analytical interferences and physiological limitations of blood glucose meters ken ervin
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Analytical Interferences and Physiological Limitations of Blood Glucose Meters
Ken Ervin
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Published information
Package inserts Review articles (partial list)
Boren and Clarke Tonyushkina and Nichols Pitkin and Rice Montagnana et al Wahl Dungan Arabadjief and Nichols Heller and Feldman
Specific articles (partial list) Kimberly, et al Fiore and Delanghe Lyon, et al Kazmierczak and Catrou Goudable, et al Zheng, et al Vesper, et al Katelijne and Delanghe Tang, et al
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Package inserts address “Procedural limitations” Sample related
e.g. Hct, pO2, DKA, HHNK, etc.
Endogenous compounds Exogenous compounds Environmental
Temperature Humidity Altitude
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The limitations of a product are dependent upon the choice of technology to achieve the design goals.
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BGM Design GoalsDrive the specifications and choice of technology Accurate and precise Highly specific *Stable at room temperature *Rapid test (use whole
blood directly) *Very easy to use Small blood volume
*Inexpensive meter *Cal code strategy Low cost/test More recently
No pO2 dependence No maltose interference No hematocrit effect
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To meet the specifications, technologies are chosen for the measurement device and its method of production
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BGM measurement based on combining technologies Method of introducing sample to device
Most devices now rely on capillary action, sometimes in two directions
Method to identify glucose in sample (specificity) Enzymatic reaction (GO, GDH, Hexokinase/G6PDH)
Method to quantify glucose Colorimetric Electrochemical
Method of calibration Methods to assess performance of the test or correct
results
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Interferences and physiological limitations are related to choices of sample type and technology
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Interferences result from
Analyte specificity issues or Sample and environmental influences on the
measurement reaction
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Analyte specificity
Use of enzymes specific for glucose GO GDH Hexokinase/G6PDH
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Sample influences on measurement Endogenous substances
Uric acid Bilirubin Lipemia, Hemolysis
Exogenous substances Acetominophen Ascorbate Maltose, Icodextrin metabolites Mannitol Dopamine
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Sample influences
DKA, HHNK pH and/or Viscosity
Hyperosmolar, flow effects Less water volume to reconstitute reagent
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Environmental influences
Analytical Variability Temperature Humidity Altitude (i.e. oxygen availability)
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Physiological limitations
Sample choice Capillary, venous, or arterial
Actual concentrations are different and relationship may vary If capillary; hypotension, perfusion and other conditions such
as Reynaud’s syndrome disturb normal relationship Alternate site time lag pO2 differences
Hematocrit Smaller sample sizes increase the potential for
residue to influence results
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Some relevant examples
How a pO2 dependence became a maltose interference
Hematocrit effects
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The pO2 effect
glucose + O2 + H2O gluconic acid + H2O2 GO
glucose + med (ox) gluconolactone + med (red)GO
H2O2 + dye precursor dye color + H20HRPO
(colorimetric)
(electrochemical)
med (red) e- + med (ox)Epot
(YSI and Beckman Glucose Analyzer)
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How a pO2 interference became a maltose interference Original methods based on glucose oxidase coupled
to a colorimetric indicator system. Oxygen available from atmosphere
blood removed by blotting, wiping etc. exposed to air during the reaction time
Electrochemical methods used mediators Systems calibrated for capillary blood
Oxygen would interfere competitively Use of venous or arterial blood exacerbated this competition
Venous reads higher; less 02 competition Arterial reads lower; more 02 competition
pO2 effects generally greater at lower glucose concentrations
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How a pO2 interference became a maltose interference Second Generation products
GO Open to atmospheric oxygen Oxygen blocked by windows or capillary design
Hexokinase/G6PDH
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How a pO2 interference became a maltose interference GDH-PQQ systems introduced to alleviate pO2
GDH reaction does not involve oxygen RT stable enzyme
However, GDH-PQQ less specific for glucose Recognizes maltose, galactose, xylose and other sugars
with glucose moiety, with false elevation of glucose results. Recent versions of GDH with NAD or FAD cofactor
are more specific and stable.
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Hematocrit effects
For a rapid test, WB is preferable if not necessary Most systems now report “plasma equivalent” Systems are calibrated at normal hematocrit. WB sample hematocrits may vary significantly (~15 to >70) Glucose content of whole blood as compared to plasma is inversely related
with hematocrit.
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Hematocrit dependence
0
10
20
30
40
50
60
70
80
90
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
East
West
North
Hematocrit effect
-40
-30
-20
-10
0
10
20
30
40
0 20 40 60 80
Hematocrit
Bia
s t
o p
lasm
a (
%)
Physiological effect
Little method effect
Greater method effect
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Hematocrit effects
Hematocrit may influence access of plasma or diffusion of glucose to measurement system suppressing results.
Hematocrit effects generally greater at higher glucose concentrations
Hematocrit can be measured and corrected for Greater imprecision?
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In Conclusion
Limitations and interferences are related to the particular technologies chosen.
The unique goals of a BGM system make it unlikely they will ever completely match a lab based system.
The evolution of BGM devices is a demonstration of achieving a balance between a high degree of performance with a rapid, more versatile, easy to use system.
Using a WB sample and reporting plasma (unless corrected for) introduces a ± 6% error in the range 25-65 hct.
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