Method, device and system for adjusting test HbA1c values

Abstract

Physiological parameters related to the dynamics of red blood cell hemoglobin glycation, red blood cell removal, and red blood cell generation in a subject's body can be used, for example, to calculate more reliable calculated HbA1c (cHbA1c), adjusted HbA1c (aHbA1c), and / or personalized target glucose ranges for subject-personalized diagnostic, therapeutic, and / or monitoring protocols, among others. Such physiological parameters can be determined using models that consider transmembrane glucose transport and glycation.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application No. 62 / 939,970, filed November 25, 2019, U.S. Provisional Patent Application No. 63 / 015,044, filed April 24, 2020, and U.S. Provisional Patent Application No. 63 / 081,599, filed September 22, 2020.

[0002] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT Not applicable [Background technology]

[0003] Measurement of various analytes in an individual can sometimes be essential to monitoring their health. During the normal circulation of red blood cells in mammals, such as humans, glucose molecules attach to hemoglobin, which is called glycosylated hemoglobin (also called glycated hemoglobin). The higher the amount of glucose in the blood, the higher the percentage of circulating hemoglobin molecules that have glucose molecules attached. Because glucose molecules remain attached to hemoglobin for the lifespan of a red blood cell (usually about 120 days), the level of glycosylated hemoglobin reflects the average blood glucose level over that period.

[0004] Most hemoglobin is of a type called HbA. When a glucose molecule attaches to an HbA molecule, glycosylated HbA, called HbA1, is formed. HbA1 has three components: HbA1a, HbA1b, and HbA1c. Because glucose binds more strongly and to a greater extent to HbA1c than to HbA1a and HbA1b, a measurement of blood HbA1c (HbA1c test) is often used as an indication of a subject's average blood glucose level over a 120-day period (the average lifespan of a red blood cell). HbA1c tests are performed by drawing a blood sample from the subject in the doctor's office, which is then analyzed in a laboratory. HbA1c tests may be used as a screening and diagnostic test for prediabetes and diabetes. A subject's glucose exposure, as determined by HbA1c levels, is one of the key factors used in diagnostic and / or therapeutic decisions. That is, normal or healthy glucose exposure is correlated to an HbA1c level or range, assuming a 120-day red blood cell lifespan, and a subject's test HbA1c level (also referred to in the art as measured HbA1c) is compared to this normal or healthy range when diagnosing and / or treating the subject. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] U.S. Patent Application No. 2018 / 0235524 [Patent Document 2] U.S. Provisional Patent Application No. 62 / 750,957 [Patent Document 3] U.S. Provisional Patent Application No. 62 / 939,956 [Patent Document 4] U.S. Patent No. 6,175,752 [Patent Document 5] U.S. Patent Application No. 2011 / 0213225 [Patent Document 6] U.S. Patent Application No. 2014 / 0188400 [Patent Document 7] U.S. Patent Application No. 2014 / 0350369 [Patent Document 8] U.S. Patent Application No. 2008 / 0009692 [Patent Document 9] U.S. Patent Application No. 2011 / 0319729 [Patent Document 10] U.S. Patent Application No. 2015 / 0018639 [Patent Document 11] U.S. Patent Application No. 2015 / 0025345 [Patent Document 12] U.S. Patent Application No. 2015 / 0173661 [Patent Document 13] U.S. Patent Application No. 2011 / 0193704 [Non-patent literature]

[0006] [Non-Patent Document 1] "Glucose management indicator (GMI): A new term for estimating A1C from continuous glucose monitoring," Diabetes 41(11) pp. 2275-2280, November 2018 [Non-patent document 2] "Translating the A1C assay into estimated average glucose values," Diabetes Care 31(8) pp. 1473-1478, August 2008, PMID: 18540046 [Non-patent document 3] "Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring," Sci.Transl.Med.8, 359ra130, October 2016 [Non-patent document 4] Xu Y, Dunn TC, Ajjan RA. "A kinetic model for glucose levels and hemoglobin A1C provides a novel tool for individualized diabetes management." J Diab Sci Tech. 2020, DOI: 10.1177 / 1932296819897613 Summary of the Invention [Problem to be solved by the invention]

[0007] However, although red blood cell lifespan does not vary to a large extent within a subject (except in some subjects with certain diseases), the red blood cell lifespan for an individual subject can be between about 50 days and about 170 days. Thus, testing HbA1c levels for subjects with longer red blood cell lifespans will overestimate glucose exposure and underestimate glucose exposure for subjects with shorter red blood cell lifespans. Thus, diagnosis and treatment (and even when treatment should be administered) are based on inaccurate glucose exposure.

[0008] The following figures are included to illustrate certain aspects of the present disclosure and should not be construed as exclusive embodiments. The disclosed subject matter is capable of considerable modification, alteration, combination, and equivalents in form and function without departing from the scope of this disclosure. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 shows that individual RBC life span can affect HbA1c and diabetes treatment, such that 31% of tested HbA1c were erroneous in this study, potentially leading to under- or over-treatment. [Figure 2] FIG. 1 shows an exemplary time series illustrating a collection of at least one HbA1c value and multiple glucose levels over a period of time. [Figure 3] FIG. 1 illustrates an example of a physiological parameter analysis system for providing physiological parameter analysis in accordance with some embodiments of the present disclosure. [Figure 4] FIG. 1 illustrates an example of a physiological parameter analysis system for providing physiological parameter analysis in accordance with some embodiments of the present disclosure. [Figure 5] FIG. 10 illustrates an example of a cHbA1c report that may be generated as an output by a physiological parameter analysis system according to some embodiments of the present disclosure. [Figure 6A] FIG. 1 illustrates an example method for determining a personalized target glucose range according to some embodiments of the present disclosure. [Figure 6B] FIG. 10 illustrates an example of a personalized target glucose range report that may be generated as an output by a physiological parameter analysis system according to some embodiments of the present disclosure. [Figure 7] FIG. 10 illustrates an example of a personalized-target average glucose report that may be generated as an output by a physiological parameter analysis system according to some embodiments of the present disclosure. [Figure 8] FIG. 10 illustrates an example of a glucose pattern insight report that may be generated as an output by a physiological parameter analysis system according to some embodiments of the present disclosure. [Figure 9] FIG. 1 illustrates an example of an in-vivo analyte monitor system according to some embodiments of the present disclosure. [Figure 10]FIG. 1 is a plot of glucose monitor data (right y-axis), three HbA1c values ​​(left y-axis), and estimated HbA1c values ​​(left y-axis) based on a 14-day eHbA1c model over 200 days. [Figure 11] FIG. 11 is a plot of FIG. 10 with cHbA1c (left y-axis) over the first 100 days determined using kgly and kage according to the methods described herein. [Figure 12] 12 is a plot of FIG. 11 with cHbA1c over the next 100 days (extension from day 100 to day 200, left y-axis) using kgly and kage determined in relation to FIG. 10 by the method described herein. [Figure 13A] FIG. 10 shows a cross-plot comparison of predicted HbA1c levels (by 14-day glucose model) compared to test HbA1c levels. [Figure 13B] FIG. 1 shows a cross-plot comparison of cHbA1c levels (by the methods described herein) compared to laboratory HbA1c levels. [Figure 14] FIG. 1 is a plot of test HbA1c compared to aHbA1c ("aA1C") by RBC lifetime. [Figure 15] This is a plot showing the distribution of RBC lifespan and the adjustment of test HbA1c by RBC lifespan for type 1 (n=51) and type 2 (N=80) diabetes, where the majority of subjects (69%) in this study belonged to the average RBC lifespan bin. [Figure 16A] FIG. 11 shows cross-plots and correlations of mean 14-day intracellular glucose (I)G values ​​with adjusted aHbA1c. [Figure 16B] FIG. 1 is a cross-plot of originally collected data of 14-day mean plasma glucose (PG) and test HbA1c. [Figure 17A] FIG. 10 shows an example of a glucose pattern insight report for the same subject using measurement PG. [Figure 17B] FIG. 10 shows an example of a glucose pattern insight report for the same subject using PGeff. DETAILED DESCRIPTION OF THE INVENTION

[0010] The present disclosure generally describes methods, devices, and systems for determining dynamic physiological parameters of red blood cell glycation, clearance, and generation within a subject's body. Such physiological parameters can be used, for example, to calculate, among other things, more reliable calculated HbA1c (cHbA1c), adjusted HbA1c (aHbA1c), and / or personalized target glucose ranges for subject-personalized diagnostic, therapeutic, and / or monitoring protocols.

[0011] The terms "HbA1c level," "HbA1c value," and "HbA1c" are used interchangeably herein. The terms "aHbA1c level," "aHbA1c value," and "aHbA1c" are used interchangeably herein. The terms "cHbA1c level," "cHbA1c value," and "cHbA1c" are used interchangeably herein.

[0012] Dynamic Model High glucose exposure in certain organs (especially the eyes, kidneys, and nerves) is a risk factor for the development of diabetic complications. Testing HbA1c (also referred to in the art as measured HbA1c) is routinely used to assess glycemic control, but studies have reported discrepancies between this glycemic marker and diabetic complications in some individuals. The exact mechanism by which testing HbA1c fails to predict diabetic complications is often unclear but is likely related to inaccurate estimation of intracellular glucose exposure in affected organs in some cases.

[0013] Equation 1 kinetically illustrates red blood cell hemoglobin glycation (or simply referred to herein as red blood cell glycation), red blood cell clearance, and red blood cell production, where "G" is free glucose, "R" is unglycated red blood cells, and "GR" is glycated red blood cell hemoglobin. The rate at which glycated red blood cell hemoglobin (GR) is formed is referred to herein as the red blood cell hemoglobin glycation rate constant (typically dL * mg -1* day -1k has units of gly ) is called chemical formula 1 [ka]

[0014] Over time, red blood cell hemoglobin, including glycated red blood cell hemoglobin, is continually removed from the subject's circulatory system, and new red blood cells containing hemoglobin are generated, typically at a rate of about 2 million per second. The rates of removal and generation are each referred to herein as the red blood cell removal constant (typically 0.1%). -1 k has units of age ) and the erythrocyte development rate constant (typically M 2 k with units of / day gen ) The amount of red blood cells in the body is maintained at a stable level most of the time, so k age and k gen The ratio of can be a discrete constant that is the square of the red blood cell concentration.

[0015] Regarding glycation, Equation 2 illustrates this mechanism in more detail, where glucose transporter 1 (GLUT1) facilitates the transport of glucose (G) into red blood cells. Intracellular glucose (G) then interacts with hemoglobin (Hb) to produce glycated hemoglobin (HbG), where the hemoglobin glycation reaction rate constant is k g (typically dL * mg -1* day -1 A typical experimental measurement is k g The value is 1.2x10 -3 dL / mg / day. Hemoglobin glycation is a non-enzymatic chemical reaction, therefore, k g can be considered a universal constant. The rate constant for transporting glucose into red blood cells and glycating Hb to HbG is k gly Furthermore, k age represents red blood cell removal (together with hemoglobin), also referred to herein as red blood cell turnover rate. chemical formula 2 [ka]

[0016] While high intracellular glucose concentrations are the cause of diabetic complications, extracellular hyperglycemia selectively damages cells with limited ability to effectively regulate transmembrane glucose transport. HbA1c is used as a biomarker for diabetes-related intracellular hyperglycemia for two main reasons. First, glycation occurs within red blood cells (RBCs), and therefore HbA1c is modified by intracellular glucose levels. Second, RBCs lack the ability to regulate the level of the glucose transporter GLUT1 and therefore cannot modulate the transmembrane glucose absorption rate, behaving similarly to cells selectively damaged by extracellular hyperglycemia. Therefore, under conditions of fixed RBC lifespan and transmembrane glucose absorption rate, HbA1c faithfully reflects intracellular glucose exposure in organs affected by diabetic complications. However, considering interindividual variability in both transmembrane glucose absorption rate and RBC lifespan, test HbA1c may not always reflect intracellular glucose exposure. Although variations in RBC transmembrane glucose absorption rates are likely related to the estimated risk of diabetic complications in susceptible organs, red blood cell lifespan is specific to RBCs and therefore unrelated to complication risk in other tissues. This explains the inability to clinically base HbA1c testing in individuals with hematological disorders characterized by abnormal RBC turnover and represents a possible explanation for the apparent "discrepancy" between HbA1c testing and the development of complications in some individuals with diabetes (Figure 1).

