医学検査

医学検査
	手のX線撮影。X線検査は一般的な医学検査である。
MeSH	D019937
	[edit on Wikidata]

医学検査とは、特定、診断、または病気の監視、疾病プロセス、感受性、または治療方針を決定するために行われる医療処置のことである。人間ドックや視力検査、画像診断、遺伝子検査、臨床化学や分子診断学に関連する化学・細胞分析などの医学検査は、一般的に医療現場で行われる。

検査の種類

目的別

医学検査は、診断、スクリーニング、モニタリングなど、その目的によって分類することができる。

診断

肺シンチグラフィーによる肺がんの評価

診断検査は、通常、症状の報告後、または他の医学検査結果に基づいて、疾患の疑いがある個人の疾患の存在を確認または決定するために行われる処置である。これには死後診断も含まれる。このような検査の例としては、以下のようなものがある：

リンパ腫が疑われる患者を核医学で調べる。
糖尿病が疑われる人の血糖値を、排尿が増加した後に測定する。
細菌感染を調べるために、高発熱を経験している人の全血球数を測定する。
胸痛のある患者の心電図測定値をモニタリングし、心臓不整脈の診断や判定を行う。

スクリーニング

スクリーニングとは、集団、家族、労働力などの定義されたグループ内のリスクのある個人における疾患の存在を検出または予測するために使用される医学検査または一連の検査のことである。

スクリーニングの例としては、先天性甲状腺機能低下症の新生児スクリーニングの一環として新生児乳児の血液中のTSHのレベルを測定すること、規制されていない労働環境でセコンドハンドスモークにさらされている非喫煙者の肺がんをチェックすること、子宮頸がんの予防または早期発見のためのパップスメアスクリーニングなどがある。

モニタリング

いくつかの医学検査は、モニタリングの進行状況や医学的治療に対する反応を調べるために用いられる。

方法別

ほとんどの試験方法は、以下の大まかなグループのいずれかに分類することができる：

患者を観察し、写真に撮ったり、記録したりする。
個人の病歴を調べる際に尋ねられる質問
身体検査で行われる検査。
放射線検査では、例えばX線を使用して身体標的の画像を形成する。これらの検査ではしばしば造影剤の投与が行われる。
生体内で検査する生体内診断などがある：
- マノメトリーを行う。
- グルテン負荷試験、収縮負荷試験、気管支負荷試験、経口食物負荷試験、ACTH刺激試験のように、診断薬を投与し、身体の反応を測定する。
組織や体液のサンプルを検査するIn vitro diagnostics(試験管内診断)などがある：
- 液体生検
- 微生物学的培養、体内サンプル中の微生物の有無を判定するもので、通常は病原性細菌の検出を対象とする。
- 遺伝学的検査
- 血糖値
- 肝機能検査
- カルシウム検査
- ナトリウム、カリウム、クレアチニン、尿素などの血液中の電解質検査

検体の部位別

試験管内検査は、検査される試料の場所によって以下のように分類できる：

血液検査
尿検査,肉眼検査を含む
便検査,肉眼検査を含む
喀痰（痰）,肉眼検査を含む

Accuracy and precision

Accuracy of a laboratory test is its correspondence with the true value. Accuracy is maximized by calibrating laboratory equipment with reference material and by participating in external quality control programs.
Precision of a test is its reproducibility when it is repeated on the same sample. An imprecise test yields widely varying results on repeated measurement. Precision is monitored in laboratory by using control material.

Detection and quantification

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 a 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.

Positive or negative

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.

Continuous values

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.

Interpretation

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.

Risks

Some medical testing procedures have associated health risks, and even require general anesthesia, such as the mediastinoscopy. Other tests, such as the blood test or pap smear have little to no direct risks. 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 health care provider (including physicians, physician assistants, and nurse practitioners) prescribing any test for further information.

Indications

Each test has its own indications and contraindications. An indication is a valid medical reason to perform the test. A contraindication is a valid medical reason not to perform the test. For example, a basic cholesterol test may be indicated (medically appropriate) for a middle-aged person. However, if the same test was performed on that person very recently, then the existence of the previous test is a contraindication for the test (a medically valid reason to not perform it).

Information bias is the cognitive bias that causes healthcare providers to order tests that produce information that they do not realistically expect or intend to use for the purpose of making a medical decision. Medical tests are indicated when the information they produce will be used. For example, a screening mammogram is not indicated (not medically appropriate) for a woman who is dying, because even if breast cancer is found, she will die before any cancer treatment could begin.

In a simplified fashion, how much a test is indicated for an individual depends largely on its net benefit for that individual. Tests are chosen when the expected benefit is greater than the expected harm. The net benefit may roughly be estimated by:

$b_{n} = Δ p \times r_{i} \times (b_{i} - h_{i}) - h_{t}$

, where:

b_n is the net benefit of performing a test
Λp is the absolute difference between pre- and posttest probability of conditions (such as diseases) that the test is expected to achieve. A major factor for such an absolute difference is the power of the test itself, such as can be described in terms of, for example, sensitivity and specificity or likelihood ratio. Another factor is the pre-test probability, with a lower pre-test probability resulting in a lower absolute difference, with the consequence that even very powerful tests achieve a low absolute difference for very unlikely conditions in an individual (such as rare diseases in the absence of any other indicating sign), but on the other hand, that even tests with low power can make a great difference for highly suspected conditions. The probabilities in this sense may also need to be considered in context of conditions that are not primary targets of the test, such as profile-relative probabilities in a differential diagnostic procedure.
r_i is the rate of how much probability differences are expected to result in changes in interventions (such as a change from "no treatment" to "administration of low-dose medical treatment"). For example, if the only expected effect of a medical test is to make one disease more likely compared to another, but the two diseases have the same treatment (or neither can be treated), then, this factor is very low and the test is probably without value for the individual in this aspect.
b_i is the benefit of changes in interventions for the individual
h_i is the harm of changes in interventions for the individual, such as side effects of medical treatment
h_t is the harm caused by the test itself.

Some additional factors that influence a decision whether a medical test should be performed or not included: 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.

In some cases, tests being performed are expected to have no benefit for the individual being tested. Instead, the results may be useful for the establishment of statistics in order to improve health care for other individuals. Patients may give informed consent to undergo medical tests that will benefit other people.

患者の期待

In addition to considerations of the nature of medical testing noted above, other realities can lead to misconceptions and unjustified expectations among patients. These include: Different labs have different normal reference ranges; slightly different values will result from repeating a test; "normal" is defined by a spectrum along a bell curve resulting from the testing of a population, not by "rational, science-based, physiological principles"; sometimes tests are used in the hope of turning something up to give the doctor a clue as to the nature of a given condition; and imaging tests are subject to fallible human interpretation and can show "incidentalomas", most of which "are benign, will never cause symptoms, and do not require further evaluation," although clinicians are developing guidelines for deciding when to pursue diagnoses of incidentalomas.

報告および評価の基準

QUADAS-2リビジョンが発表された。

医学検査一覧

こちらも参照

さらに読む

World Health Organization (2019). First WHO Model List of Essential In Vitro Diagnostics. Geneva: World Health Organization. hdl:10665/311567. ISBN 978-92-4-121026-3. ISSN 0512-3054. WHO Technical Report Series, No. 1017. License: CC BY-NC-SA 3.0 IGO.