Dr. Sarah Larsen ~ Medical Intuitive and Energy Healer

Medical Intuitive and Energy Healer for the Mind, Body, and Soul

Understanding Tests for Covid-19 (or false-/false+) Why You May Need Antigen & Antibody Test

Viral Tests

Test Overview
From: https://www.uofmhealth.org/health-library/hw235580

A viral test is done to find infection-causing viruses. Viruses grow only in living cells. Viruses cause disease by destroying or damaging the cells they infect, damaging the body’s immune system, changing the genetic material (DNA) of the cells they infect, or causing inflammation that can damage an organ. Viruses cause many types of diseases, such as human immunodeficiency virus (HIV), cold sores, chickenpox, measles, flu (influenza), and some types of cancer.

Viral tests may be done for viruses such as:

Several types of tests may be used to check for viruses:

  • Antibody test. Antibodies are substances made by the body’s immune system to fight a specific viral infection. The antibodies attach to a cell infected by the virus and cause the virus to be destroyed. This test looks for antibodies to a specific viral infection. It is generally done on a blood sample. If the antibody is found, this test can show whether a person was infected recently or in the past.
  • Viral antigen detection test. Viral antigens develop on the surface of cells infected with a specific virus. A viral antigen detection test is done on a sample of tissue that might be infected. Specially tagged (with dye or a tracer) antibodies that attach to those viral antigens are mixed with the sample. The tagged antibodies can be seen by using a special light (or other method). If the tagged antibodies are attached to the cells, the cells are infected with the virus.
  • Viral culture. This is a test to find a virus that can cause an infection. A sample of body fluid or tissue is added to certain cells used to grow a virus. If no virus infects the cells, the culture is negative. If a virus that can cause infection infects the cells, the culture is positive. A viral culture may take several weeks to show results.
  • Viral DNA or RNA detection test. Using a sample of tissue or blood or other fluid (such as spinal fluid), this type of test looks for the genetic material (DNA or RNA) of a specific virus. This test can show the exact virus causing an infection.

Different types of samples are used for a viral test, including blood, urine, stool (feces), organ tissue, spinal fluid, and saliva. The type of sample used for the test depends on the type of infection that may be present.

Emma_Bryce

A mosquito lands on your arm, injects its chemicals into your skin, and begins to feed. You wouldn’t even know it was there, if not for the red lump that appears, accompanied by a telltale itch. It’s a nuisance, but that bump is an important signal that you’re protected by your immune system, your body’s major safeguard against infection, illness, and disease. 00:31

This system is a vast network of cells, tissues, and organs that coordinate your body’s defenses against any threats to your health. Without it, you’d be exposed to billions of bacteria, viruses, and toxins that could make something as minor as a paper cut or a seasonal cold fatal. 00:51

The immune system relies on millions of defensive white blood cells, also known as leukocytes, that originate in our bone marrow. These cells migrate into the bloodstream and the lymphatic system, a network of vessels which helps clear bodily toxins and waste. Our bodies are teeming with leukocytes: there are between 4,000 and 11,000 in every microliter of blood. 01:17

As they move around, leukocytes work like security personnel, constantly screening the blood, tissues, and organs for suspicious signs. This system mainly relies on cues called antigens. These molecular traces on the surface of pathogens and other foreign substances betray the presence of invaders. As soon as the leukocytes detect them, it takes only minutes for the body’s protective immune response to kick in. 01:44

Threats to our bodies are hugely variable, so the immune response has to be equally adaptable. That means relying on many different types of leukocytes to tackle threats in different ways. 01:55

Despite this diversity, we classify leukocytes in two main cellular groups, which coordinate a two-pronged attack. First, phagocytes trigger the immune response by sending macrophages and dendritic cells into the blood. As these circulate, they destroy any foreign cells they encounter, simply by consuming them. That allows phagocytes to identify the antigen on the invaders they just ingested and transmit this information to the second major cell group orchestrating the defense, the lymphocytes. 02:29