[0017] To overcome the limitations of laboratory HbA1c, we developed a method for personalized HbA1c that takes into account individual variations in both RBC turnover and cellular glucose absorption rates. The current study aims to extend this model by adjusting for a standard RBC lifespan of 100 days (equivalent to a 1% RBC turnover rate per day or a mean RBC age of 50 days) to establish a new clinical marker called adjusted HbA1c (aHbA1c). We propose that aHbA1c is the most suitable glycemic marker for estimating organ exposure to hyperglycemia and the subsequent risk of diabetes-related complications. As mentioned above, HbA1c is a typically used analyte that indicates the fraction of glycated hemoglobin found in red blood cells. Therefore, for example, a dynamic model can be used to derive a calculated HbA1c based on at least the glucose levels measured for a subject. However, this dynamic model can also be applied to HbA1. For simplicity's sake, HbA1c will be used throughout this specification, but it is contemplated that HbA1 could be used instead, except in instances where a specific HbA1c value is used, in which case a similar formula could be derived using the specific HbA1 value.

[0018] Typically, when dynamically modeling a physiological process, assumptions are made to emphasize the factors that most affect the physiological process and to simplify some of the numerical calculations.

[0019] The present disclosure uses only the following set of assumptions to dynamically model the physiological processes exemplified in Equations 1 and 2: The following set of assumptions were made during model construction: 1. Absence of any abnormal red blood cells that may affect HbA1c measurement. 2. The widely accepted assumption is that the glycation process has a linear dependence on the concentrations of both hemoglobin and intracellular glucose in red blood cells. 3. Newly produced red blood cells contain only small amounts of glycosylated hemoglobin. 4. Red blood cells are removed from the circulation when a subject reaches a certain age. Individual red blood cell removal rates are approximated using constants. Thus, the glycated hemoglobin removal rate is proportional to the product of the total red blood cell removal rate and the HbA1c at that time.

[0020] Using these, the rate of change of glycated and non-glycated hemoglobin in red blood cells can be modeled by differential equations 1 and 2. formula 1 JPEG0007770316000003.jpg672 formula 2 JPEG0007770316000004.jpg695

[0021] [HbG] and [Hb] are the concentrations of glycated and unglycated hemoglobin, respectively, and [GI] is the intracellular glucose concentration. g is (concentration * time) -1 is the rate constant for hemoglobin glycation in units of . C is the total hemoglobin concentration, where C = [Hb] + [HbG]. HbA1c is the fraction of glycated hemoglobin molecules. r is the red blood cell clearance rate in units of concentration / time. α has no unit of measure and is a coefficient used to scale HbA1c for the fraction of glycated hemoglobin that is cleared. All concentrations can have units such as mmol / l or mg / dL. Time units are hours or days.

[0022] The glucose transporter (GLUT1) on the erythrocyte membrane follows Michaelis-Menten kinetics. M is the Michaelis constant for the affinity of an enzyme (e.g., GLUT1) for a substrate (e.g., glucose). M is experimentally determined. K for GLUT1-glucose interaction M Different values ​​for K range from about 100 mg / dL to about 700 mg / L. Two specific exemplary values ​​are 306 mg / dL (17 mM) and 472 mg / dL (26.2 mM). Unless otherwise specified, KM However, embodiments of the present disclosure may be modified to accommodate this particular K M That is, intracellular glucose is not limited to k c is the glucose consumption rate in red blood cells, d[GI] / dt=V max *[G] / (K M +[G])-k c *Modeled by [GI]. Maximum speed V max should be proportional to the GLUT1 level on the membrane. c and V max Both can vary independently. Under equilibrium, Equation 3 is derived. formula 3 JPEG0007770316000005.jpg1147Here, g=(K M *[G]) / (K M +[G]) and k c is the rate constant for glucose consumption in red blood cells (typically 1000 kJ / day) -1 ), V max is the maximum glucose transport rate (typically in mg * dL -1* day -1 (having units of 0.01), which should be proportional to the GLUT1 level on the membrane, and K M is the Michaelis-Menten kinetic rate constant for GLUT1 transporting glucose across the red blood cell membrane (typically with units of mM / dL or mg / dL).

[0023] By definition, HbA1c is the fraction of glycated hemoglobin found in red blood cells, i.e., HbA1c = [HbG] / C = (C - [Hb]) / C. At steady state, d[Hb] / dt = d[HbG] / dt = 0, and Equation 1 reduces to C*k g / (α*r)=[HbG] / ([GI][Hb]). Combining this with equation 3 yields equation 4: formula 4 TIFF0007770316000006.tif1139

[0024] By combining all the parameters for intermembrane glucose transport with the glycation rate constant from the right-hand side of Eq. 4, the complex glycation rate constant k gly =k g *V max / (k c *K M ) and k in this formula g and K. M are universal constants for non-enzymatic hemoglobin glycation and the affinity of glucose to GLUT1, respectively. Therefore, k gly are individually k c and V max The remaining parameters for red blood cell turnover are k age =α * Due to r / C, this equation leads to the definition of the apparent glycation parameter K in terms of Equation 5. formula 5 JPEG0007770316000007.jpg660

[0025] Under a hypothetical steady state of constant glucose level, HbA1c should reach an equilibrium level, which is "equilibrium HbA1c" (EA). Since C = [HbG] + [Hb], Equation 5 can be rewritten as K = (C - [Hb]) / (g * [Hb]). Applying the definition HbA1c = (C - [Hb]) / C yields Equation 6. formula 6 JPEG0007770316000008.jpg634

[0026] This relationship approximates the mean glucose and HbA1c for individuals with stable daily glucose profiles. Equation 1 can be rearranged to Equation 7: formula 7 JPEG0007770316000009.jpg6100

[0027] Given a starting HbA1c (HbA1c0), and assuming a constant glucose level during interval t, the HbA1c value at the end of this time interval can be calculated by solving the differential equation in Equation 7 and integrating from time 0 to t: tEquation 8 is derived for formula 8 JPEG0007770316000010.jpg683

[0028] To accommodate varying glucose levels over time, each subject's glucose history is recorded along with the corresponding glucose level [G i ] a series of time intervals t i By recursively applying Equation 8, the HbA1c value is calculated as z (At the end of the time interval t z ) can be expressed as Equation 9 for numerical calculation. formula 9 JPEG0007770316000011.jpg11125where, JPEG0007770316000012.jpg1240. At the end of the time interval t z The HbA1c value z is equivalent to calculated HbA1c (cHbA1c). cHbA1c is the preferred term introduced by the applicant's research. EA i and D i are both k gly , k age Note that the results were affected by the glucose level. i is the time interval t i depends on the length of

[0029] Equations 8 and 9 show that HbA1c change can be estimated using glucose levels and individual kinetic constants k gly and k age The data section contains two HbA1c measurements, one at the beginning and one at the end of the period, with frequent glucose levels between them. Similarly, cHbA1c is dependent on k gly and k age can be calculated at any time point, assuming that HbA1c and frequent glucose measurements are available. The purpose of frequent glucose measurements is to measure HbA1c at defined time intervals (ti ) and the average glucose ([G i In this study, frequent glucose levels were measured at 15-minute intervals, and the time interval between tests (t i ) were 3 hours, 6 hours, 12 hours, 24 hours, and 36 hours.

[0030] Calculation of physiological parameters from dynamic models Embodiments of the present disclosure provide dynamic modeling of the glycation, clearance, and development of red blood cells within a subject's body.

[0031] Physiological parameter k gly , k age and / or K can be derived from the formulas described herein given at least one test HbA1c value (also referred to as a measured HbA1c level) and a plurality of glucose levels (also referred to as measured glucose levels) over a period of time immediately preceding the HbA1c measurement.

[0032] FIG. 2 illustrates an exemplary time series 200 showing a collection of at least one test HbA1c value 202 a , 202 b , 202 c and a plurality of glucose levels 204 a over a period of time 206 .

[0033] k gly , k age The number of test HbA1c values ​​202a, 202b, 202c needed to calculate K and / or K depends on the frequency and duration of multiple glucose levels and the dynamics of HbA1c and glucose levels over time.

[0034] In a first embodiment, one test HbA1c 202b is used with multiple glucose measurements over a period of time 206. gly , k age , and / or K. Such an embodiment is applicable to subjects with regular daily glucose measurements over an extended period 206.

[0035] k gly and k age teeth, Since JPEG0007770316000013.jpg628 approaches zero over time, it can be calculated using Equation 9 when glucose levels are measured over a sufficient amount of time (e.g., over about 200 days). Thus, an initial HbA1c level measurement is not necessarily required.

[0036] Because the initial HbA1c value is not measured, the period 206 of initial glucose level measurements with frequent measurements may need to be long to obtain an accurate representation of average glucose and reduce error. Using a steady glucose pattern longer than 100 days for this method can reduce error. Additional lengths, such as 200 days or more or 300 days or more, further reduce error.

[0037] Embodiments in which the test HbA1c value 202b can be used include a period 206 in which glucose levels are measured at least about 72 times per day (e.g., about every 20 minutes) to about 96 times per day (e.g., about every 15 minutes) or more frequently, ranging from about 100 to 300 days (or longer). Furthermore, in such embodiments, the time between glucose level measurements can be somewhat consistent, in which case the interval between two glucose level measurements should not exceed about one hour. When using only one test HbA1c value, some missing data glucose measurements are acceptable. An increase in missing data may result in more error.

[0038] Alternatively, in some cases where a single test HbA1c value 202b is used, the time period 206 can be shortened if the subject has an existing glucose level monitoring history with a stable and consistent glucose profile. For example, in a subject who has been testing for a long time (e.g., six months or longer), but perhaps not tested very frequently or many times, the existing glucose level measurements can be used to analyze the glucose profile. Furthermore, if more frequent and numerous glucose monitors are performed over the time period 206 (e.g., about 72 to about 96 times per day for about 14 days or longer), followed by measurements of HbA1c 202b, these three can be used to determine one or more physiological parameters (k gly , k age , and / or K) can be calculated.

[0039] Alternatively, in some embodiments, two test HbA1c values ​​can be used, a first test HbA1c value 202a at the beginning of the time period 206 and a second test HbA1c value 202b at the end of the time period 206, and multiple glucose levels 204a are measured during the time period 206. In these embodiments, one or more physiological parameters (k gly , k age , and / or K) can be calculated. In such embodiments, multiple glucose levels 204a can be measured over a period of about 10 to about 30 days or longer, with these measurements occurring on average from about 4 times per day (e.g., about every 6 hours) to about 24 times per day (e.g., about every hour) or more frequently.

[0040] The above-described embodiments are not limited to the exemplary glucose level measurement duration and frequency ranges provided. Glucose levels can be measured over a period of time ranging from as little as a few days to about 300 days or more (e.g., about 1 week or more, about 10 days or more, about 14 days or more, about 30 days or more, about 60 days or more, about 90 days or more, about 120 days or more, etc.). The frequency of such glucose levels can be, on average, from about 14,400 times daily (e.g., about every 10 seconds) (or more frequently) to about three times daily (e.g., about every 8 hours) (e.g., 1,440 times daily (e.g., about every minute), about 288 times daily (e.g., about every 5 minutes), about 144 times daily (e.g., about every 10 minutes), about 96 times daily (e.g., about every 15 minutes), about 72 times daily (e.g., about every 20 minutes), about 48 times daily (e.g., about every 30 minutes), about 24 times daily (e.g., about every hour), about 12 times daily (e.g., about every 2 hours), about 8 times daily (e.g., about every 3 hours), about 6 times daily (e.g., about every 4 hours), and about 4 times daily (e.g., about every 6 hours), etc.). In some cases, less frequent monitors (such as once or twice daily) can be used, where glucose measurements are taken at approximately the same time each day (within about 30 minutes) to allow for a more direct comparison of day-to-day glucose levels and reduce error in subsequent analyses.

[0041] The above-described embodiments may further include calculating an error or inaccuracy associated with one or more physiological parameters. In some embodiments, the error may be used to determine whether to measure another HbA1c value (not illustrated) near t1, whether to measure one or more glucose levels 204b (e.g., near t1), whether to extend the monitoring and analysis (e.g., to extend through the period 208 from t1 to t2, which includes measuring the glucose level 204b at time t2 and the measured HbA1c value 202c), and / or whether to increase the frequency of glucose level measurements 204b within the extended period 208 relative to the frequency of glucose level measurements 204a during the period 206. In some embodiments, k gly , k ageOne or more of the above actions can be taken when the error associated with K (e.g., error from an HbA1c assay) is about 15% or greater, preferably about 10% or greater, preferably about 7% or greater, preferably about 5% or greater. When a subject has an underlying disease condition (e.g., cardiovascular disease), a lower error can be preferred, so as to have more rigorous monitoring and less error in the analyses described herein.

