| Title |
Variability of the QuantiFERON®-TB Gold In-Tube Test Using Automated and Manual Methods
|
|---|---|
| Published in |
PLOS ONE, January 2014
|
| DOI | 10.1371/journal.pone.0086721 |
| Pubmed ID | |
| Authors |
William C. Whitworth, Donald J. Goodwin, Laura Racster, Kevin B. West, Stella O. Chuke, Laura J. Daniels, Brandon H. Campbell, Jamaria Bohanon, Atheer T. Jaffar, Wanzer Drane, Paul A. Sjoberg, Gerald H. Mazurek |
| Abstract |
The QuantiFERON®-TB Gold In-Tube test (QFT-GIT) detects Mycobacterium tuberculosis (Mtb) infection by measuring release of interferon gamma (IFN-γ) when T-cells (in heparinized whole blood) are stimulated with specific Mtb antigens. The amount of IFN-γ is determined by enzyme-linked immunosorbent assay (ELISA). Automation of the ELISA method may reduce variability. To assess the impact of ELISA automation, we compared QFT-GIT results and variability when ELISAs were performed manually and with automation. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Unknown | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 23% |
| Student > Ph. D. Student | 4 | 11% |
| Student > Bachelor | 3 | 9% |
| Student > Doctoral Student | 3 | 9% |
| Researcher | 3 | 9% |
| Other | 8 | 23% |
| Unknown | 6 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 40% |
| Immunology and Microbiology | 5 | 14% |
| Agricultural and Biological Sciences | 3 | 9% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Computer Science | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 6 | 17% |