analytical interferences and physiological limitations of blood glucose meters ken ervin

Analytical Interferences and Physiological Limitations of Blood Glucose Meters

Ken Ervin

03162010 Ken Ervin Consulting Services

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

Ken Ervin

So, just how do BGM systems using basically the same measurement tecchnology differ from laboratory methods?


Package inserts address “Procedural limitations” Sample related

e.g. Hct, pO2, DKA, HHNK, etc.

Endogenous compounds Exogenous compounds Environmental

Temperature Humidity Altitude


The limitations of a product are dependent upon the choice of technology to achieve the design goals.


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


To meet the specifications, technologies are chosen for the measurement device and its method of production


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


Interferences and physiological limitations are related to choices of sample type and technology


Interferences result from

Analyte specificity issues or Sample and environmental influences on the

measurement reaction


Analyte specificity

Use of enzymes specific for glucose GO GDH Hexokinase/G6PDH


Sample influences on measurement Endogenous substances

Uric acid Bilirubin Lipemia, Hemolysis

Exogenous substances Acetominophen Ascorbate Maltose, Icodextrin metabolites Mannitol Dopamine


Sample influences

DKA, HHNK pH and/or Viscosity

Hyperosmolar, flow effects Less water volume to reconstitute reagent


Environmental influences

Analytical Variability Temperature Humidity Altitude (i.e. oxygen availability)


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


Some relevant examples

How a pO2 dependence became a maltose interference

Hematocrit effects


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)


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


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


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.


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.

Ken Ervin

especially in a hospital situation

Ken Ervin

insert hematocrit graph


Hematocrit dependence

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Hematocrit effect

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Physiological effect

Little method effect

Greater method effect


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?

Ken Ervin

more important in diffusion based systems and short time frames


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.

analytical interferences and physiological limitations of blood glucose meters ken ervin

Documents

technology slide

reagent slide

measurement reaction

method of production

gdh hexokinaseg6pdh

hematocrit effect slide

oxygen availability

procedural limitations