Title |
Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection
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Published in |
BMC Infectious Diseases, April 2012
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DOI | 10.1186/1471-2334-12-88 |
Pubmed ID | |
Authors |
Jörg Schüpbach, Leslie R Bisset, Martin D Gebhardt, Stephan Regenass, Philippe Bürgisser, Meri Gorgievski, Thomas Klimkait, Corinne Andreutti, Gladys Martinetti, Christoph Niederhauser, Sabine Yerly, Stefan Pfister, Detlev Schultze, Marcel Brandenberger, Franziska Schöni-Affolter, Alexandra U Scherrer, Huldrych F Günthard, Swiss HIV Cohort Study |
Abstract |
Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Venezuela, Bolivarian Republic of | 1 | 25% |
United Kingdom | 1 | 25% |
United States | 1 | 25% |
Unknown | 1 | 25% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 1 | 3% |
Portugal | 1 | 3% |
Argentina | 1 | 3% |
Unknown | 27 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 30% |
Student > Bachelor | 5 | 17% |
Student > Ph. D. Student | 4 | 13% |
Student > Master | 2 | 7% |
Other | 2 | 7% |
Other | 4 | 13% |
Unknown | 4 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 9 | 30% |
Agricultural and Biological Sciences | 3 | 10% |
Mathematics | 2 | 7% |
Immunology and Microbiology | 2 | 7% |
Unspecified | 1 | 3% |
Other | 7 | 23% |
Unknown | 6 | 20% |