[0042] Alternatively, or when the error is within an acceptable range, in some embodiments, one or more physiological parameters (k gly , k age , and / or K) can be used to determine one or more parameters or characteristics related to the subject's individual diabetes management (e.g., cHbA1c at the end of time period 208, personalized target glucose range, and / or treatment or treatment changes for the subject in the near future), each of which is further described in more detail herein. Optionally, the HbA1c value can be measured at time t2 and one or more physiological parameters can be recalculated and applied to a future time period (not illustrated).

[0043] One or more physiological parameters and / or one or more parameters or characteristics related to a subject's individual diabetes management can be measured and / or calculated at two or more times (e.g., t1 and t2) and compared. For example, k at t1 gly and k at t2 gly In another example, the cHbA1c at t2 can be compared to the cHbA1c at a subsequent time. Additionally, some embodiments described herein can use such comparisons to (1) monitor the progress and / or effectiveness of a subject's individual diabetes management and optionally modify the subject's individual diabetes management, (2) identify abnormal or pathological physiological conditions, and / or (3) identify subjects receiving nutritional supplements and / or medications that alter red blood cell development and / or metabolism.

[0044] One or more physiological parameters (k gly , k age , and K) and associated analytical results (e.g., personalized-target glucose range, personalized-target average glucose, cHbA1c, and aHbA1c, etc.), one or more physiological parameters (k gly , k age , and K) and related analytical results can be updated periodically (e.g., about every three months to one year). The frequency of updates can depend, among other things, on the subject's glucose levels and diabetes history (e.g., how well the subject stays within specified thresholds), other medical conditions, etc.

[0045] Adjusted HbA1c In the art of diabetes and red blood cell glycation, generally accepted average RBC life spans may vary. ref age Preferably, k reflects a baseline average RBC lifespan of 85 to 135 days, 85 to 110 days, 90 to 110 days, 95 to 125 days, or 110 to 135 days, although the baseline RBC lifespan may be outside of these ranges. ref age reflects a reference RBC lifespan of 85 to 110 days, or 90 to 110 days, or 100 days. ref age is 0.01 days -1 However, embodiments of the present disclosure may be modified to accommodate this particular k ref age Not limited to.

[0046] aHbA1c for a subject is the HbA1c level and k age and k ref age and can be calculated using Equation 10. Formula 10 JPEG0007770316000014.jpg1653HbA1c in the above formula can be cHbA1c or test HbA1c as described herein.

[0047] Usually K=k gly / k age requires only one section of data to make a decision with high confidence. Larger K values ​​usually require smaller k age Since it correlates with the value of k age K can be used to generate a rough aHbA1c early when K is not yet available (Equation 11). ref The value is, for example, 5.2 x 10 -4 However, embodiments of the present disclosure may be modified to accommodate this particular K ref Not limited to. Formula 11 JPEG0007770316000015.jpg1153HbA1c in the above formula can be cHbA1c or test HbA1c as described herein.

[0048] The aHbA1c for the subject (based at least in part on the test HbA1c and / or calculated HbA1c) can then be used for diagnostic, treatment, and / or monitoring protocols for the subject. For example, the subject can be diagnosed as having diabetes, pre-diabetes, or another abnormal or pathological physiological condition based at least in part on the aHbA1c described herein. In another embodiment, the subject can be monitored and / or treated, such as by self-monitoring and / or self-injection of insulin and continuous insulin monitoring and / or injection, based at least in part on the aHbA1c described herein. In yet another example, the aHbA1c described herein can be used to determine and / or administer individual treatments for subject triage, to determine and / or administer individual treatments for diabetic drug titration, to determine and / or administer individual closed-loop or hybrid closed-loop control systems, to determine and / or administer individual treatments using glycosylation drugs, to determine physiological age, to identify whether and / or which nutritional supplements and / or medications are present during testing, and for similar purposes and any combination thereof.

[0049] By eliminating the interference of differences in RBC turnover rates, aHbA1c is a better individual biomarker than HbA1c for the risk of complications in people with diabetes. aHbA1c can be higher or lower than laboratory HbA1c, making a significant difference in the diagnosis and management of diabetes. In individuals with faster-than-normal RBC turnover rates, HbA1c, typically observed in patients with kidney disease or after heart valve surgery, can be artificially low, giving people the illusion of good glycemic control. Conversely, slower-than-normal RBC turnover can lead to artificially high HbA1c and overtreatment, resulting in dangerous hypoglycemia.

[0050] In one example, 0.0125 days -1 k age(or an 80-day RBC lifespan) and a test HbA1c of 7% would result in an aHbA1c of 8.6%. A test HbA1c of 7% without adjustment for RBC turnover rate indicates good glycemic control. However, this HbA1c value is an underestimate, and in this case, a more accurate value of 8.6% (aHbA1c) adjusted for RBC turnover rate would indicate a higher risk of complications for the subject.

[0051] Another example is 0.0077 days -1 k age (or 130-day RBC lifespan) and a seemingly high test HbA1c of 9% would result in an aHbA1c of 7.1%. A seemingly high test HbA1c of 9% would be considered indicative of poor glycemic control and a significant complication risk. However, with an aHbA1c of 7.1%, this person has only a low complication risk. Working from a test HbA1c value of 9%, with an aHbA1c of 7.1%, the subject would likely be receiving treatment that may put them at risk for hypoglycemia.

[0052] Only when K is available can aHbA1c be estimated using Equation 11. For example, if the test HbA1c is 8% and 6×10 -4 day -1 When a high K value of 7% is determined, the aHbA1c estimate is 7%. This adjustment is usually conservative, so k age is still not available. In this example, unnecessary and potentially harmful treatment may be administered based on the test HbA1c value when treatment should not be provided based on the aHbA1c value.

[0053] In another example, if the test HbA1c is 7%, and 4 x 10 -4 day -1 When a low K value of 8.9% is determined, the estimated aHbA1c is 8.9%. In this case, treatment may not be administered if relying solely on the laboratory HbA1c value, but treatment should be provided due to the high aHbA1c.

[0054] k in this specification ref age is a predetermined value used as a reference mean RBC turnover rate that represents the RBC lifespan. The RBC turnover rate is k age Divide 1 by the RBC lifespan to give a percentage point per day * 100 (or k age =(1 / RBC life) * 100). k ref age is calculated in the same manner using the desired baseline mean RBC lifetime.

[0055] Subject's k age can be determined by a variety of methods, including but not limited to, those described in U.S. Patent Application Publication No. 2018 / 0235524, U.S. Provisional Patent Application No. 62 / 750,957, and U.S. Provisional Patent Application No. 62 / 939,956, the entire contents of each of which are incorporated herein by reference for all purposes.

[0056] HbA1c can be measured in a laboratory and / or calculated based at least in part on glucose monitor data (e.g., as described herein as cHbA1c). Preferably, this glucose monitor data is continuous with almost no missing readings to provide greater accuracy in the calculated HbA1c level. Although HbA1c is described herein as calculated HbA1c, those skilled in the art may also refer to HbA1c levels as calculated or estimated HbA1c levels.To calculate (or estimate) HbA1c levels, the eAG / A1C Conversion Calculator provided by the American Diabetes Association, the glucose management indicator (GMI) method (e.g., "Glucose management indicator (GMI): A new term for estimating A1C from continuous glucose monitoring," Diabetes 41(11) pp. 2275-2280, November 2018), the method described in "Translating the A1C assay into estimated average glucose values," Diabetes Care 31(8) pp. 1473-1478, August 2008, PMID: 18540046, "Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes" can be used. Several methods can be used, including, but not limited to, those described in "Mechanistic Modeling of Hemoglobin Glycation and Erythrocyte Dynamics Enables Individualized Diabetes Monitoring," Sci. Transl. Med. 8, 359ra130, October 2016, U.S. Patent Application Publication No. 2018 / 0235524, U.S. Provisional Patent Application No. 62 / 750,957, and U.S. Provisional Patent Application No. 62 / 939,956, and any hybrids thereof. The entire contents of each of the above-mentioned patent applications are incorporated herein by reference for all purposes.

[0057] The disclosed methods include determining an HbA1c level for a subject (e.g., measuring and / or calculating based on a glucose monitor) and determining an RBC elimination rate constant (RBC turnover rate and k ageAlso known as -1 determining the HbA1c level and k age The standard k is defined as age (k ref age and calculating an adjusted HbA1c value (aHbA1c) for the subject based on the aHbA1c. The subject can then be diagnosed, treated, and / or monitored based on the aHbA1c.

[0058] Non-exclusive exemplary methods of the present disclosure include providing (or taking) a plurality of blood glucose measurements for a subject; calculating HbA1c for the subject based at least in part on the plurality of blood glucose measurements; and calculating a kcal for the subject. age and providing (or determining) the HbA1c level and k age and k ref age and calculating an aHbA1c for the subject based on the aHbA1c. The subject can then be diagnosed, treated, and / or monitored based on the aHbA1c.

[0059] Another non-exclusive exemplary method of the present disclosure includes providing (or measuring) HbA1c for a subject; age and providing (or determining) the HbA1c level and k age and k ref age and calculating an aHbA1c for the subject based on the aHbA1c. The subject can then be diagnosed, treated, and / or monitored based on the aHbA1c.

[0060] Other factors One or more physiological parameters (k gly , k ageIn some of the embodiments described herein that apply K, Kb, Kc, and / or Kd), one or more other subject-specific parameters can be used in addition to one or more physiological parameters. Examples of subject-specific parameters can include, but are not limited to, underlying conditions (e.g., cardiovascular disease, heart valve replacement, cancer, and systemic disorders such as autoimmune diseases, hormonal disorders, and blood cell disorders), family history of conditions, current treatments, age, race, sex, geographic location (e.g., where the subject grew up or where the subject currently lives), diabetes type, and duration of diabetes diagnosis, and the like, and any combination thereof.

[0061] system In some embodiments, one or more physiological parameters (k gly , k age , and / or K) may be performed by a physiological parameter analysis system.

[0062] 3 illustrates an example physiological parameter analysis system 310 for providing physiological parameter analysis according to some embodiments of the present disclosure. The physiological parameter analysis system 310 includes one or more processors 312 and one or more machine-readable storage media 314. The one or more machine-readable storage media 314 include a set of instructions for implementing physiological parameter analysis routines that are executed by the one or more processors 312.

[0063] In some embodiments, these instructions are based on input 316 (e.g., one or more previously determined glucose levels, one or more HbA1c levels, one or more physiological parameters (k gly , k age , and / or K), or one or more other subject-specific parameters, and one or more times for any of these); and output 318 (e.g., one or more physiological parameters (k gly , k age, and / or K), errors associated with one or more physiological parameters, one or more parameters or characteristics related to the subject's individual diabetes management (e.g., cHbA1c, aHbA1c, personalized-target glucose range, average target glucose level, dosage of nutritional supplement or medication, among other parameters or characteristics), and communicating an output 318. In some embodiments, the communication of the input 316 can be, for example, through a user interface (which can be part of the display), a data network, a server / cloud, another device, a computer, or any combination thereof. In some embodiments, the communication of the output 318 can be, for example, to a display (which can be part of the user interface), a data network, a server / cloud, another device, a computer, or any combination thereof.

[0064] As used herein, the term "machine-readable medium" includes any mechanism that can store information in a form accessible by a machine (which may be, for example, a computer, a network device, a cellular telephone, a personal digital assistant (PDA), a manufacturing tool, or any device having one or more computers). For example, machine-accessible media includes recordable and non-recordable media (e.g., read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, etc.).

[0065] In some cases, the one or more processors 312 and the one or more machine-readable storage media 314 may reside in a single device (e.g., a computer, a network device, a cellular phone, a PDA, an analyte monitor, etc.).

[0066] In some embodiments, the physiological parameter analysis system may include other components. Figure 4 illustrates another example physiological parameter analysis system 410 for providing physiological parameter analysis according to some embodiments of the present disclosure.

[0067] The physiological parameter analysis system 410 includes a health monitor device 420 having a subject interface 420A and an analysis module 420B, which is or can be operatively coupled to a data network 422. Further provided within the physiological parameter analysis system 410 are a glucose monitor 424 (e.g., an in vivo and / or in vitro (ex vivo) device or system) and a data processing terminal / personal computer (PC) 426, each operatively coupled to the health monitor device 420 and / or the data network 422. FIG. 4 also shows a server / cloud 428 operatively coupled to the data network 422 for bidirectional data communication with one or more of the health monitor device 420, the data processing terminal / PC 426, and the glucose monitor 424. The physiological parameter analysis system 410 within the present disclosure can exclude one or more of the server / cloud 428, the data processing terminal / PC 426, and / or the data network 422.

