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A hypothetical ideal "gold standard" test has a sensitivity of 100% concerning the presence of the disease (it identifies all individuals with a well-defined disease process; it does not have any false-negative results) and a specificity of 100% (it does not falsely identify someone with a condition that does not have the condition; it does not have any false-positive results).
The 'worst-case' sensitivity or specificity must be calculated in order to avoid reliance on experiments with few results. For example, a particular test may easily show 100% sensitivity if tested against the gold standard four times, but a single additional test against the gold standard that gave a poor result would imply a sensitivity of ...
Whether a bacterium is sensitive or not is determined by visual inspection or automatic optical methods, after a period of incubation. [5] Broth dilution is considered the gold standard for phenotypic testing. [14] The lowest concentration of antibiotics that inhibits growth is considered the MIC. [5]
The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
The Quantiferon-TB Gold test (QFT-G) is a whole-blood test for use as an aid in diagnosing Mycobacterium tuberculosis infection, including latent tuberculosis infection (LTBI) and tuberculosis (TB) disease. [15] This test was approved by the U.S. Food and Drug Administration (FDA) in 2005.
The blood tests QuantiFERON-TB Gold In-Tube and T-SPOT.TB use these antigens to detect people with tuberculosis. Lymphocytes from the patient's blood are incubated with the antigens. These tests are called interferon γ tests and are not equivalent. [19] If the patient has been exposed to tuberculosis before, T lymphocytes produce interferon γ ...
These studies can thus be subjected to verification bias. One method to limit verification bias in clinical studies is to perform gold standard testing in a random sample of study participants. [citation needed] In most situations, verification bias introduces a sensitivity estimate that is too high and a specificity that is too low. [3]
The glucose clamp technique was developed by University of Texas (UT) School of Medicine Professors DeFronzo, Andres and Tobin in 1979. [2] It has since been the gold standard for pharmacodynamic studies in diabetes drug development and diagnostics evaluation. [3]
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