Abstract
Leptospirosis is a zoonotic disease that has spread worldwide and causes significant economic losses in the dairy industry. The causal agents of this infectious disease are members of the genus Leptospira, known as pathogenic Leptospira spp. Specific clinical signs of the infection are difficult to detect. Therefore, the disease is normally under-diagnosed, mostly due to the lack of a cost-effective technique for diagnosing animals with a low bacterial load in their urine. The aim of this study was to assess the diagnostic accuracy of a qPCR coupled with a previous Immunomagnetic separation (IMS) step (IMS-qPCR) against a qPCR without using IMS, using a Bayesian latent class model (2 tests, 3 populations) to determine the leptospirosis infectious status in naturally infected dairy cattle. The results revealed that IMS qPCR had a sensitivity (Se) of 95.7% (95% Probability Interval (PI) = 85.0; 99.4%) and a specificity (Sp) of 98% (95% PI = 96.1; 99.4%), indicating that it is more sensitive than conventional qPCR (Se = 69.7% (95% PI = 59.2; 79.0%); median difference = 25.2% (Monte Carlo Error = 10.2%); and the Sp = 98.8% (95% PI = 97.6; 99.5%), median difference = 0.8% (Monte Carlo Error = 2.1%). Therefore, results shows that IMS-qPCR is a more useful diagnostic tool in terms of accuracy for detecting infectious animals with pathogenic Leptospira in their urine.
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