsely categorized cardiac effusions, in the setting of natriuretic peptide lacking data.
Methods: We retrospectively analyzed data from 3182 patients with exudative pleural effusions based on Light's criteria, of whom 276 had heart failure (derivation set).
Objective: To establish the diagnostic accuracy of pleural fluid (PF) CEA and CA 15-3 in identifying malignancy, and to determine the additional value of these markers in patients with malignant pleural effusions (MPEs) with false negative results from cytological fluid examination.
Methods: PF concentrations of CEA and/or CA 15-3 were determined in 1,575 patients with non-purulent exudates, 549 of whom had confirmed MPEs, 284 probable MPEs, and 742 benign effusions. Tumor marker cut-off points were set to ensure 100% specificity for malignant effusion.
Background And Objective: The clinical relevance of pleural effusions in lung cancer has seldom been approached systematically. The aim of this study was to determine the prevalence, causes and natural history of lung cancer-associated pleural effusions, as well as their influence on survival.
Methods: Retrospective review of clinical records and imaging of 556 consecutive patients with a newly diagnosed lung cancer over a 4-year period at our institution.
Background And Objective: The purpose of this study was to compare the diagnostic utility of pleural fluid N-terminal pro-B-type natriuretic peptide (NT-proBNP), midregion pro-atrial natriuretic peptide (MR-proANP) and midregion pro-adrenomedullin (MR-proADM) for discriminating heart failure (HF)-associated effusions.
Methods: NT-proBNP, MR-proANP and MR-proADM were measured by commercially available methodologies in the pleural fluid of a retrospective cohort of 185 consecutive patients with pleural effusions, of whom 95 had acute decompensated HF. Receiver-operating characteristic and area under the curve (AUC) analyses allowed comparisons of the discriminative properties of these biomarkers to be made at their optimal cut-off points.