When Tests Deceive: Making Sense of Diagnostic Test Accuracy | Talk 7

A positive result isn't proof. In this lesson we break down how sensitivity, specificity, and disease prevalence determine what a diagnostic test actually tells you in practice. Starting from the simple 2×2 table, we cover predictive values (and why prevalence changes everything), ROC curves and AUC, and likelihood ratios — then work through a real case using NT-proBNP for occult HCM in cats. Clear, practical epidemiology for interpreting veterinary literature and applying test results to your own patients. 👍 Like and subscribe for more short, no-nonsense epidemiology lessons. #VeterinaryMedicine #VetMed #DiagnosticTesting #Sensitivity #Specificity #ROCCurve #LikelihoodRatios #EvidenceBasedMedicine #ClinicalEpidemiology #VetStudent #VeterinaryEducation #NTproBNP #FelineHCM #TestAccuracy #Biostatistics #vetschool