This manuscript describes the variability of complete blood count (CBC) results in a fingerstick capillary sample. It was an initial pilot study, but the results have ramifications for the reliability of point-of-care testing devices that use capillary blood samples. Although the paper only looked at CBC and hemoglobin, anything that provides a quantitative value – glucose meters, coagulation devices, serology, disease markers and more – can be tested by fingerstick, so all of these tests may be subject to the variability the authors observed. It’s been known for some time that glucose meters often give different results with capillary samples than with venous samples. But even between capillary samples, there’s variation. Some of this is due to operator technique; people who squeeze the finger to get enough blood for the device end up contaminating the sample with interstitial fluid and other non-blood substances. It’s even more of a problem when you are sampling for coagulation tests or other devices. But I think this paper is interesting because it looks at standard blood samples by fingerstick – no difficult draws or unusual sampling methods – and determines that there is variability even within a single drop of blood. As a pilot analysis, it’s quite in-depth. The authors looked at multiple samples from 11 different donors. In practice, though, I wouldn’t recommend the use of multiple fingerstick collection from the same patient – it increases the time and expense of testing. It’s useful for method validations – examining the variability we see with a particular sample type and looking at reproducibility with different patients and operators. Part of the advantage of point-of-care testing is its speed, and the ability to take action on the spot. If you have to run three tests from three different fingersticks on same patient, wait for the results, and then average them, you delay the intervention.
A possible limitation of the paper is that the authors needed to dilute the samples, because they weren’t able to collect sufficient amounts of blood for cell counts on a larger automated hematology analyzer. That dilution step could add variability to the test results. To mitigate its effects, the authors also used a HemoCue device to analyze hemoglobin. This analyzer only requires 5 μL of sample, so there’s no need for dilution, and it showed similar variability to the larger hematology analyzer in different portions of the fingerstick blood samples. I don’t think there’s any way of overcoming the issue of variability while maintaining small sample sizes – but I also don’t think we should stop taking small samples. It doesn’t preclude the use of capillary sample tests; it’s just something we should be aware of as we perform the tests, like any other limitation or source of variation. We’ll consider it as we educate our operators, too; we have nearly 6,000 operators doing glucose testing, and we’ll want them to be aware of their sampling technique and try to minimize variation.
It will be interesting to see if similar variability is seen in portions of a blood drop for other common point-of-care tests, like glucose, hemoglobin A1c, coagulation or chemistries (like sodium, potassium, creatinine and even cardiac markers). As technologies become more sensitive – using smaller and smaller sample sizes to detect increasingly minor changes – I expect that variability will be a continuing problem. It’s a good opportunity for engineers and designers to collaborate with the end-users of the instruments to figure out ways to minimize its effect. In the future, we might even find that certain technologies are more prone to these effects than others, on the basis of sample volume or sampling technique. That may help us to steer more towards those technologies that are less dependent on variability within the drop.
Variations on a Drop by James Nichols
A Paper to Circulate by Ian Cree
Hyperspectral Disease Diagnosis by Peter Griffiths
Diagnosis: Digital by Liron Pantanowitz
Collagen and the Colon by Miguel Reyes-Múgica
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