[0068] In certain embodiments, analysis module 420B is programmed or configured to perform physiological parameter analysis and optionally other analyses (e.g., cHbA1c, aHbA1c, personalized-target glucose ranges, and others as described herein). As shown, analysis module 420B is part of (e.g., executed by a processor therein) health monitor device 420. However, analysis module 420B may alternatively be associated with one or more of server / cloud 428, glucose monitor 424, and / or data processing terminal / PC 426. For example, one or more of server / cloud 428, glucose monitor 424, and / or data processing terminal / PC 426 may include one or more machine-readable storage media having a set of instructions that cause one or more processors to execute the set of instructions corresponding to analysis module 420B.

[0069] Although health monitor device 420, data processing terminal / PC 426, and glucose monitor 424 are each shown as operatively coupled to data network 422 for communication to / from server / cloud 428, one or more of health monitor device 420, data processing terminal / PC 426, and glucose monitor 424 may be programmed or configured to bypass data network 422 and communicate directly with server / cloud 428. Modes of communication between health monitor device 420, data processing terminal / PC 426, and glucose monitor 424 and data network 422 may include one or more of wireless communication, wired communication, RF communication, BLUETOOTH® communication, WiFi data communication, radio frequency identification (RFID) enabled communication, ZIGBEE® communication, or any other suitable data communication protocol, optionally supporting data encryption / decryption, data compression, data decompression, and the like.

[0070] As described in more detail below, the physiological parameter analysis may be performed by one or more of the health monitor device 420, the data processing terminal / PC 426, the glucose monitor 424, and the server / cloud 428, and the resulting analysis output is shared within the physiological parameter analysis system 410.

[0071] Additionally, although the glucose monitor 424, health monitor device 420, and data processing terminal / PC 426 are each shown as operatively coupled to one another through a communication link, they may be modules within a single integrated device (e.g., a sensor having a processor and a communication interface for sending / receiving and processing data).

[0072] Measurement of glucose and HbA1c levels The measurements of multiple glucose levels over different time periods described herein can be performed using in vivo and / or in vitro (ex vivo) methods, devices, or systems for measuring at least one analyte, such as glucose, in a bodily fluid, such as blood, interstitial fluid (ISF), subcutaneous fluid, dermal fluid, sweat, tears, saliva, or other biological fluid. In some cases, a combination of in vivo and ex vivo methods, devices, or systems can be used.

[0073] Examples of in-vivo methods, devices, or systems measure glucose levels and optionally other analytes in blood or ISF where at least a portion of the sensor and / or sensor control device is placed or can be placed on the body of a subject (e.g., beneath the surface of the subject's skin). Examples of devices include, but are not limited to, continuous analyte monitoring devices and intermittent analyte monitoring devices. Specific devices or systems are further described herein and can be found in U.S. Pat. No. 6,175,752 and U.S. Patent Application Publication No. 2011 / 0213225, the entire disclosures of each of which are incorporated herein by reference for all purposes.

[0074] In vitro methods, devices, or systems (including those that are completely non-invasive) include sensors that contact bodily fluids outside the body to measure glucose levels. For example, an in vitro system can use a metering device having a port for accepting an analyte test strip that can hold a subject's bodily fluid and be analyzed to determine the glucose level therein. Additional devices and systems are described below.

[0075] As noted above, the frequency and duration of measuring glucose levels can vary from an average of about 3 times per day (e.g., about every 8 hours) to about 14,400 times per day (e.g., about every 10 seconds) (or more frequently), and from a few days to about 300 days.

[0076] Once the glucose level is measured, it can be used to measure one or more physiological parameters (k gly , k age , and / or K) and optionally other analytical results (e.g., cHbA1c, aHbA1c, personalized-target glucose ranges, and others described herein) can be determined. In some cases, such analyses can be performed by a physiological parameter analysis system. For example, referring back to FIG. 4 , in some embodiments, glucose monitor 424 can include a glucose sensor coupled to electronics for (1) processing a signal from the glucose sensor and (2) communicating the processed glucose signal to one or more of health monitor device 420, server / cloud 428, and data processing terminal / PC 426.

[0077] Measurement of one or more HbA1c levels at various times as described herein can be according to any suitable method. Typically, HbA1c levels are measured in a laboratory using a blood sample from a subject. Examples of laboratory tests include, but are not limited to, chromatographic assays, antibody-based immunoassays, and enzyme-based immunoassays. HbA1c levels can be measured using an electrochemical biosensor.

[0078] The frequency of HbA1c level measurements can vary from monthly to yearly on average (or less frequently if the subject's average glucose levels remain stable).

[0079] Once the glucose level is measured, it can be used to determine one or more physiological parameters and, optionally, other analytical results described herein. In some cases, such analyses can be performed by a physiological parameter analysis system. For example, referring back to FIG. 4 , in some embodiments, the HbA1c level can be measured by a laboratory test, where the results are entered into the server / cloud 428, subject interface 420A, and / or display from a testing entity, a medical professional, a subject, or other user. The HbA1c level can then be received by the health monitor device 420, the server / cloud 428, and the data processing terminal / PC 426 for analysis by one or more methods described herein.

[0080] Calculation HbA1c (cHbA1c) One or more physiological parameters (k gly , k age , and / or K), multiple glucose measurements can be taken over a subsequent period of time and used to calculate HbA1c during and / or at the end of the period. For example, referring back to FIG. 2, at time t1, one or more physiological parameters (k gly , k age , and / or K) can then be calculated. Then, multiple glucose levels 204b can be measured over a subsequent period 208. Additionally, during and / or at the end of period 204b, a cHbA1c value (HbA1c in Equation 9) can be calculated using Equation 9. z) can be determined, where HbA1c0 is the test HbA1c level 202b at the end of time period 206 (which is the beginning of time period 208), and [G i ] is the time t over the period 208 (or the portion of the period 208 over which cHbA1c is determined). i is the glucose level measured at time t1 or its average, and is the glucose level measured at time t2 or its average, and is the glucose level measured at time t3 or its average, and is the glucose level measured at time t4 or its average, and is the glucose level measured at time t5 or its average, and is the glucose level measured at time t6 or its average, and is the glucose level measured at time t7 or its average, and is the glucose level measured at time t8 or its average, and is the glucose level measured at time t9 or its average, and is the glucose level measured at time t1 ...2 or its average, and is the glucose level measured at time t3 or its average, and is the glucose level measured at time t4 or its average, and is the glucose level measured at time t5 or its average, and is the glucose level measured at time t6 or its average, and is the glucose level measured at time t5 or its average, and gly , k age , and / or K) are used.

[0081] One or more physiological parameters (k) determined using the most recent test HbA1c level and the intermediate glucose level measurements. gly , k age , and / or K), a subject's cHbA1c can be determined over several consecutive time periods. HbA1c can be measured periodically (e.g., every 6 months to 1 year) to recalculate one or more physiological parameters. The time between assessments of test HbA1c may depend on (1) the consistency of glucose level measurements, (2) the frequency of glucose level measurements, (3) the subject's and corresponding family's diabetes history, (4) the length of time the subject has been diagnosed with diabetes, (5) changes to the subject's individual diabetes management (e.g., medication / dosage changes, dietary changes, and exercise changes), and combinations thereof. For example, a subject who exhibits consistent glucose level measurements (e.g., [G] with less than a 5% change) and who performs frequent glucose level measurements (e.g., a continuous glucose monitor) may not measure their HbA1c levels as frequently as a subject who exhibits consistent glucose level measurements and frequent glucose level measurements but who recently (e.g., within the last 6 months) changed their glycosylation medication dosage.

[0082] FIG. 5, with reference to FIG. 3, illustrates an example of a cHbA1c report that can be generated as output 318 by the physiological parameter analysis system 310 of the present disclosure. The illustrated example report includes a plot of average glucose levels over time. The report also includes the most recent test HbA1c level (open circle) and the cHbA1c level calculated by the physiological parameter analysis system 310 (asterisk). Although two cHbA1c levels are shown, one or more cHbA1c levels can be displayed on the report, including a line tracing the cHbA1c continuously. Alternatively, the output 318 of the physiological parameter analysis system 310 can include a single numerical value for the current or most recently calculated cHbA1c, aHbA1c, a table corresponding to the data in FIG. 5, or any other report that provides at least one cHbA1c level to a subject, healthcare provider, or similar.

[0083] In some cases, cHbA1c can be compared to a previous cHbA1c level and / or a previous test HbA1c level to monitor the effectiveness of the subject's individual diabetes management. For example, if a dietary plan and / or exercise regime is being implemented as part of a subject's individual diabetes management, all other factors (e.g., medications and other diseases) being equal, a change in cHbA1c compared to a previous cHbA1c level and / or a previous test HbA1c level can indicate whether the dietary plan and / or exercise regime is effective, ineffective, or somewhere in between.

[0084] In some cases, the cHbA1c can be compared to a previous cHbA1c level and / or a previous test HbA1c level to determine whether to obtain another HbA1c measurement. For example, another test HbA1c level can be tested if there is a change of 0.5 percentage units or more compared to the previous cHbA1c level and / or the previous test HbA1c level (e.g., a change from 7.0% to 6.5% or from 7.5% to 6.8%).

[0085] In some cases, a comparison of cHbA1c with a previous cHbA1c level and / or a previous laboratory HbA1c level can indicate whether an abnormal or pathological physiological condition exists. For example, if a subject has maintained a cHbA1c level and / or laboratory HbA1c level for an extended period of time and then a change in cHbA1c is identified without any other apparent cause, the subject may have an abnormal or pathological physiological condition. Indications of a new abnormal or pathological physiological condition may include a change in one or more physiological parameters (k gly , k age , and / or K). Details of abnormal or pathological physiological conditions relating to one or more physiological parameters are discussed later in this specification.

[0086] Personalized - Target Glucose Ranges and Personalized Glucose Levels Typically, glucose levels in subjects with diabetes are preferably maintained between 70 mg / dL and 180 mg / dL. However, the dynamic model described herein assumes that intracellular glucose levels are maintained at a constant rate of k gly Furthermore, intracellular glucose levels are associated with hypoglycemic and hyperglycemic damage to organs, tissues, and cells. Therefore, measured glucose levels may not actually correspond to the actual physiological conditions for diabetes management in a subject. For example, higher than normal k gly A subject with a kappa blood glucose level absorbs glucose more readily into their cells. Therefore, a measured glucose level of 180 mg / dL may be excessively high for this subject and may further perpetuate the subject's diabetes in the long term. In another example, a subject with a kappa blood glucose level lower than normal may have a kappa blood glucose level higher than normal. gly A subject with HIV does not absorb glucose into their cells as well. Therefore, at a glucose level of 70 mg / dL, the subject's intracellular glucose level is quite low, making the subject feel weak and potentially rendering the subject hypoglycemic over the long term.

[0087] As used herein, subject-specific k values ​​for glucose readings and / or corresponding personalized glucose ranges are used. glyThree methods for accepting the upper and lower limits of acceptable normal glucose are: (a) gly (b) adjusting the subject's measured glucose level for an effective plasma glucose level that correlates with an acceptable upper and lower normal glucose limit; and (c) adjusting the subject's measured glucose level for an intracellular glucose level that correlates with an acceptable lower normal intracellular glucose limit (LIGL) and an acceptable upper normal intracellular glucose limit (UIGL).

[0088] First, the lower acceptable normal glucose limit (LGL) and upper acceptable normal glucose limit (AU) can be used to derive equations (Equations 12 and 13) for the personalized lower glucose limit (GL) and equations (Equations 14 and 15) for the personalized upper glucose limit (GU). Equations 13 and 15 are rewrites of Equations 12 and 14 for the case where both test HbA1c and aHbA1c are available. Formula 12 JPEG0007770316000016.jpg1642 JPEG0007770316000017.jpg1110 is the normal body k gly and JPEG0007770316000018.jpg1110 is the subject's k gly is. Formula 13 JPEG0007770316000019.jpg1174 formula 14 JPEG0007770316000020.jpg1642 formula 15 JPEG0007770316000021.jpg1174

[0089] Since the upper and lower limits of the glucose range are based on equivalent intracellular glucose levels, Equations 12 and 14 are used to calculate k gly is based on.

[0090] The current acceptable values ​​for the above are LGL = 70 mg / dL, JPEG0007770316000022.jpg1110=6.2 * 10 -6 dL * mg -1* day -1 , and AU=180 mg / dL.

