Slope-Based Compensation

• US 20090177406A1
• Filed: 12/08/2008
• Published: 07/09/2009
• Est. Priority Date: 12/10/2007
• Status: Active Grant

• Current Assignee: Ascensia Diabetes Care Holdings AG (PHC Holdings Corporation)
• Original Assignee: Bayer Healthcare LLC (Bayer AG)
• Inventors: WU, Huan-Ping
• Granted Patent: US 10,739,350 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: G01N 27/3273 Devices therefor, e.g. test element readers, circuitry details not specific to biochemical electrodes G01N33/4875
• CPC Class Codes: G01N 33/66 involving blood sugars, e.g. galactose

Abstract

A biosensor system determines analyte concentration from an output signal generated from a light-identifiable species or a redox reaction of the analyte. The biosensor system adjusts a correlation for determining analyte concentrations from output signals with one or more index functions extracted from the output signals. The index functions determine at least one slope deviation value, ΔS, or normalized slope deviation from one or more error parameters. The slope-adjusted correlation between analyte concentrations and output signals may be used to determine analyte concentrations having improved accuracy and/or precision from output signals including components attributable to bias.

Claims

1. A method for determining an analyte concentration in a sample, comprising:

generating at least one output signal value responsive to the concentration of the analyte in the sample;

determining at least one Δ

S value from at least one error parameter;

compensating the at least one output signal value with at least one reference correlation and at least one Δ

S value; and

determining the analyte concentration in the sample from the at least one output signal value.

2. The method of claim 1, where the sample is a biological fluid.

3. The method of claim 1, where the analyte comprises glucose and the sample comprises whole blood.

4. The method of claim 1, where the percent bias in the determined analyte concentration is at most ±

10%.

5. The method of claim 1, where over 95% of the analyses determined from the method fall within a ±

20% bias limit.

6. The method of claim 1, where percent bias in the determined analyte concentration is in a substantially linear relationship with Δ

S.

7. The method of claim 1, where the determining of the at least one Δ

S value from the at least one error parameter and at least one index function.

8. The method of claim 7, where the error parameter is responsive to error contributors causing an alteration of the at least one output signal value.

9. The method of claim 7, where the at least one error parameter is selected from the group consisting of temperature, hematocrit, and combinations thereof.

10. The method of claim 7, where the error parameters are independently responsive to different error contributors.

11. The method of claim 7, where the error parameter has an R² correlation with Δ

S_cal of at least 0.3.

12. The method of claim 7, where the at least one index function transforms the at least one error parameter into the at least one Δ

S value.

13. The method of claim 1, where the output signal value is generated in response to an input signal comprising pulsed electrical excitations.

14. The method of claim 1, where the output signal value is generated from light.

15. The method of claim 1, where the at least one reference correlation is pre-determined with a reference instrument.

16. The method of claim 1, where the compensating is represented as follows:

$A_{\mathrm{corr}}=\frac{i-\mathrm{Int}}{S_{\mathrm{cal}}+\mathrm{\Delta <br><br>}<br><br><br><br>S}$

where A_corr is the determined analyte concentration, i is the at least one output signal value responsive to the concentration of the analyte in the sample, Int is the intercept from the reference correlation, S_cal is the slope from the reference correlation, and Δ

S is the at least one Δ

S value.

17. The method of claim 16, where the at least one Δ

S value represents the difference in slope between the slope from the reference correlation and a hypothetical slope of a line for the output signal value that would provide the analyte concentration of the sample without bias.

18. The method of claim 1, where the at least one reference correlation and the at least one output signal value are modified with a second Δ

S value, each Δ

S value determined from a different index function.

19. The method of claim 18, where different error parameters are transformed by the different index functions to provide the at least two Δ

S values.

20. The method of claim 19, where correlation between analyte concentration and the different error parameters is represented as follows:

$A_{\mathrm{corr}<br><br>\left(2\right)}=\frac{i-\mathrm{Int}}{S_{\mathrm{cal}}+\mathrm{\Delta <br><br>}<br><br><br><br>S_1+\mathrm{\Delta <br><br>}<br><br><br><br>S_2}$

where A_corr(2) is the analyte concentration corrected with two Δ

S values and Δ

S₁ and Δ

S₂ are the at least two Δ

S values.

21. The method of claim 19, were Δ

S₁ represents the error parameter responsive to the error contributor providing the largest bias in the determined analyte concentration.

22. The method of claim 19, were Δ

S₂ is represented as follows;

$\mathrm{\Delta <br><br>}<br><br><br><br>S_{2<br><br><br><br>\mathrm{cal}}=S_{\mathrm{cal}}*\left(\frac{{A_{\mathrm{corr}}}_{\left(1\right)}}{A_{\mathrm{ref}}}-1\right),$

where Δ

S₂ is slope deviation remaining after a first f(Index) compensation and represents the difference in slope between S_cal and S_hyp for a second error parameter after the first compensation, S_cal is the slope from the reference correlation, A_corr(1) is the analyte concentration corrected with the first f(Index), and A_ref is the reference analyte concentration of the sample.

23. The method of claim 1, where the compensating is with an equation relating percent bias to current.

24. The method of claim 1, where the sample is selected from the group consisting of a biological fluid, a derivative of a biological fluid, and combinations thereof.

25. The method of claim 1, where the determining is performed by a portable measurement device.

26. The method of claim 1, further comprising normalizing the at least one Δ

S value.

27. The method of claim 26, further comprising normalizing the at least one Δ

S value in response to a slope of a reference correlation equation.

28. The method of claim 26, further comprising normalizing the at least one Δ

S value in response to a normalized slope function.

29. A method for determining index functions from error parameters, comprising:

determining at least one error parameter responsive to the percent bias in a determined analyte concentration in a sample;

determining at least one Δ

S_cal value from a reference correlation, a reference concentration of an analyte in a sample, and an output signal; and

relating the at least one error parameter to the least one Δ

S_cal value with at least one index function.

30-36. -36. (canceled)

37. A biosensor system, for determining an analyte concentration in a sample, comprising:

a sensor strip having a sample interface adjacent to a reservoir formed by the strip; and

a measurement device having a processor connected to a sensor interface, the sensor interface having electrical communication with the sample interface, and the processor having electrical communication with a storage medium,

where the processor determines an output signal value responsive to the concentration of the analyte in the sample from the sensor interface,

where the processor determines at least one Δ

S value from an error parameter, and

where the processor compensates the output signal value with the at least one Δ

S value and at least one reference correlation present in the storage medium.

38-43. -43. (canceled)

44. A sensor strip, for a biosensor system for determining the analyte concentration of a sample, the strip arranged and configured to have a substantially linear relationship between the percent bias in a determined analyte concentration and Δ

S.

45. (canceled)

46. A method for determining an analyte concentration in a sample, comprising:

generating at least one output signal from a sample;

determining at least one index function, where the at least one index function is responsive to at least one error parameter; and

determining the analyte concentration in the sample from the at least one output signal responsive to the at least one index function.

47-63. -63. (canceled)

64. A method for determining an analyte concentration in a sample, comprising:

applying at least one potential sequence to the sample;

recording at least one output signal from the sample;

determining at least one index function; and

determining the analyte concentration in the sample from the at least one output signal responsive to the at least one index function.

65-82. -82. (canceled)