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Few experiences are more frustrating for a patient than receiving "normal" blood test results when they're feeling unwell. They've already spent time and money seeking out a solution, only to be told there isn't even a problem. Often, they're made to feel as if they're overreacting or exaggerating their symptoms and sent on their way.
In no small part, this all-too-common experience is caused by our flawed approach towards analyzing blood test results. Many medical professionals mistake “normal” blood biomarker levels as actually corresponding with healthy or optimal biomarker levels. It’s a common misconception because normal does not mean optimal.
In fact, there is a huge range of dysfunctions that wouldn’t necessarily result in an abnormal blood test reading, even though they can significantly affect a patient’s quality of life and potentially worsen into disease if left unassessed. We often see patients with unremarkable blood test results complaining of the following conditions:
While many of these dysfunctions won’t affect biomarker levels to the extent that they’ll read as high or low on a blood test, there are changes and patterns in blood biomarker levels associated with them.
By merely scanning a patient’s blood test results for biomarkers that clearly fall out of the normal range, medical practitioners are leaving potentially valuable clinical information on the table. In order to identify and treat these dysfunctions before they become disease, we need to analyze blood test results with a keener eye.
When conducting a blood test, labs compare the sample’s blood biomarker levels to what’s known as the reference range. Ninety-five percent of the population is meant to fall within this range of values for any given blood biomarker. Thus, if your patients’ blood biomarkers fall within this range, your results are considered normal.
To calculate the reference range, labs take blood from a representative sample of the population, measure the levels of each blood biomarker, and generate a bell curve from the results. Then, they find the points that lie two standard deviations away from the peak (i.e., the mean) of the bell curve — this captures 95% of the population and is defined as normal. The upper 2.5% and lower 2.5% represent abnormal blood test results.
Now that we understand how these ranges are calculated, we can see that there are a few clear problems with using reference ranges to determine whether a patient is healthy or not.
First, the original sample used to create the reference range may not be representative of the general population or — more importantly — may not be representative of optimally healthy individuals. Consider the facts that the American obesity rate has increased from 23 to 42.4 percent since it was first measured in 1962, testosterone levels have been steadily decreasing in men for the last few decades and 42 percent of Americans suffer from vitamin D insufficiency or deficiency.
In many respects, it is normal to be overweight, suffering from low testosterone, and deficient in vitamin D. But no medical professional would ever argue that it is healthy.
What’s more, due to variations in testing equipment, chemical reagents, statistical techniques, and patient samples, each individual lab calculates its own reference range. As a result, a patient could register as normal on one lab’s blood test analysis and abnormal on another’s. This isn’t to state that there is no value in measuring blood biomarker levels — merely that basing an assessment of optimal health solely off of whether those values fall within the normal range isn’t reliable.
However, these flaws have more of an impact on the allopathic, disease-focused approach to medicine. When diagnoses and treatment plans depend on whether blood test biomarkers are high or low compared to the reference range, patients can present unhealthy but “normal” blood test results for months or even years and only receive treatment once their dysfunction has evolved into disease.
That’s why Functional Medicine practitioners use far tighter ranges when analyzing their patients’ blood test results and measure blood biomarkers over time to catch trends towards optimal health or away from it. By observing which biomarkers appear elevated relative to their optimal range — as opposed to their normal reference range — we can help treat the dysfunctions listed previously.
First, however, we need to build an understanding of where the functional ranges for the different blood biomarkers lie and what changes in their levels can signify. We’ve put together a reference guide that Functional Medicine practitioners can use to begin viewing blood test analysis from a functional perspective called “Stay Optimal: An Insider’s Guide to Your Patients’ Blood Biomarkers.”
Just because blood test results are so often misused to write off patients’ medical concerns doesn’t mean that they can’t be used to drive better health outcomes. In fact, with the right analytical approach, a blood test can be the Functional Medicine practitioner’s greatest tool in improving their patients’ health.