A group of lymphocyte cells called T-cells go in search of infected body cells and swiftly kill them off. Meanwhile, B-cells and helper T-cells use the information gathered from the unique antigens to start producing special proteins called antibodies. This is the pièce de résistance: Each antigen has a unique, matching antibody that can latch onto it like a lock and key, and destroy the invading cells. B-cells can produce millions of these, which then cycle through the body and attack the invaders until the worst of the threat is neutralized. 03:07

While all of this is going on, familiar symptoms, like high temperatures and swelling, are actually processes designed to aid the immune response. A warmer body makes it harder for bacteria and viruses to reproduce and spread because they’re temperature-sensitive. And when body cells are damaged, they release chemicals that make fluid leak into the surrounding tissues, causing swelling. That also attracts phagocytes, which consume the invaders and the damaged cells. 03:37

Usually, an immune response will eradicate a threat within a few days. It won’t always stop you from getting ill, but that’s not its purpose. Its actual job is to stop a threat from escalating to dangerous levels inside your body. And through constant surveillance over time, the immune system provides another benefit: it helps us develop long-term immunity. When B- and T-cells identify antigens, they can use that information to recognize invaders in the future. So, when a threat revisits, the cells can swiftly deploy the right antibodies to tackle it before it affects any more cells. That’s how you can develop immunity to certain diseases, like chickenpox. 04:19

It doesn’t always work so well. Some people have autoimmune diseases, which trick the immune system into attacking the body’s own perfectly healthy cells. No one knows exactly what causes them, but these disorders sabotage the immune system to varying degrees, and underlie problems like arthritis, Type I diabetes, and multiple sclerosis. 04:42

For most individuals, however, a healthy immune system will successfully fight off an estimated 300 colds and innumerable other potential infections over the course of a lifetime. Without it, those threats would escalate into something far more dangerous. So the next time you catch a cold or scratch a mosquito bite, think of the immune system. We owe it our lives. 

False Positives and False Negatives

Small changes can have huge consquences

When developing detection algorithms or tests, a balance must be chosen between risks of false negatives and false positives. Usually there is a threshold of how close a match to a given sample must be achieved before the algorithm reports a match. The higher this threshold, the more false negatives and the fewer false positives.

In medical testing, and more generally in binary classification, a false positive is an error in data reporting in which a test result improperly indicates presence of a condition, such as a disease (the result is positive), when in reality it is not present, while a false negative is an error in which a test result improperly indicates no presence of a condition (the result is negative), when in reality it is present. These are the two kinds of errors in a binary test (and are contrasted with a correct result, either a true positive or a true negative.) They are also known in medicine as a false positive (respectively negative) diagnosis, and in statistical classification as a false positive (respectively negative) error.[1] A false positive is distinct from overdiagnosis,[2] and is also different from overtesting.[3]

In statistical hypothesis testing the analogous concepts are known as type I and type II errors, where a positive result corresponds to rejecting the null hypothesis, and a negative result corresponds to not rejecting the null hypothesis. The terms are often used interchangeably, but there are differences in detail and interpretation due to the differences between medical testing and statistical hypothesis testing.

Contents

False positive error[edit]

A false positive error, or in short a false positive, commonly called a “false alarm“, is a result that indicates a given condition exists, when it does not. For example, in the case of “The Boy Who Cried Wolf“, the condition tested for was “is there a wolf near the herd?”; the shepherd at first wrongly indicated there was one, by calling “Wolf, wolf!”

A false positive error is a type I error where the test is checking a single condition, and wrongly gives an affirmative (positive) decision. However it is important to distinguish between the type 1 error rate and the probability of a positive result being false. The latter is known as the false positive risk (see Ambiguity in the definition of false positive rate, below).[4]

False negative error[edit]

A false negative error, or in short a false negative, is a test result that indicates that a condition does not hold, while in fact it does. In other words, erroneously, no effect has been inferred. An example for a false negative is a test indicating that a woman is not pregnant whereas she is actually pregnant. Another example is a truly guilty prisoner who is acquitted of a crime. The condition “the prisoner is guilty” holds (the prisoner is indeed guilty). But the test (a trial in a court of law) failed to realize this condition, and wrongly decided that the prisoner was not guilty, falsely concluding a negative about the condition.

