We have a series of extraordinary medical tests available to us. Many of them - usually blood tests - even come with results expressed in numbers that show the exact number of things measured. In laboratory reports, the amount measured is often accompanied by a "normal range" for what according to the laboratory should be its value, indicating a lower number and a higher number. So if you have laboratory tests, what does it mean when your measurements are inside or outside this range?
It all depends on the information. First of all, it's important what is being measured and why it is measured in the first place. In theory, laboratory tests are ordered when a doctor asks a question that a laboratory test should provide an answer. (If there is no question, how can laboratory tests be the answer?) For example, suppose a doctor sulfur analyzer indonesia wonders whether the vibration of your hand is caused by too much thyroid hormone in your bloodstream. So the doctor's question is: Does this person have too much thyroid hormone in the bloodstream? Tests that measure thyroid hormone will provide a clean answer if it is too high (yes) or within the normal range (no). Because thyroid hormone levels that are too low do not produce tremors, measurements that are too low will not be relevant to the questions asked. It may still require consideration in itself as "incidental findings," but not different from results in the range in answering the initial question.
What about the same blood test, but with different questions? Suppose the doctor is looking for why you are gaining weight. Doctors know that some people gain weight when their thyroid glands produce too little thyroid hormone. So the doctor's question is: Does this person have too little thyroid hormone in the bloodstream? This time, measuring thyroid hormone will provide a clean answer to the question whether it is lower than the normal range (yes) or in the normal range (no). Because elevated thyroid hormone levels usually do not cause weight gain, numbers higher than the normal range will produce answers to initial questions that are not different from those in the range. (But even if this result is unexpected, it might still be followed up.)
For some blood tests, the only meaningful outcome is in one direction. For example, measurement of blood urea nitrogen (BUN) assesses kidney function. If the BUN measurement is too high, it can indicate that the kidney is disrupted. But what does it mean if your BUN measurement is lower than the normal range? Absolutely nothing. This is not an event. So, it is very strange that the normal range for BUN even includes a lower number. How did it get there?
These examples lead to the question of how the normal range is made in the first place. They are produced by statistics produced by measurements obtained in healthy volunteers. In the case of BUN measurements, for example, this substance can be measured in the blood, say, 100 people without kidney disease. The average number will be calculated by adding numbers produced by all 100 people, and then dividing by 100. This average will be the center of the normal range.
But the top and bottom numbers are generated by other methods by looking at how broad BUN measurements are for these 100 people. After all, it is very unlikely that 100 people will produce exactly the same number value. So how far is the average still okay? 100 measurements are plugged into mathematical formulas to calculate "standard deviation," statistics that are widely used are related to how widely the numbers are spread apart. Further separated numbers produce larger standard deviations, while numbers closer together produce smaller standard deviations.
The next step is to decide how many standard deviations above and below the average must be accepted as normal. The typical choice for a blood test is two standard deviations in both directions. It is known that measurements in the range of two standard deviations above and below the average will include, on average, 95% of healthy people. This would also exclude or label the seemingly abnormal 5% of other healthy volunteers. So if the "normal range" is produced this way, one thing we already know is that it will be wrong 5% of the time.
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