[0091] 6A illustrates an example of a method for determining a personalized target glucose range 630. A desired glucose range 632 (e.g., a currently acceptable glucose range) having a lower limit 634 and an upper limit 636 is determined based on a physiological parameter k gly 638, can be personalized using Equations 12 and 14, respectively. This results in a personalized lower glucose limit (GL) 640 (Equation 12±7%) and a personalized upper glucose limit (GU) 642 (Equation 14±7%) that define a personalized-target glucose range 630. Alternatively or additionally, a desired glucose range 632 (e.g., a current acceptable glucose range) having lower and upper limits 634 and 636 can be personalized using Equations 13 and 15, respectively, using the test HbA1c and calculated aHbA1c 683. Thus, in general, the method comprises: (a) k gly and / or (b) after measuring HbA1c and calculating aHbA1c, a personalized target glucose range can be determined, in which case the lower glucose limit can be changed according to Equation 12 (and / or Equation 13) ± 7% and the upper glucose limit can be changed according to Equation 14 (and / or Equation 15) ± 7%. For example, 5.5 * 10 -6 dL * mg -1* day -1 A subject with DMARD may have a personalized target glucose range of about 81±7 mg / dL to about 219±27 mg / dL, and thus may have an acceptable glucose level range that differs from their current clinical glucose range.

[0092] 6B illustrates an example of a personalized target glucose range report that may be generated as output 318 by the physiological parameter analysis system 310 of the present disclosure with reference to FIG. 3. The illustrated example report includes a plot of glucose levels over the course of a day relative to the personalized target glucose range (shaded area) described above. Alternatively, other reports may include, but are not limited to, an ambulatory glucose profile (AGP) plot and a numerical display of the personalized target glucose range with recent glucose level measurements, and the like, and any combination thereof.

[0093] Another example is 6.5*10 -6 dL*mg -1 *day -1 k gly A subject with ≥ 18 years of age may have a personalized-target glucose range of about 66±5.5 mg / dL to about 167±18 mg / dL. Due to the significantly lower upper glucose level limit, this subject's individual diabetes management may include more frequent glucose level measurements and / or medication administration to remain substantially within this personalized-target glucose range.

[0094] In yet another example, 5.0 * 10 -6 dL * mg -1* day -1 k gly A subject with HIV may have a personalized target glucose range of about 92±8 mg / dL to about 259±34 mg / dL. This subject may be more sensitive to lower glucose levels and may experience weakness, hunger, dizziness, etc. more frequently with the glucose ranges currently in clinical practice (70 mg / dL and 180 mg / dL).

[0095] All of the above examples include a personalized lower glucose limit and a personalized upper glucose limit, but alternatively, the personalized target glucose range may include only a personalized lower glucose limit or a personalized upper glucose limit, and the other value in the personalized target glucose range may be the currently administered lower glucose limit or upper glucose limit.

[0096] Subject-specific k for glucose readings and / or corresponding personalized glucose ranges gly The second method to consider effective plasma glucose (PG eff The subject's plasma glucose level (e.g., measured using an analyte sensor configured to measure glucose levels in a bodily fluid, which in this case may be part of a larger system) is used to provide a k ) level. gly It is personalized using Equation 16. formula 16 JPEG0007770316000023.jpg1135where, JPEG0007770316000024.jpg1115.

[0097] PG eff The levels can be used in combination with the lower and / or upper normal glucose limits to diagnose, monitor, and / or treat a subject. eff Levels are interpreted relative to acceptable glucose limits, considered herein to be between 70 mg / dL and 180 mg / dL, but which may change based on new clinical and / or scientific data and health authority recommendations.

[0098] For example, 6.5 * 10 -6 dL * mg -1* day -1 k glyA subject with a blood glucose level of 170 mg / dL may receive a measured glucose level of 183 mg / dL, which changes when Equation 16 is applied, and this value is interpreted based on the acceptable glucose limits (70 mg / dL to 180 mg / dL). Thus, at this point, the subject would consider the 170 mg / dL measurement to be within acceptable limits. However, the effective plasma glucose may actually be higher, which may affect the appropriate dosage of insulin or other medication delivered.

[0099] Subject-specific k for glucose readings and / or corresponding personalized glucose ranges gly In a third method for considering the above, the subject's plasma glucose level (e.g., measured using an analyte sensor configured to measure glucose levels in a bodily fluid, which in this case may be part of a larger system) is expressed as k with respect to intracellular glucose (IG) levels. gly It is personalized by Equation 17 using formula 17 JPEG0007770316000025.jpg1125

[0100] The subject's IG level can then be compared to the acceptable lower normal intracellular glucose limit (LIGL) and upper normal intracellular glucose limit (UIGL). The current acceptable values ​​for LIGL and UIGL are 0.29 mg / dL and 0.59 mg / dL, respectively.

[0101] The personalized-target glucose range and / or personalized glucose level (e.g., effective plasma glucose level or intracellular glucose level) can be determined within and / or implemented in a physiological parameter analysis system. For example, an instruction set or program associated with a glucose monitor and / or health monitoring device that determines a therapy (e.g., insulin dosage) can use the personalized-target glucose range and / or personalized glucose level for such analysis. In some cases, a display or a subject interface associated therewith can display the personalized-target glucose range and / or personalized glucose level.

[0102] The personalized-target glucose range and / or personalized glucose level can be updated over time as one or more physiological parameters are recalculated.

[0103] Personalized - Target Average Glucose A personalized-target average glucose level (GT) can be calculated from the reference glucose target (RG) using Equation 18. The reference target glucose can take any value that the physician determines is appropriate, for example, 120 mg / dL. formula 18 JPEG0007770316000026.jpg1640

[0104] Instead of or in combination with Equation 18, GT can be calculated using Equation 19, which is based on test HbA1c and calculated aHbA1c. formula 19 JPEG0007770316000027.jpg1173

[0105] Equation 20 can be used instead of or in combination with Equation 18 and / or Equation 19 to calculate GT when the target HbA1c value (AT) is known. formula 20 JPEG0007770316000028.jpg640

[0106] In some embodiments, the physiological parameter analyzing system can determine an average glucose level for the subject during the time period 208 and optionally display the average glucose level and / or the target average glucose level. The subject can self-monitor their progress over the time period 208 using the current average glucose level and the target average glucose level. In some cases, the current average glucose level can be transmitted (periodically or regularly) to a healthcare professional using the physiological parameter analyzing system for monitoring and / or analysis.

[0107] 7, with reference to FIG. 3, illustrates an example of a personalized-target average glucose report that may be generated as output 318 by the physiological parameter analysis system 310 of the present disclosure. The illustrated example report includes a plot of the subject's average glucose over time (solid line) and a plot of the personalized-target average glucose (shown with a dashed line at 150 mg / dL). Alternatively, other reports may include, but are not limited to, a numerical display of the personalized-target average glucose along with the subject's average glucose level over a given time frame (e.g., the last 12 hours), and any combination thereof.

[0108] The personalized target average glucose level may be updated over time as the latest relevant physiological parameters, relevant calculations, and / or relevant measurements for one or more of Equations 18-20 are obtained.

[0109] Personalized Treatment - Patient Triage Insulin pumps can be used in conjunction with continuous glucose monitors for subjects who require tight control of their glucose levels. As exemplified above, target glucose ranges can be personalized. glyTherefore, in some cases, subjects with narrower personalized-target glucose ranges may be good candidates for an insulin pump with a continuous monitor. Triage of subjects who are good candidates for an insulin pump with a continuous glucose monitor is based on the width of the personalized-target glucose range and k gly It can be based on the following.

[0110] The range between the lower and upper glucose limits currently in clinical practice is approximately 110 mg / dL. However, as illustrated above, gly It is believed that depending on the individual's glucose level, this range could be narrowed to about 60 mg / dL or less. Some embodiments can involve triaging the subject to an insulin pump with a continuous glucose monitor when the personalized-target glucose range falls below a threshold below 110 mg / dL.

[0111] Some embodiments include k gly is 6.2 * 10 -6 dL * mg -1* day -1 This may involve triaging the subject to an insulin pump with a continuous glucose monitor when a higher threshold is exceeded.

[0112] Some embodiments include k gly is the threshold, e.g., 6.2 * 10 -6 dL * mg -1* day -1 This may involve placing the subject in a severe hypoglycemia prevention program when the blood glucose level is lower than 100mg / kg.

[0113] In some embodiments, triaging a subject to an insulin pump with a continuous glucose monitor can be a stepped triage in which the subject's glucose levels are first continuously monitored for a reasonable period of time (e.g., about 5 days, about 10 days, about 15 days, about 30 days, or longer). This continuous monitoring period can be used to assess whether the subject has the ability to substantially manage their glucose levels or whether an insulin pump would be more appropriate or necessary.

[0114] Whether the triage step is straight to insulin pump with continuous glucose monitoring or stepwise triage with monitoring before treatment with insulin pump is determined by indicators (i.e., personalized target glucose range extension, k gly , or any combination thereof). For example, k gly is about 6.4 * 10 -6 dL * mg -1* day -1 and the spread of the personalized-target glucose range is about 103 mg / dL, then this subject may be suitable for tiered triage compared to another subject whose corresponding indicators suggest that they should use an insulin pump.

[0115] In some embodiments, the triage may be based on a look-up table (e.g., stored in the physiological parameter analysis system of the present disclosure). The look-up table may, for example, include a look-up table that includes one or more physiological parameters (k gly , k age, and / or K), personalization—correlating multiple values ​​with each other, including but not limited to, the spread of a target glucose range, and / or other factors described herein, such as underlying medical conditions, family history of the condition, current treatment, age, race, sex, geographic location, diabetes type, and duration of diabetes diagnosis, and the like, and any combination thereof. Columns in the lookup table can, for example, define ranges or limit values ​​for the above-mentioned parameters, and rows can indicate suggested action progressions, which can be the output 318 of the physiological parameter analysis system 310 of FIG. 3. For example, two columns can be used to define k gly An upper and lower bound can be defined, where each row corresponds to a suggested action progression such as "candidate for insulin pump," "candidate for closed-loop control system," "candidate for basal / bolus insulin therapy," "candidate for basal-only insulin therapy," or any such treatment used to control diabetes or to cause glycation in the subject. In some cases, more than one action progression can be indicated. Thus, in this example, the subject triage report can simply display a suggested action progression.

[0116] Alternatively, the subject triage report may show a map of zones corresponding to action progression on a plot defined by, for example, one or more of the parameters described above with respect to a lookup table. Such zones may, in some cases, be defined by a lookup table that labels each zone with a recommendation, and may show glycemic parameter points on the map to indicate the appropriate zone for the subject.

[0117] The above two subject triage reports are examples based on lookup tables, but alternatively, (1) one or more physiological parameters (k gly , k age , and / or K), personalized-target glucose range spread, and / or other factors described herein, and (2) other correlations between action progression (e.g., mathematical algorithms or matrix analysis).

[0118] As discussed above, a subject's glycation parameters can help healthcare providers and payers better determine which therapeutic tools are most appropriate for which subjects. For example, closed-loop insulin pump systems are expensive to use and maintain, but subjects with high glycation rates may have very narrow personalized-target glucose ranges, in which case the safest treatment is to use a closed-loop insulin pump system to keep these subjects' glucose levels within those ranges.

[0119] In some embodiments, an insulin pump together with a continuous glucose monitor can be a closed-loop system. In some embodiments, an insulin pump together with a continuous glucose monitor can be a mixed-loop system. For example, referring back to FIG. 4, physiological parameter analysis system 410 can further include one or more of its internal components, such as a glucose monitor 424 (e.g., a continuous glucose monitoring system) and one of the insulin pumps described above that can communicate with health monitoring device 420.

[0120] Personalized Treatment - Diabetes Drug Titration In some embodiments, the dosage of a diabetes medication (e.g., insulin) to a subject is titrated using one or more physiological parameters (k gly , k age , and K) can be used. For example, with reference to FIG. 3 , a physiological parameter analysis system 310 of the present disclosure can determine or have inputs of (1) one or more physiological parameters, (2) a personalized-target glucose range, (3) a personalized glucose level (e.g., an effective plasma glucose level or an intracellular glucose level), and / or (4) a personalized-target average glucose. Then, when subsequent glucose levels are measured, the physiological parameter analysis system 310 can output a recommended diabetes drug dosage. An alternative or supplemental output 318 can be a glucose pattern insight report.

[0121] Examples of glucose pattern insight reports can be found in U.S. Patent Application Publication Nos. 2014 / 0188400 and 2014 / 0350369, each of which is incorporated herein by reference. The analyses and reports disclosed in the aforementioned applications may be used to analyze one or more physiological parameters (kcal) of the present disclosure. gly , k age , and K).