A false negative error is a type II error occurring in a test where a single condition is checked for and the result of the test is erroneously that the condition is absent.[5]

Related terms[edit]

False positive and false negative rates[edit]

Main articles: Sensitivity and specificity and False positive rate

The false positive rate 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.

The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.

In statistical hypothesis testing, this fraction is given the Greek letter ?, and 1?? is defined as the specificity of the test. Increasing the specificity of the test lowers the probability of type I errors, but raises the probability of type II errors (false negatives that reject the alternative hypothesis when it is true).[a]

Complementarily, the false negative rate is the proportion of positives which yield negative test outcomes with the test, i.e., the conditional probability of a negative test result given that the condition being looked for is present.

In statistical hypothesis testing, this fraction is given the letter ?. The “power” (or the “sensitivity“) of the test is equal to 1??.

Ambiguity in the definition of false positive rate[edit]

The term false discovery rate (FDR) was used by Colquhoun (2014)[6] to mean the probability that a “significant” result was a false positive. Later Colquhoun (2017)[4] used the term false positive risk (FPR) for the same quantity, to avoid confusion with the term FDR as used by people who work on multiple comparisons. Corrections for multiple comparisons aim only to correct the type I error rate, so the result is a (corrected) p value. Thus they are susceptible to the same misinterpretation as any other p value. The false positive risk is always higher, often much higher, than the p value.[6][4] Confusion of these two ideas, the error of the transposed conditional, has caused much mischief.[7] Because of the ambiguity of notation in this field, it is essential to look at the definition in every paper. The hazards of reliance on p-values was emphasized in Colquhoun (2017)[4] by pointing out that even an observation of p = 0.001 was not necessarily strong evidence against the null hypothesis. Despite the fact that the likelihood ratio in favor of the alternative hypothesis over the null is close to 100, if the hypothesis was implausible, with a prior probability of a real effect being 0.1, even the observation of p = 0.001 would have a false positive rate of 8 percent. It wouldn’t even reach the 5 percent level. As a consequence, it has been recommended[4][8] that every p value should be accompanied by the prior probability of there being a real effect that it would be necessary to assume in order to achieve a false positive risk of 5%. For example, if we observe p= 0.05 in a single experiment, we would have to be 87% certain that there as a real effect before the experiment was done to achieve a false positive risk of 5%.

Receiver operating characteristic[edit]

The article “Receiver operating characteristic” discusses parameters in statistical signal processing based on ratios of errors of various types.

Consequences[edit]

In many legal traditions there is a presumption of innocence, as stated in Blackstone’s formulation:”It is better that ten guilty persons escape than that one innocent suffer.”

That is, false negatives (a guilty person is acquitted and goes unpunished) are far less adverse than false positives (an innocent person is convicted and suffers). This is not universal, however, and some systems prefer to jail many innocent, rather than let a single guilty escape – the tradeoff varies between legal traditions.[citation needed]

Notes[edit]

  1. ^ When developing detection algorithms or tests, a balance must be chosen between risks of false negatives and false positives. Usually there is a threshold of how close a match to a given sample must be achieved before the algorithm reports a match. The higher this threshold, the more false negatives and the fewer false positives.


April 28, 2020, 2:00 PM PDTBy Denise Chow

Cities and states across the country are looking to expand coronavirus testing as part of efforts to emerge from lockdowns, but two major barriers remain: how to screen huge parts of the population and how to do it quickly.

Antigen testing, which can offer faster results with less lab work, is the newest idea beginning to take hold.

“We have to have a breakthrough innovation in testing,” Dr. Deborah Birx, the White House coronavirus task force coordinator, said in an interview Sunday on NBC News’ “Meet the Press.” “We have to be able to detect antigens, rather than constantly trying to detect the actual live virus or the viral particles itself, and really move into antigen testing.”

But antigen tests are not a single fix for the widespread testing shortages. No coronavirus antigen tests have been approved by the Food and Drug Administration, and existing antigen tests for other viruses have their faults. But experts say the tools could become part of the broader solution.

