Medical test | |
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Intervention | |
X-ray of a hand. X-rays are a common medical test. |
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MeSH | D019937 |
A medical test is a kind of medical procedure performed to detect, diagnose, or monitor diseases, disease processes, susceptibility, and determine a course of treatment.
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Medical tests can be classified by what the test result will be used for, mainly including usage for diagnosis, screening or evaluation, as separately detailed below.
A diagnostic test is a procedure performed to confirm, or determine the presence of disease in an individual suspected of having the disease, usually following the report of symptoms, or based on the results of other medical tests.[1][2] Such tests include:
A screening is a medical test or series used to detect or predict the presence of disease in individuals at risk for disease within a defined group, such as a population, family, or workforce.[4] [5] Screenings may be performed to monitor disease prevalence, manage epidemiology, aid in prevention, or strictly for statistical purposes.[6]
Examples of screenings include measuring the level of TSH in the blood of a newborn infant as part of newborn screening for congenital hypothyroidism,[7] checking for Lung cancer in non-smoking individuals who are exposed to second-hand smoke in an unregulated working environment, and Pap smear screening for prevention or early detection of cervical cancer.
Some medical tests are used to monitor the progress of, or response to medical treatment.
Most test methods can be classified into either of the following broad groups:
Tests can be classified according to the location of the sample being tested, including:
Tests performed in a physical examination are usually aimed at detecting a symptom or sign, and in these cases, a test that detects a symptom or sign is designated a positive test, and a test that indicated absence of a symptom or sign is designated a negative test, as further detailed in separate section below.
A quantification of a target substance, a cell type or another specific entity is a common output of, for example, most blood tests. This is not only answering if a target entity is present or absent, but also how much is present. In blood tests, the quantification is relatively well specified, such as given in mass concentration, while most other tests may be quantifications as well although less specified, such as a sign of being "very pale" rather than "slightly pale". Similarly, radiologic images are technically quantifications of radiologic opacity of tissues.
Especially in the taking of a medical history, there is no clear limit between a detecting or quantifying test versus rather descriptive information of an individual. For example, questions regarding the occupation or social life of an individual may be regarded as tests that can be regarded as positive or negative for the presence of various risk factors, or they may be regarded as "merely" descriptive, although the latter may be at least as clinically important.
The result of a test aimed at detection of an entity may be positive or negative: this has nothing to do with a bad prognosis, but rather means that the test worked or not, and a certain parameter that was evaluated was present or not. For example, a negative screening test for breast cancer means that no sign of breast cancer could be found (which is in fact very positive for the patient).
The classification of tests into either positive or negative gives a binary classification, with resultant ability to perform bayesian probability and performance metrics of tests, including calculations of sensitivity and specificity.
Tests whose results are of continuous values, such as most blood values, can be interpreted as they are, or they can be converted to a binary ones by defining a cutoff value, with test results being designated as positive or negative depending on whether the resultant value is higher or lower than the cutoff.
In the finding of a pathognomonic sign or symptom it is almost certain that the target condition is present, and in the absence of finding a sine qua non sign or symptom it is almost certain that the target condition is absent. In reality, however, the subjective probability of the presence of a condition is never exactly 100% or 0%, so tests are rather aimed at estimating a post-test probability of a condition or other entity.
Most diagnostic tests basically use a reference group to establish performance data such as predictive values, likelihood ratios and relative risks, which are then used to interpret the post-test probability for an individual.
In monitoring tests of an individual, the test results from previous tests on that individual may be used as a reference to interpret subsequent tests.
Some medical testing procedures have health risks, and even require general anesthesia, such as the mediastinoscopy.[8] Other tests, such as the blood test or pap smear have little to no direct risks.[9] Medical tests may also have indirect risks, such as the stress of testing, and riskier tests may be required as follow-up for a (potentially) false positive test result. Consult the physician prescribing any test for further information.
Each test has its own indications and contraindications, but in a simplified fashion, how much a test is indicated for an individual depends largely on its net benefit for that individual, which may roughly be estimated by:
, where:
Additional factors that influence a decision whether a medical test should be performed or not include: cost of the test, availability of additional tests, potential interference with subsequent test (such as an abdominal palpation potentially inducing intestinal activity whose sounds interfere with a subsequent abdominal auscultation), time taken for the test or other practical or administrative aspects. The possible benefits of a diagnostic test may also be weighed against the costs of unnecessary tests and resulting unnecessary follow-up and possibly even unnecessary treatment of incidental findings.[10] Also, even if not beneficial for the individual being tested, the results may be useful for the establishment of statistics in order to improve health care for other individuals.
The QUADAS-2 revision is available.[11]
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