The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Michael R Jordan - One of the best experts on this subject based on the ideXlab platform.
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collaborative update of a rule based expert system for hiv 1 genotypic resistance Test Interpretation
PLOS ONE, 2017Co-Authors: Roger Paredes, Philip L Tzou, Geoff Barrow, Ricardo Jorge Camacho, Sergio Carmona, Philip M Grant, Ravindra K Gupta, Raph L Hamers, Richard P Harrigan, Michael R JordanAbstract:CITATION: Paredes, R., et al. 2018. Collaborative update of a rule-based expert system for HIV-1 genotypic resistance Test Interpretation. PLoS ONE, 12(7):e0181357, doi:10.1371/journal.pone.0181357.
Jonathan Taylor - One of the best experts on this subject based on the ideXlab platform.
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predictive value of hiv 1 genotypic resistance Test Interpretation algorithms
The Journal of Infectious Diseases, 2009Co-Authors: Sooyon Rhee, Jeffrey W Fessel, Natalia Marlowe, Charles M Rowland, Richard A Rode, Annemieke Vandamme, Kristel Van Laethem, Franccoise Brunvezinet, Vincent Calvez, Jonathan TaylorAbstract:Retrospective studies have shown that the presence of human immunodeficienc virus type 1 (HIV-1) drug resistance before the start of a new antiretroviral (ARV) regimen is an independent predictor of the virologic response (VR) to that regimen [1]. Prospective controlled studies have shown that patients whose physicians have access to drug-resistance data respond better to therapy than those whose physicians do not [2–5]. The accumulation of such retrospective and prospective data has led to the routine use of genotypic resistance Testing in the management of HIV-1–infected patients [6–8]. However, interpreting the results of HIV-1 genotypic drug-resistance Tests is one of the most diffi ult challenges facing clinicians who care for HIV-1–infected patients. First, there are many mutations associated with drug resistance [9]. Second, there are synergistic and antagonistic interactions among these drug-resistance mutations [10]. Third, some mutations may not reduce susceptibility by themselves but may compensate for the effect of other mutations [11] or may be sentinel indicators of emerging drug resistance. As a result, several different algorithms have been developed for interpreting HIV-1 genotypic drug-resistance Test results. Several studies have compared the predictive ability of different genotypic drug-resistance algorithms using retrospective clinical data sets [12–17]. In the present study, we evaluate the predictive value of 4 genotypic drug-resistance Test Interpretation algorithms in a patient population undergoing a wide range of salvage ARV therapy.
Robert W Shafer - One of the best experts on this subject based on the ideXlab platform.
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web resources for hiv type 1 genotypic resistance Test Interpretation
Clinical Infectious Diseases, 2006Co-Authors: Robert W ShaferAbstract:Interpreting the results of plasma human immunodeficiency virus type 1 (HIV-1) genotypic drug-resistance Tests is one of the most difficult tasks facing clinicians caring for HIV-1-infected patients. There are many drug-resistance mutations, and they arise in complex patterns that cause varying levels of drug resistance. In addition, HIV-1 exists in vivo as a virus population containing many genomic variants. Genotypic-resistance Testing detects the drug-resistance mutations present in the most common plasma virus variants but may not detect drug-resistance mutations present in minor virus variants. Therefore, Interpretation systems are necessary to determine the phenotypic and clinical significance of drug-resistance mutations found in a patient's plasma virus population. We describe the scientific principles of HIV-1 genotypic-resistance Test Interpretation and the most commonly used Web-based resources for clinicians ordering genotypic drug-resistance Tests.
George R Wilson - One of the best experts on this subject based on the ideXlab platform.
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family physicians proficiency in urine drug Test Interpretation
Journal of opioid management, 2007Co-Authors: Gary M Reisfield, Roger L Bertholf, Fern J Webb, Paul A Sloan, George R WilsonAbstract:Objective: To determine the proficiency in urine drug Test Interpretation among family medicine physicians who order these Tests to monitor adherence in their patients on chronic opioid therapy. Methods: A seven-question instrument, consisting of six, five-option, single-best-answer multiple choice questions and one yes/no question was administered to 80 family medicine physicians attending a University of Kentucky Family Medicine Review Course. We calculated frequencies and performed χ2 analyses to examine bivariate associations between urine drug Test utilization and interpretive knowledge. Results: The instrument was completed by 60/80 (75 percent) of eligible physicians (44 order urine drug Testing; 16 do not). None of the physicians who order urine drug Testing answered more than five of the seven questions correctly, and only 20 percent answered more than half correctly. Physicians who order urine drug Testing performed better than physicians who do not order urine drug Testing on only four of the seven questions, although there were no statistically significant differences between the groups on any question. Conclusions: Family medicine physicians who order urine drug Testing to monitor their patients on chronic opioid therapy are not proficient in their Interpretation. This study highlights the need for improved physician education in this area. It is imperative for physicians to work closely with certified laboratory professionals when ordering and interpreting urine drug Tests.
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urine drug Test Interpretation what do physicians know
Journal of opioid management, 2007Co-Authors: Gary M Reisfield, Roger L Bertholf, Robert L Barkin, Fern J Webb, George R WilsonAbstract:Objective: To determine the level of urine drug Test (UDT) interpretive knowledge of physicians who use these instruments to monitor adherence in their patients on chronic opioid therapy. Methods: A seven-question instrument consisting of six five-option, single-best-answer multiple choice ques¬tions and one yes/no question was completed by 114 physicians (77 who employ UDT and 37 who do not) attending one of three regional opioid education confer¬ences. We calculated frequencies and performed %2 analyses to examine bivariate associations between UDT utilization and interpretive knowledge. Results: The instrument was completed by 80percent of eligible respondents. None of the physicians who employ UDT answered all seven questions correctly, and only 30 percent answered more than half correctly. Physicians who employ UDTperformed no better on any of the ques¬tions than physicians who do not employ UDT. Conclusions: Physicians who employ UDT to monitor patients receiving chronic opioid therapy are not profi¬cient in Test Interpretation. This study highlights the need for improved physician education; it is imperative for physicians to work closely with certified laboratoryprofes- sionals when ordering and interpreting these Tests.
Roger Paredes - One of the best experts on this subject based on the ideXlab platform.
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collaborative update of a rule based expert system for hiv 1 genotypic resistance Test Interpretation
PLOS ONE, 2017Co-Authors: Roger Paredes, Philip L Tzou, Geoff Barrow, Ricardo Jorge Camacho, Sergio Carmona, Philip M Grant, Ravindra K Gupta, Raph L Hamers, Richard P Harrigan, Michael R JordanAbstract:CITATION: Paredes, R., et al. 2018. Collaborative update of a rule-based expert system for HIV-1 genotypic resistance Test Interpretation. PLoS ONE, 12(7):e0181357, doi:10.1371/journal.pone.0181357.