Antigen tests are designed to detect viral proteins — which, in the case of the coronavirus, would come from the spikes that coat the outside surface of the virus — that trigger an immune response in the body.

More states ease lockdowns, White House reveals testing ‘blueprint’: TODAY’s top news stories

APRIL 28, 202018:10

For now, the main way to screen for COVID-19, the disease caused by the coronavirus, is through what’s known as polymerase chain reaction, or PCR, testing. The test lookS for the coronavirus’ genetic material in a sample, but because the viral RNA is so tiny, it needs to be “amplified,” or copied millions of times in a lab, to get a result.

“They’re much more complicated to do, but PCR tests are the most sensitive,” said Dr. Pedro Piedra, a professor of molecular virology and microbiology at the Baylor College of Medicine in Houston.

Full coverage of the coronavirus outbreak

Although it is accurate, PCR testing is both resource and time intensive.

“Many of the current tests require multiple steps, manual pipetting of reaction components, and very accurate pipetting skills,” Dr. Marie-Louise Landry, director of the Clinical Virology Laboratory at the Yale School of Medicine in New Haven, Connecticut, said in an email. “There are large instruments that can automate much of the PCR process and have a higher ‘throughput,’ but these may still only do 300-400 samples in an eight-hour shift.”

That makes it difficult to significantly ramp up PCR testing throughout the country.

“There will never be the ability on a [PCR] test to do 300 million tests a day or to test everybody before they go to work or to school, but there might be with the antigen test,” Birx said during a coronavirus task force briefing April 17.

Both antigen and PCR tests require nasal swabs, but antigen testing is simpler and could be conducted by primary care physicians. Patients would also get results in less than an hour.

Recommended

CORONAVIRUSCongress sounds alarm over inaccurate antibody tests

CORONAVIRUSNew York City teacher dies from COVID-19 after she was denied tests, family says

Antigen testing exists for the flu, in which doctors can administer “rapid influenza diagnostic tests” that deliver results in 15 to 30 minutes. It is hoped that any breakthroughs in antigen testing for the coronavirus would have similar outcomes.

“You don’t need specialized personnel to run the test, it’s cost-effective and you get rapid results — that’s what you’re looking for here,” said Dr. Aron Lukacher, chair of the department of microbiology and immunology at Penn State College of Medicine in Hershey, Pennsylvania.

But antigen testing is not as sensitive as PCR testing, which means there is a greater chance that antigen tests could deliver false negative results. In other words, a patient could be infected but an antigen test is just not sensitive enough to detect it.

For some antigen tests, the rate of false negatives can be 5 percent to 10 percent, according to Lukacher, which makes them less reliable. PCR testing, although not perfect, is thought to be more finely tuned, because amplifying the virus’ genetic material also means smaller amounts of the virus can be detected.

Download the NBC News app for full coverage and alerts about the coronavirus outbreak

Antigen tests can also be challenging to develop because scientists need to be intimately familiar with the virus’ structure and biology to know what immune response will be triggered by these foreign substances.

“PCR tests have the advantage that you can test for many pathogens, not just one virus,” Piedra said. “Antigen tests have to be built for specific viruses.”

Health officials are hopeful that significant strides can be made in designing new diagnostic tools. Earlier this month, the federal government’s Biomedical Advanced Research and Development Authority awarded more than $710,000 to a Pennsylvania-based company called OraSure Technologies to develop a rapid coronavirus test using saliva samples. Other researchers at E25Bio, a Massachusetts-based biotech company, are working on a coronavirus antigen test that could deliver results in 15 minutes.

Still, Lukacher said, rapid antigen tests are unlikely to be a silver bullet for cities looking to restart their economies and emerge from lockdowns. Rather, any breakthroughs in antigen testing will likely have to be scaled up in tandem with PCR testing for health officials to determine how much the virus has spread in a community.

“The bottom line is we would want both — rapid screening and the ability to test by PCR,” Lukacher said. “All of these things have to be done in conjunction with one another.”

Testimonials

Dr. Sarah Larsen