Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2002-11-4
pubmed:abstractText
Evidence-based medicine encourages the use of quantitative diagnostic test results to estimate the probability of a particular diagnosis. Likelihood ratios (LRs) are among the best tools for maximizing the diagnostic information gained from diagnostic assays that provide results on a continuous scale. They provide the odds that an animal with a particular test result actually has the disease in question based on the magnitude of the test result. A commercial enzyme-linked immunosorbent assay (ELISA) was used to test sera from 143 dairy cattle infected with Mycobacterium paratuberculosis and 2974 cattle free of this infection. This assay transforms ELISA reader optical density values into sample-to-positive (S/P) ratios. The LR was calculated for S/P results from 0.00 to 1.00 at 0.05-S/P unit intervals. LRs were directly but not linearly correlated with ELISA S/P ratios (r(2) = 0.94). The mathematical function describing the relationship between the ELISA S/P ratio and the LR was LR = 265 x (S/P value)(2.03). LRs were also directly related to the frequency of animals testing positive for paratuberculosis by fecal culture and other serologic tests. Based on these LRs, guidelines for interpretation and application of this ELISA for the diagnosis and control of paratuberculosis in dairy cattle herds are recommended.
pubmed:commentsCorrections
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pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1071-412X
pubmed:author
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1367-71
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Interpretation of a commercial bovine paratuberculosis enzyme-linked immunosorbent assay by using likelihood ratios.
pubmed:affiliation
School of Veterinary Medicine, University of Wisconsin, Madison, Wisconsin 53706, USA. mcollin5@facstaff.wisc.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't