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Swiss-model. Domains. InterPro. The N-terminal prohormone of brain natriuretic peptide (NT-proBNP or BNPT) is a prohormone with a 76 amino acid N-terminal inactive protein that is cleaved from the molecule to release brain natriuretic peptide 32 (BNP, also known as B-type natriuretic peptide). Both BNP and NT-proBNP levels in the blood are used ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. [6] The false positive rate depends on the significance level. The specificity of the test is equal to 1 minus the false positive rate.
The BNP test is also used for the risk stratification of patients with acute coronary syndromes. [40] [41] When interpreting an elevated BNP level, values may be elevated due to factors other than heart failure. Lower levels are often seen in obese patients. [42] Higher levels are seen in those with renal disease, in the absence of heart failure.
A natriuretic peptide is a hormone molecule that plays a crucial role in the regulation of the cardiovascular system. These hormones were first discovered in the 1980s and were found to have very strong diuretic, natriuretic, and vasodilatory effects. There are three main types of natriuretic peptides: atrial natriuretic peptide (ANP), brain ...
v. t. e. Reference ranges (reference intervals) for blood tests are sets of values used by a health professional to interpret a set of medical test results from blood samples. Reference ranges for blood tests are studied within the field of clinical chemistry (also known as "clinical biochemistry", "chemical pathology" or "pure blood chemistry ...
Sensitivity (true positive rate) is the probability of a positive test result, conditioned on the individual truly being positive. Specificity (true negative rate) is the probability of a negative test result, conditioned on the individual truly being negative. If the true status of the condition cannot be known, sensitivity and specificity can ...
An example of the base rate fallacy is the false positive paradox (also known as accuracy paradox). This paradox describes situations where there are more false positive test results than true positives (this means the classifier has a low precision). For example, if a facial recognition camera can identify wanted criminals 99% accurately, but ...
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.