[0122] For example, FIG. 8, with reference to FIG. 3, illustrates an example of a glucose pattern insight report that may be an output 318 of a physiological parameter analysis system 310 (e.g., an insulin titration system). The illustrated glucose pattern insight report incorporates an AGP table of glycemic control measures (or “traffic lights”). As illustrated, the report includes an AGP plot over the analysis period (e.g., from about 1 month to about 4 months) showing a personalized-target average glucose at 120 mg / dL, the average glucose level for the subject over the analysis period, the 25th to 75th percentiles of glucose levels for the subject over the analysis period, and the 10th to 90th percentiles of glucose levels for the subject over the analysis period. Optionally, the glucose pattern insight report can additionally or alternatively display the personalized-target glucose range and / or personalized glucose level (e.g., effective plasma glucose level or intracellular glucose level) compared to the current acceptable glucose range. Additionally, the glucose pattern insight report may optionally further include one or more of the following: test HbA1c level, cHbA1c level, adjusted HbA1c level based on either the test HbA1c or glucose data, and the data range over which the mean glucose and associated percentiles were determined.

[0123] Below the AGP plot on the glucose pattern insight report is a table correlating one or more (shown as three) glycemic control measures with the subject's average glucose level over a given shortened time period for that day during the analysis period. This correlation, in this example, displays a traffic light (e.g., green (good), yellow (moderate), or high (red)) corresponding to the risk of the condition based on the glycemic control measures. Examples of glycemic control measures include, but are not limited to, likelihood of low glucose, likelihood of high glucose, proximity of average glucose to personalized-target average glucose, adherence of glucose levels to personalized-target glucose range and / or personalized glucose level compared to the current acceptable glucose range, degree of change in average glucose below (or above) the personalized-target average glucose, and degree of change in glucose level outside (below and / or above) the personalized-target glucose range and / or personalized glucose level compared to the current acceptable glucose range.

[0124] In some embodiments, the glucose pattern insight reports can be used as part of a diabetes drug titration system, where the lights (or related values) can drive logic to provide treatment modifications, such as changing the basal dose of a diabetes drug or an additional dose of a diabetes drug relative to a meal. For example, when used in conjunction with an automated or semi-automated system for titration, these lights driving logic can provide titration recommendations to the subject.

[0125] Glucose pattern insight reports and associated analyses incorporating the use of the dynamic models described herein can provide more targeted treatment for subjects with diabetes. In this example, as described above, 5.1 * 10 -6 dL * mg -1* day -1 k glyA subject with a glucose tolerance disorder may have a personalized target glucose range of about 90±8 mg / dL to about 250±32 mg / dL. This subject may be more sensitive to lower glucose levels and may experience weakness, hunger, dizziness, etc. more frequently with the glucose ranges currently in clinical practice (70 mg / dL and 180 mg / dL). One or more physiological parameters (k gly , k age The analysis logic used in the glucose pattern insight reports described herein using (K, K, and K) can include set values ​​that define hypoglycemia risk as a traffic light for "probable low glucose." For example, if the probable low glucose indicates a low risk (e.g., a green traffic light), it is considered safe to increase insulin. If the probable low glucose indicates a moderate risk (e.g., a yellow traffic light), it is considered that the current risk is acceptable, but another increase in insulin should not be made. Finally, if the probable low glucose indicates a high risk, it is recommended that insulin be decreased to bring glucose back to an acceptable level. For subjects with a high hypoglycemia risk due to a high lower glucose level threshold, the amount of risk (how far below the lower glucose level threshold) associated with moderate and high risk may be lower than for subjects with a normal lower glucose level threshold.

[0126] In the above example, a glucose pattern insight report was discussed as the output 318, but in other embodiments, other outputs using the same logic and analysis can be used. For example, the output 318 can be a dosage recommendation value.

[0127] One or more physiological parameters (k gly , k age, and K) and associated analytical results (e.g., personalized target glucose range, personalized glucose level, personalized target average glucose, cHbA1c, and aHbA1c, etc.) can be updated periodically (e.g., about every three months to one year). The frequency of updates can depend, among other things, on the subject's glucose level and diabetes history (e.g., how well the subject stays within specified thresholds), other disease conditions, etc.

[0128] The insulin titration system measures one or more physiological parameters (k gly , k age , and K) can optionally be utilized. Error values ​​can be determined by one of skill in the art using standard statistical techniques and can be used as another set of parameters for including the titration system. For example, the titration system can use a small risk amount for hypoglycemia when the lower glucose levels of a personalized-target glucose range of about 75 mg / dL have an error of about 7% or less (i.e., a small tolerance can be implemented that is lower than the lower glucose level thresholds for indicating moderate and high risk).

[0129] The dosage of the diabetes drug (eg, by titration) can be updated over time as one or more physiological parameters are recalculated.

[0130] Closed-loop and hybrid closed-loop control systems Closed-loop and hybrid closed-loop systems that recommend or administer insulin doses to subjects have been developed for insulin delivery based on near real-time glucose readings. These systems are often based on models that represent the subject's physiology, glucose sensor dynamics, and glucose sensor error characteristics. In some embodiments, to better meet the subject's needs, one or more physiological parameters (k gly , k age, and K) and associated analytical results (e.g., personalized target glucose range, personalized glucose level, personalized target average glucose, cHbA1c, and aHbA1c, etc.) can be incorporated into a closed-loop system.

[0131] In many cases, the closed-loop system is configured to "drive" the subject's glucose level to a target range and / or to a single glucose target, which may be a personalized target glucose range, personalized glucose level, and / or personalized target average glucose compared to the acceptable target glucose range described herein. For example, a high k gly and a high lower glucose limit for the personalized-target glucose range, the controller gly The subject's glucose level can be driven to stay above the lower glucose limit based on the target glucose range, which avoids lower glucose levels that would have a significantly worse effect on these subjects than subjects with a normal glucose range. Similarly, subjects with an upper glucose limit that is low relative to the personalized-target glucose range can have the controller of the closed-loop insulin delivery system and the hybrid closed-loop insulin delivery system drive their glucose to stay below the personalized upper glucose limit to mitigate hyperglycemic effects.

[0132] The metrics that the closed-loop insulin delivery systems and hybrid closed-loop insulin delivery systems rely on to determine insulin dosages can be updated over time when one or more physiological parameters are recalculated, for example, the personalized target glucose range, personalized glucose level, and / or personalized target average glucose can be updated when one or more physiological parameters are recalculated.

[0133] Personalized Treatment - Glycation Drugs Diabetes is a disease caused by the inability of a subject's pancreas to produce enough insulin (or any insulin at all). However, in some cases, a subject's glycation process may be the cause of the body's inability to properly control intracellular glucose. Such subjects may be more responsive to treatment with glycation drugs (e.g., azathioprine, meloxicam, nimesulide, piroxicam, mefenamic acid, oxaprozin, D-penicillamine, penicillin G, trimethylphloroglucinol, ranitidine, phloroglucinol dihydrate, epinephrine bitartrate, pyridoxine HCl, topiramate, escitalopram, hydroquinone, tretinoin, colchicine, and rutin) rather than traditional diabetes treatments. The dynamic model of the present disclosure provides a k gly and / or K(k gly Thus, one or both of these physiological parameters can be used to identify, treat, and / or monitor subjects with glycation disorders.

[0134] Some embodiments provide a method for administering a kappa to a subject regarding a glycosylation drug. gly and / or K, and optionally k gly and / or modifying the drug dosage based on changes in K. For example, referring to FIG. 2, some embodiments may modify the drug dosage based on changes in K at time t. gly1 and / or K1 is determined, and k gly2 and / or K2 (as described above) and treating the subject with a glycosylation drug for a period of time 208. Then, k gly1 and / or K1 and the corresponding k gly2 and / or K2, the dosage and / or type of glycosylation drug for the subsequent period may be modified based on a comparison with one or more of the previously determined physiological parameters. Additionally, in some cases, the corresponding k at the end of the subsequent period may be modified based on a comparison with one or more of the previously determined physiological parameters. gly3and / or K3 can be determined. The times between t1 and t2 and between t2 and t3 should be at least the expected time for the glycosylation drug to cause a measurable change in the monitored parameter, which may be drug and dose dependent.

[0135] In some embodiments, the output 318 of the physiological parameter analysis system 310 of FIG. 3 is the k gly and / or a glycosylation drug report including glycosylation drug and / or dosage recommendations based on K. This output 318 can be displayed to the subject, healthcare provider, and / or similar for review and adjustment of the glycosylation drug and / or dosage.

[0136] Alternatively, these dosage recommendations provide the next dose to be administered to the subject and / or the automated drug delivery system. In this case, the system guides the titration of the drug, allowing the subject to start with the lowest dose or the recommended initial dose. The initial dose may be determined based on the subject's current condition, the subject's k gly1 and / or K1, and other factors described herein. After an adequate amount of time has elapsed to adequately determine the effect of the current drug dose, k is calculated based on a new test HbA1c level and glucose levels measured during drug administration. gly2 and / or K2 can then be determined. gly2 and / or K2 to (1)k gly1 and / or K1, and / or (2) target k gly and / or target K. For example, for a hyperglycemic subject taking a drug to reduce the glycation rate, it is possible to determine whether the dosage needs to be changed. gly2 If k is still higher than desired, the dosage recommendation can be increased according to (1) a standard titration protocol and / or (2) a system that accounts for how previous dosage changes have affected the subject (known as control theory). gly2If K is low, the dose can be reduced. Drugs could also be titrated to affect K or other parameters. In addition, a similar process could be used to recommend non-drug treatments such as blood transfusions or blood sampling by inducing the appropriate amount of blood to be affected.

[0137] To monitor and titrate the effects of glycosylation drugs gly The use of and / or K may be beneficial to health care providers in treating subjects with abnormal glycation physiology.

[0138] The metrics relied upon when determining the dosage of a glycation drug can be updated over time as one or more physiological parameters are recalculated.

[0139] Identifying abnormal or pathological physiological conditions Dynamic modeling, in certain embodiments, involves the analysis of physiological parameters (e.g., k gly , k age (or k gen ), and / or K), where the same parameters are compared during different time periods to indicate an abnormal or pathological physiological condition in the subject. gly , k age Changes in k and / or k can provide an indication of an abnormal or pathological condition in the subject. gly , k age , and / or K varies between subjects, but k for a single individual gly , k age , and / or K changes are small and slow. Therefore, k gly , k age Comparison of k and / or k provides information about the physiological condition of the subject. gly , k age When clinically significant changes in β and / or K are seen over time, an abnormal or pathological physiological condition may and likely exists.

[0140] For example, k glyWhen a significant change over time occurs that is clinically significant, such a clinically significant change may indicate that significant glucose transporter levels or cell membranes have changed. Such biotransformations may indicate underlying metabolic changes in the subject's body resulting from the subject's physiology undergoing a disease condition.

[0141] k age and / or k gen When a clinically significant change occurs over time, such a clinically significant change can indicate a change in the subject's immune system, because the immune system is designed to recognize cells that need to be eliminated.

[0142] k age and / or k gen Clinically significant changes in k may additionally or alternatively be related to oxygen-sensing mechanisms in the body. age and / or k gen can indicate that the subject's body needs red blood cells to carry more oxygen, or that the oxygen-sensing mechanism is not functioning properly, either of which indicates a change in physiological condition, such as blood loss or a disease state.

[0143] In yet another example (in combination with or instead of the above examples), k age and / or k gen Clinically significant changes in k can be associated with changes in the bone marrow. For example, if the bone marrow suddenly produces more oxygen-carrying red blood cells, the subject's body will respond by destroying or eliminating more red blood cells. age and / or k gen A clinically significant increase in β-glucan can be associated with bone marrow abnormalities.

[0144] In another example, hormonal disorders include age , k genHormones can affect heart rate, contractile strength, blood volume, blood pressure, and erythropoiesis. Stress hormones such as catecholamines and cortisol stimulate the release of reticulocytes from the bone marrow and possibly also enhance erythropoiesis. Thus, large fluctuations in hormone levels can lead to clinically significant changes in k age and / or k gen may be changed, which may result in a change in K.

[0145] In yet another example, k gly , k age Deviations from normal for K and / or K can be indicators of diabetes or prediabetes. gly , k age Using K and / or K may be more effective than standard fasting glucose testing and testing HbA1c. For example, a subject with a test HbA1c in the normal range and normal fasting glucose may have a low k associated with high glucose values ​​at times other than fasting. gly Therefore, this subject may be a candidate for early involvement with diabetes that may otherwise go unnoticed based on standard diabetes diagnostic methods.

[0146] In another example, standard diabetes treatments can be used for subjects with newly elevated test HbA1c to reduce the HbA1c of these subjects. gly A determination that is abnormal is an indication of a problem associated with glycation physiology rather than the subject's pancreas, and may suggest other, more targeted forms of treatment.

