Primo infection test positif

The Human Phenotype Ontology (HPO) provides the following list of features that have been reported in people with this condition. Much of the information in the HPO comes from Orphanet , a European rare disease database. If available, the list includes a rough estimate of how common a feature is (its frequency). Frequencies are based on a specific study and may not be representative of all studies. You can use the MedlinePlus Medical Dictionary for definitions of the terms below.

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This project is supported by the Health Resources and Services Administration (HRSA) of the . Department of Health and Human Services (HHS) under grant number U1OHA28686 (AIDS Education and Training Centers National Coordinating Resource Center) awarded to the François-Xavier Bagnoud Center from the Rutgers University School of Nursing. No percentage of this project was financed with non-governmental sources. This information or content and conclusions are those of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS or the . Government.

Of course, the actual numbers vary depending on the testing population. This is because interpreting of the results of any medical test (assuming no test is 100% accurate) depends upon the initial degree of belief, or the prior probability that an individual has, or does not have a disease. Generally the prior probability is estimated using the prevalence of a disease within a population or at a given testing location. The positive predictive value and negative predictive value of all tests, including HIV tests, take into account the prior probability of having a disease along with the accuracy of the testing method to determine a new degree of belief that an individual has or does not have a disease (also known as the posterior probability ). The chance that a positive test accurately indicates an HIV infection increases as the prevalence or rate of HIV infection increases in the population. Conversely, the negative predictive value will decrease as the HIV prevalence rises. Thus a positive test in a high-risk population, such as people who frequently engage in unprotected anal intercourse with unknown partners, is more likely to correctly represent HIV infection than a positive test in a very low-risk population, such as unpaid blood donors.

Primo infection test positif

primo infection test positif

Of course, the actual numbers vary depending on the testing population. This is because interpreting of the results of any medical test (assuming no test is 100% accurate) depends upon the initial degree of belief, or the prior probability that an individual has, or does not have a disease. Generally the prior probability is estimated using the prevalence of a disease within a population or at a given testing location. The positive predictive value and negative predictive value of all tests, including HIV tests, take into account the prior probability of having a disease along with the accuracy of the testing method to determine a new degree of belief that an individual has or does not have a disease (also known as the posterior probability ). The chance that a positive test accurately indicates an HIV infection increases as the prevalence or rate of HIV infection increases in the population. Conversely, the negative predictive value will decrease as the HIV prevalence rises. Thus a positive test in a high-risk population, such as people who frequently engage in unprotected anal intercourse with unknown partners, is more likely to correctly represent HIV infection than a positive test in a very low-risk population, such as unpaid blood donors.

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