In the first post of the Greyledge Blog, I introduced the Blog, Greyledge Technologies and my recent shift in employment. I had left off with describing aspects of the service Greyledge provides to physicians who wish to have tighter control over the composition of autologous PRP and BMC preparations for use in a physician’s practice of regenerative medicine.

Analysis of autologous patient samples produced in the Greyledge system offers physicians a chance to see what levels of important constituents like Platelets, RBCs, WBCs, and so on are present in the preparation. Here is a list of 14 absolute value parameters that are analyzed for each sample:

RBC – Red Blood Cell – Cells responsible for the transport of oxygen and carbon dioxide

HGB – Hemoglobin – The oxygen-carrying pigment and predominant protein in the red blood cells.

HCT – Hematocrit – The percentage of the volume of whole blood that is made up of red blood cells.

MCV – Mean Corpuscular Volume – A measure of the mean red blood cell volume.

MCHC – Mean Corpuscular Hemoglobin Concentration – The average concentration of hemoglobin in a given volume of blood

RDW – Red Blood Cell Distribution Width – is a measure of the variation of red blood cell width

PLT – Platelet – Colorless bodies that are present in blood and responsible for clot formation.

MPV – Mean Platelet Volume – Machine-calculated measurement of the average platelet size

WBC – White Blood Cell – Or leukocytes, are cells of the immune system defending the body against both infectious disease and foreign materials

NEU – Neutrophil – Also known as a granulocyte, which is the chief phagocytic white blood cell of the blood

LYM – Lymphocyte – Any of the colorless weakly motile white blood cells differentiating in lymphoid tissue

MONO – Monocyte – A large white blood cell which differentiates into a macrophage

EOS – Eosinophil – A white blood cell or other granulocyte with cytoplasmic inclusions readily stained by eosin

BASO – Basophil – a white blood cell with basophilic granules that is similar in function to a mast cell

The Neu/Lym/Mono/EOS/BOS set of cell determinations is known as a “diff”, which stands for a differential analysis of the larger category of white blood cells (WBC). There are another 13 parameters included in Greyledge’s sample analysis, which involve a percentage determination. For example, you not only know how many MONOs you have in the PRP sample, but what percentage the MONOs are within the “diff” set of nucleated cells.

So, Greyledge provides a physician with a lot of data, but how might a physician take advantage of the data? The most obvious use would be for the physician to record values from the patient’s sample analysis in a spreadsheet and subsequently enter in demographic and outcomes data. For example, the physician might enter results of outcomes assessments obtained during follow-up visits that are routinely used to monitor the patient’s recovery. Typically, a metric for pain might be employed and the results entered into the spreadsheet. By applying this strategy to all patients being seen at a clinic, the clinical staff could build an internal database that might inform them about optimization strategies for treating their patients.

As indicated above, Greyledge’s approach to characterizing autologous therapeutic samples generated at POC involves a 27-parameter analysis on a hemoanalyzer performed just prior to providing the sample itself to the physician, which lets the physician examine the results and either modify the preparation or proceed with the treatment. Consequently, Greyledge offers physicians a timely opportunity to make adjustments, as well as an opportunity to record the data in a spreadsheet they can create and maintain.

Why go to the trouble, you might be asking yourself? My counter argument is that having a detailed knowledge of what you are injecting into your patients puts you in a position to refine your practice of regenerative medicine. And that is a good thing, since your patients ultimately will benefit from your optimizing the use of autologous materials like PRP and BMC.

To illustrate how knowledge of what is in the PRP and BMC preps you use can inform your practice of medicine, I refer you to a publication by Riboh, et al. (2016)(opens in a new tab). The authors performed a meta-analysis of publications in which PRP preparations were used to treat knee osteoarthritis (OA). They conducted a very thorough vetting of the clinical studies included in their paper. The primary question they addressed concerned any differences in the use of a leukocyte-poor (LP-) versus a leukocyte-rich (LR-) PRP preparation. The short answer is that there is a modest improvement in the outcome if you treat knee OA with LP-PRP compared to LR-PRP, but only if you use the WOMAC metric assessment for knee health.

So, the result is kind of like kissing your cousin—underwhelming. But if you read about the methodology used to assign a study to the LP or LR category you will begin to appreciate why the conclusion is, well, like kissing your cousin. To quote:

“LR-PRP was defined as PRP having a WBC concentration greater than 100% that of whole blood. Conversely, LP-PRP was defined as PRP having a WBC concentration less than 100% of whole blood.”

The authors did their best to sort out the type of PRP being used in each clinical study, but, unfortunately, a number of authors failed to count the WBCs.

What is the lesson you, as a physician, should learn? Clearly, if all of the clinical studies cited in Riboh et al. (2016) had contained explicit WBC values, it might have been easier to distinguish the therapeutic potential of LP- compared to LR-PRP preparations. Instead, the authors had a binary choice—above or below 100% WBCs in whole blood—while patient response to a treatment could be all over the place. Without the individual WBC values, there is no way to plot patient response versus their WBCs.

In the Greyledge paradigm, a physician not only would know how many WBCs remained in a patient’s PRP, for example, but could request that the WBCs be depleted during processing. So, knowing in detail what’s in the preps might lead to a refinement in a physician’s practice of regenerative medicine. And you don’t have to wait for someone else to publish a clinical study, since you can track outcomes and do the plots yourself.  Neat, huh?