[0147] An embodiment of the present disclosure is gly , k age , and / or K, and displaying changes therein over time and / or possible abnormal or pathological physiological conditions.

[0148] According to embodiments of the present disclosure, physiological parameter analysis provides an indication of an abnormal or pathological condition in a subject in the manner described herein, as well as analysis and / or monitoring tools for one or more parameters or characteristics related to the subject's individual diabetes management.

[0149] Identification of nutritional supplements and / or medications Some nutritional supplements and drugs interact with the dynamics of glycation, elimination, and development of red blood cells in the body. For example, nutritional supplements and drugs used by athletes for doping include, but are not limited to, human growth hormone, nutritional supplements and drugs that increase metabolic levels, and the like. Human growth hormone increases the total number of red blood cells, resulting in k age In another example, nutritional supplements and drugs that increase metabolic levels (e.g., exercise mimetics such as AMPK agonists) can increase k gly Therefore, some embodiments may be implemented by measuring one or more physiological parameters (k gly , k age , and / or K) can be used as indicators of doping.

[0150] In the first example, one or more physiological parameters (k gly , k age , and / or K) can be used as an indicator of doping in some cases.

[0151] In another example, one or more physiological parameters (k gly , k age Once K and / or K have been determined, continuous monitoring over a period of 10 days or longer could identify sudden changes in physiological parameters that could be indicative of doping. This could be used alone or in combination with the above examples where one or more physiological parameters are outside of the normal range.

[0152] Physiological age Age-related changes in physiological parameters age changes, and as a result, K changes. Therefore, k age and / or K(k gly Assuming a stable or known change in k over time, k can be used as a biomarker to calculate a standard metabolic age. age decreases and K increases. age And / or the correlation between K and age can be used to calculate the metabolic age of a new subject. This metabolic age can then be used as an indicator of the new subject's risk for age-related degenerative conditions, such as heart disease, Alzheimer's disease, or osteoporosis. The risk for an age-related degenerative condition can be used in conjunction with a family history of age-related degenerative conditions for pre-screening and / or preventative treatment. For example, a 54-year-old subject with a metabolic age of 65 and a family history of late-life onset of cardiovascular disease can be screened for signs and / or progression of cardiovascular disease more frequently than a 54-year-old subject with a metabolic age of 50 and a similar family history.

[0153] Sample monitor and monitor system Generally, embodiments of the present disclosure are used in conjunction with or as systems, devices, and methods for measuring glucose and, optionally, at least one other analyte in a bodily fluid. The embodiments described herein can be used to monitor and / or process information about glucose and, optionally, at least one other analyte. Other analytes that can be monitored include, but are not limited to, glucose derivative HbA1c, reticulocyte count, RBC GLUT1 levels, acetylcholine, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glutamine, growth hormone, hormones, ketones, ketone bodies, lactate, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid-stimulating hormone, and troponin. For example, concentrations of drugs such as antibiotics (e.g., gentamicin, vancomycin, and the like), digitoxin, digoxin, drugs of addiction, theophylline, and warfarin can be monitored. In embodiments monitoring glucose and one or more analytes, each of the analytes can be monitored at the same or different times.

[0154] The analyte monitors and / or analyte monitoring systems (collectively referred to herein as analyte monitoring systems) used in conjunction with or as systems, devices, and methods for measuring glucose and optionally one or more analytes in bodily fluids can be in vivo analyte monitoring systems or ex vivo analyte monitoring systems. In some cases, the systems, devices, and methods of the present disclosure can use both in vivo and ex vivo analyte monitoring systems.

[0155] In-vivo analyte monitoring systems include analyte monitoring systems in which at least a portion of an analyte sensor is placed or can be placed on a subject's body to obtain information about at least one analyte in the body. In-vivo analyte monitoring systems can be operated without requiring factory calibration. Examples of in-vivo analyte monitoring systems include, but are not limited to, continuous analyte monitoring systems and intermittent analyte monitoring systems.

[0156] For example, a continuous analyte monitoring system (e.g., a continuous glucose monitoring system) is an in-vivo system that can transmit data repeatedly or continuously from a sensor control device to a reader device without prompting (e.g., automatically according to a schedule).

[0157] For example, an intermittent analyte monitoring system (or intermittent glucose monitoring system or simply an intermittent system) is an in-vivo system that can transmit data from a sensor control device to a reader device in response to scanning or data need by the reader device using near field communication (NFC) or radio frequency identification (RFID) protocols.

[0158] An in-vivo analyte monitor system may include a sensor that contacts a subject's bodily fluid while positioned in vivo and senses the level of one or more analytes contained within the bodily fluid. The sensor may be part of a sensor control device that resides on the subject's body, which includes electronics and a power source that enable and control analyte sensing. Sensor control devices and variations thereof may also be referred to as "sensor control units," "on-body electronics" devices or units, "on-body" devices or units, or "sensor data communication" devices or units, etc. As used herein, these terms are not limited to devices having analyte sensors but include devices having other types of sensors, whether biometric or non-biometric. The term "on-body" refers to either a device that resides directly on the body or in close proximity to the body, such as a wearable device (e.g., eyeglasses, watches, wristbands, neckbands, or necklaces).

[0159] The in-vivo analyte monitoring system may further include one or more reader devices that receive the sensed analyte data from the sensor control device. These reader devices may process and / or display the sensed analyte data to the subject in any number of formats. These devices and variations thereof may be referred to as "handheld reader devices," "reader devices" (or simply "readers"), "handheld electronic devices" (or handhelds), "portable data processing" devices or units, "data receivers," "receiver" devices or units (or simply receivers), "relay" devices or units, or "remote" devices or units, etc. Other devices, such as personal computers, may also be used in conjunction with or incorporated into in-vivo and in-vitro monitoring systems.

[0160] 4, the sensor or portion of the in-vivo analyte monitoring system may be a glucose monitor 424, and the reader device may be a health monitor device 420. In an alternative embodiment, the in-vivo analyte monitoring system may be entirely a glucose monitor 424 that transmits data to a health monitor device 420, a data network 422, a data processing terminal / PC 426, and / or a server / cloud 428.

[0161] In vivo analyte monitoring systems may measure one or more physiological parameters (e.g., k gly , k age (or k gen ), and / or K), and / or other analytical results described herein may, in some cases, be performed within the in-vivo analyte monitor system. For example, only physiological parameters may be determined within the in-vivo analyte monitor system and transmitted to suitable other components of the physiological parameter analysis system, which may perform other analyses described herein. In some embodiments, the in-vivo analyte monitor system may generate only an output signal corresponding to a glucose level received by another component of the physiological parameter analysis system. In such cases, one or more of the other components of the physiological parameter analysis system may determine one or more physiological parameters (e.g., k gly , k age (or k gen ), and / or K), and optionally, perform one or more of the other analyses described herein.

[0162] 9 illustrates an example in-vivo analyte monitor system 960. In an embodiment of the present disclosure, this example in-vivo analyte monitor system 960 monitors glucose and optionally one or more other analytes.

[0163] The in-vivo analyte monitor system 960 includes a sensor control device 962 (which may be at least a part of the glucose monitor 424 of FIG. 4 ) and a reader device 964 (which may be at least a part of the health monitor device 420 of FIG. 4 ) that communicate with each other over a local communication pathway (or communication link) 966, which may be wired or wireless and unidirectional or bidirectional. In embodiments in which the pathway 966 is wireless, communication protocols such as near field communication (NFC) protocols, RFID protocols, BLUETOOTH® or BLUETOOTH® low energy protocols, WiFi protocols, and proprietary protocols may be used, including communication protocols existing as of the date of this application or later-developed variants thereof.

[0164] The reader device 964 (e.g., a dedicated reader, a cellular phone, or a PDA running an application, etc.) also has the capability for wired, wireless, or combinations of communication with a computer system 968 (which may be at least a portion of the data processing terminal / PC 426 in FIG. 4 ) via a communication path (or communication link) 970 and with a network 972, such as the Internet or a cloud (which may be at least a portion of the data network 422 and / or the server / cloud 428 in FIG. 4 ), via a communication path (or communication link) 974. Communication with the network 972 can include communication with a trusted computer system 976 within the network 972 or communication via the network 972 to the computer system 968 via a communication link (or communication path) 978. Communication paths 970, 974, and 978 can be wireless, wired, or both, can be unidirectional, bidirectional, and can be part of a long-distance communication network such as a Wi-Fi network, a local area network (LAN), a wide area network (WAN), the Internet, or other data network. In some cases, communication paths 970 and 974 can be the same path. All communications over paths 966, 970, and 974 can be encrypted, and each of sensor control device 962, reader device 964, computer system 968, and trusted computer system 976 can be configured to encrypt and decrypt these transmitted and received communications.

[0165] Variations of devices 962 and 964, as well as other components of in vivo-based analyte monitor systems suitable for use in conjunction with the system, device, and method embodiments described herein, are described in U.S. Patent Application Publication No. 2011 / 0213225 ('225), the entire contents of which are incorporated herein by reference for all purposes.

[0166] The sensor control device 962 can include a housing 980 that encloses the in vivo analyte monitor circuitry and a power source. In this embodiment, the in vivo analyte monitor circuitry is electrically connected to an analyte sensor 982 that extends through an adhesive patch 984 and protrudes away from the housing 980. The adhesive patch 984 includes an adhesive layer (not shown) for attachment to the skin surface of a subject's body. Other forms of body attachment to the body can be used in addition to or instead of an adhesive.

[0167] The sensor 982 is adapted to be at least partially inserted into a subject's body, where it is in fluid contact with the subject's bodily fluids (e.g., subcutaneous (subdermal) fluid, dermal fluid, or blood) and can be used in conjunction with in-vivo analyte monitor circuitry to measure analyte-related data from the subject. The sensor 982 and any associated sensor control electronics can be affixed to the body in any desired manner. For example, an insertion device (not shown) can be used to position all or a portion of the analyte sensor 982 through the outer surface of the subject and in contact with the subject's bodily fluids. The insertion device can then position the sensor control device 962 on the skin using an adhesive patch 984. In other embodiments, the insertion device can first position the sensor 982 and then later couple the associated sensor control electronics to the sensor 982, either manually or using a mechanical device. Examples of insertion devices are described in U.S. Patent Application Publication Nos. 2008 / 0009692, 2011 / 0319729, 2015 / 0018639, 2015 / 0025345, and 2015 / 0173661, the entire contents of all of which are incorporated herein by reference for all purposes.

[0168] After collecting raw data from the subject's body, the sensor control device 962 can apply analog signal conditioning to the data, transforming it into conditioned raw data in digital form. In some embodiments, this conditioned raw data can be encoded for transmission to another device (e.g., reader device 964), which then algorithmically processes the digital raw data into a final form representative of the subject's measured biometric (e.g., a form that is readily processed for display to the subject or a form that is readily used by analysis module 420B of FIG. 4). This algorithmically processed data can then be formatted or graphically processed for digital display to the subject. In other embodiments, the sensor control device 962 algorithmically processes the digital raw data into a final form representative of the subject's measured biometric (e.g., analyte level), which then encodes and wirelessly transmits this data to the reader device 964, which can then format or graphically process the received data for digital display to the subject. In other embodiments, the sensor control device 962 may graphically process the data in its final form so that it is ready for display and display this data on the display of the sensor control device 962 or transmit it to the reader device 964. In some embodiments, the biometric data in its final form is used by the system (e.g., incorporated into a diabetes monitoring plan) without processing for display to the subject (prior to graphical processing). In some embodiments, the sensor control device 962 and the reader device 864 transmit the raw digital data to another computer system for algorithmic processing and display.

[0169] Reader device 964 may include a display 986 for outputting information to the subject (e.g., one or more physiological parameters or an output derived therefrom, such as cHbA1c) and / or receiving input from the subject, and optional input components 988 (or more) such as buttons, actuators, touch-sensitive switches, capacitive switches, pressure-sensitive switches, jog wheels, etc. for inputting data, commands, or otherwise controlling operation of reader device 964. In certain embodiments, display 986 and input components 988 may be integrated into a single component, e.g., where the display is capable of measuring the presence and location of physical contact touches on the display, such as in a touchscreen subject interface (which may be at least a portion of subject interface 420A in FIG. 4). In certain embodiments, input component 988 of reader device 964 may include a microphone, and reader device 964 may include software configured to analyze audio input received from the microphone, such that functions and operation of reader device 964 may be controlled by voice commands. In certain embodiments, the output components of the reader device 964 include a speaker (not shown) for outputting information as an audible signal. Similar audio response components, such as a speaker, microphone, and software routines for generating, processing, and storing audio drive signals, can be included within the sensor control device 962.

[0170] The reader device 964 may further include one or more data communication ports 990 for wired data communication with external devices, such as a computer system 968. Exemplary data communication ports 990 include, but are not limited to, a USB port, a mini-USB port, a USB Type-C port, a USB micro-A port and / or a USB micro-B port, an RS-232 port, an Ethernet port, a Fireline port, or other similar data communication port configured to connect to a compatible data cable. The reader device 964 may further include an integrated or attachable in vitro glucose meter that includes an in vitro test strip port (not shown) for accepting in vitro test strips to perform in vitro blood glucose measurements.

[0171] The reader device 964 can display the measured biometric data wirelessly received from the sensor control device 962 and can be configured to output alerts (e.g., visual alerts on a display, audible alerts, or a combination thereof), warning notifications, glucose levels, etc., which can be visual, audible, tactile, or any combination thereof. Further details and other display embodiments can be found, for example, in U.S. Patent Application Publication No. 2011 / 0193704, the entire contents of which are incorporated herein by reference for all purposes.

[0172] The reader device 964 can act as a data conduit for communicating measurement data from the sensor control device 962 to the computer system 968 or the trusted computer system 976. In certain embodiments, data received from the sensor control device 962 can be stored (permanently or temporarily) in one or more memories of the reader device 964 before being uploaded to the computer system 968, the trusted computer system 976, or the network 972.

[0173] The computer system 968 may be a personal computer, a server terminal, a laptop computer, a tablet, or other suitable data processing device. The computer system 968 may be (or include) software for managing and analyzing data and communicating with components within the analyte monitor system 960. The computer system 968 may be used by a subject, a medical professional, or other user to display and / or analyze biometric data measured by the sensor control device 962. In some embodiments, the sensor control device 962 may communicate the biometric data directly to the computer system 968 without an intermediary such as the reader device 964, or indirectly using an internet connection (optionally also without first sending the data to the reader device 964). The operation and use of the computer system 976 is described in more detail in the incorporated '225 patent. The analyte monitor system 960 may also be configured to cooperate with a data processing module (not shown), also described in the incorporated '225 patent.

[0174] The trusted computer system 976 may be owned by the manufacturer or distributor of the sensor control device 962, connected through a secure connection, either physically or virtually, and may be used to authenticate the sensor control device 962 for secure storage of the subject's biometric data and / or as a server providing data analysis programs (e.g., accessible through a web browser) for performing analysis on the subject's measurement data.

[0175] An in vivo analyte monitoring system can be used in conjunction with or part of an integrated diabetes management system. For example, an integrated diabetes management system can include an in vivo analyte monitoring system and a nutritional supplement / drug delivery system, more specifically an in vivo glucose monitoring system and an insulin delivery system (e.g., an insulin pump). An integrated diabetes management system can be closed-loop, open-loop, or a hybrid of these. A closed-loop system provides complete control over analyte monitoring time and the amount and time of nutritional supplement / drug administration. An open-loop system allows the subject complete control over analyte monitoring time and the amount and time of nutritional supplement / drug administration. A hybrid system relies primarily on a closed-loop system approach but can allow for subject involvement.

[0176] In vitro analyte monitor systems contact bodily fluids outside the body. In some cases, the in vitro analyte monitor system includes a metering device having a port for receiving a subject's bodily fluid (e.g., on an analyte test strip / swab or by collection of the bodily fluid) that can be analyzed to determine the subject's analyte level.

[0177] Exemplary Embodiments A first non-limiting exemplary embodiment of the present disclosure comprises: (1) a plurality of first glucose levels; and (2) a test HbA1c level (e.g., one or more test HbA1c levels) using a model that accounts for intermembrane glucose transport and glycation. Erythrocyte glycation rate constant (k gly ), the erythrocyte development rate constant (k gen ), red blood cell removal constant (k age), and an apparent glycation constant (K); receiving (and / or measuring) a plurality of second glucose levels for the subject over a period of time; and deriving (e.g., using Equation 9) a calculated HbA1c (cHbA1c) level for the subject based on the at least one physiological parameter and the plurality of second glucose levels. A first non-limiting exemplary embodiment is characterized in that: Element 1: the method further includes diagnosing, treating, and / or monitoring the subject based on the cHbA1c level; Element 2: element 1 and treating the subject are performed, and the step of treating the subject includes administering and / or adjusting an insulin dose, a glycosylation drug dose, an exercise regime, a dietary intake, or a combination thereof; Element 3: the method further includes displaying the cHbA1c level (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the plurality of first and / or second glucose levels are measured, etc.); Element 4: the method further includes comparing the cHbA1c level with the k age The standard k is set as age (k ref age Element 5: The method further includes calculating (e.g., using Equation 10) an adjusted HbA1c (aHbA1c) for the subject based on the cHbA1c level and a reference K (K refelement 6: element 5 or element 6 and the method further comprises diagnosing, treating, and / or monitoring the subject based on the aHbA1c level; element 7: element 6 and the step of treating the subject is performed and includes administering and / or adjusting an insulin dosage, a glycation drug dosage, an exercise regime, dietary intake, or a combination thereof; element 8: element 5 or element 6 and the method further comprises diagnosing, treating, and / or monitoring the subject based on the cHbA1c level and / or aHbA1c level; Element 9: The method further includes a step of displaying a personalized target glucose range (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the plurality of first and / or second glucose levels are measured, etc.), element 5: The method further includes a step of displaying a personalized target glucose range (e.g., using Equations 13 and 15) based on the aHbA1c level and the test HbA1c level, a step of displaying a personalized target glucose range (e.g., using Equation 15), a step of displaying a personalized upper glucose limit (e.g., using Equation 16), and / or a step of displaying a personalized lower glucose limit (e.g., using Equation 17). Element 10: Element 9 and the method further include diagnosing, treating, and / or monitoring the subject based on the personalized-target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit; Element 11: Element 10 and the step of treating the subject is performed, and includes administering and / or adjusting an insulin dose, a glycation medication dose, an exercise regime, dietary intake, or a combination thereof; Element 12: Element 9 and the method further include diagnosing, treating, and / or monitoring the subject based on the personalized-target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit; and further including the step of displaying (e.g., on system 310, on system 410, on the glucose metering device, and / or on the closed-loop insulin pump system where the plurality of first and / or second glucose levels are measured, etc.); element 13: receiving a glucose level for the subject after element 9 and the method have derived the personalized-target glucose range, personalized upper glucose limit, and / or lower glucose limit; and receiving a glucose level for the subject after element 9 and the method have derived the personalized-target glucose range, personalized upper glucose limit, and / or lower glucose limit; andand displaying an alarm (visually, audibly, and / or tactilely (touch-related)) when the glucose level is greater than the personalized upper glucose limit and / or less than the personalized lower glucose limit; element 14: element 5 or element 6 and the method further including deriving a personalized-target average glucose (e.g., using Equation 18, Equation 19, or Equation 20); element 15: element 14 and the method further including diagnosing, treating, and / or monitoring the subject based on the personalized-target average glucose; element 16: Element 15 and the step of treating the subject is performed, and includes administering and / or adjusting an insulin dose, a glycation drug dose, an exercise regime, a dietary intake, or a combination thereof; Element 17: Element 14 and the method further includes displaying the personalized-target average glucose (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the plurality of first and / or second glucose levels are measured, etc.); Element 18: Element 5 or element 6 and the method further comprises one or more of the steps of deriving a personalized therapy for subject triage based at least in part on the aHbA1c level, deriving a personalized therapy for diabetic drug titration, deriving a personalized closed-loop or hybrid closed-loop control system, deriving a personalized therapy using glycation medication, identifying abnormal or pathological physiological conditions, identifying nutritional supplements and / or medications present during the test, and identifying physiological age; element 19: the method further comprises one or more of the steps of deriving a personalized therapy for subject triage based at least in part on the cHbA1c level, deriving a personalized therapy for diabetic drug titration, deriving a personalized closed-loop or hybrid closed-loop control system, deriving a personalized therapy using glycation medication, identifying abnormal or pathological physiological conditions, identifying nutritional supplements and / or medications present during the test, and identifying physiological age; element 20: the method further comprises k, gly The standard k is set as gly (k refgly ), deriving a personalized-target glucose range (e.g., using Equation 12 and Equation 14), deriving a personalized upper glucose limit (e.g., using Equation 14), and / or deriving a personalized lower glucose limit (e.g., using Equation 12); element 21: element 20 and the method further include diagnosing, treating, and / or monitoring the subject based on the personalized-target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit; element 22: element 21 and the step of treating the subject is performed, and includes administering and / or adjusting an insulin dose, a glycation drug dose, an exercise regime, a dietary intake, or a combination thereof; element 23: element 20 and the method further include diagnosing, treating, and / or monitoring the subject based on the personalized-target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit; element 24: receiving a glucose level for the subject after element 20 and the method have derived a personalized-target glucose range, a personalized upper glucose limit, and / or a personalized lower glucose limit; and displaying (visually, audibly, and / or tactilely (touch-related)) an alert when the glucose level is outside the personalized-target glucose range, greater than the personalized upper glucose limit, and / or less than the personalized lower glucose limit; element 25: the method further includes receiving a glucose level for the subject after element 20 and the method have derived a personalized-target glucose range, a personalized upper glucose limit, and / or a personalized lower glucose limit (e.g., on system 310, on system 410, on the glucose metering device, and / or on a closed-loop insulin pump system where the plurality of first and / or second glucose levels are measured). gly The standard k is set as gly (k ref gly) and the measured glucose level (e.g., using Equation 16 or Equation 17); element 26: element 25 and the method further include diagnosing, treating, and / or monitoring the subject based on the personalized glucose level (e.g., the personalized glucose level compared to a current acceptable glucose range or the intracellular glucose level compared to a current acceptable intracellular glucose level range (i.e., LIGL-UIGL)); element 27: element 26 and the step of treating the subject are performed, and the step of treating the subject is performed by adjusting the insulin dosage, glycation drug dosage, exercise regime, dietary intake, or a combination thereof. The method may further include one or more of the following features: the step of administering and / or adjusting the glucose level; element 28: element 25 and the method further including a step of displaying the personalized glucose level (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the multiple first and / or second glucose levels are measured); and element 29: element 25 and the method further including a step of displaying an alert (visually, audibly, and / or tactilely (touch-related)) when the personalized glucose level is outside of each current acceptable glucose range.

[0178] A second non-limiting exemplary embodiment of the present disclosure includes receiving (and / or measuring) a plurality of first glucose levels for a subject over a first period of time, and receiving (and / or measuring) a first glycated hemoglobin (HbA1c) level for the subject corresponding to an end of the first period of time; (1) a plurality of first glucose levels and (2) a first test HbA1c level using a model that accounts for intermembrane glucose transport and glycation. Erythrocyte glycation rate constant (k gly ), the erythrocyte development rate constant (k gen ), red blood cell removal constant (k age), and an apparent glycation constant (K); receiving (and / or measuring) a plurality of second glucose levels for the subject over a second period of time; and deriving (e.g., using Equation 9) a calculated HbA1c (cHbA1c) level based on the at least one physiological parameter and the plurality of second glucose levels. Measuring the glucose level may include collecting a body fluid from the subject using an analyte sensor and measuring a plurality of first glucose levels using the analyte sensor. A second non-limiting exemplary embodiment may further include one or more of elements 1 through 29.

[0179] A third non-limiting exemplary embodiment of the present disclosure is a monitor device including an analyte sensor configured to measure glucose levels in a bodily fluid, and one or more processors, and a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of the first or second non-limiting exemplary embodiment, optionally including one or more of elements 1 through 29.

[0180] A fourth non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system including an analyte sensor configured to measure glucose levels in a bodily fluid, an insulin pump, one or more processors, and a monitor device including a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of the first or second non-limiting exemplary embodiment (optionally including one or more of elements 1 through 29), wherein, when a therapy is administered, the therapy includes administering an insulin dose through the closed-loop insulin pump system.

[0181] A fifth non-limiting exemplary embodiment includes steps of receiving (and / or measuring) a test HbA1c level (e.g., one or more test HbA1c levels) for a subject, and measuring a red blood cell turnover rate (k) for the subject. age ) (e.g., using a model that accounts for transmembrane glucose transport and glycation), and determining HbA1c levels and k age The standard k is set as age (k ref ageand calculating (e.g., using Equation 10) an adjusted HbA1c (aHbA1c) for the subject based on the aHbA1c level. Yet another embodiment is a method comprising: element 30: the method further comprising diagnosing, treating, and / or monitoring the subject based on the aHbA1c level; element 31: element 30 and treating the subject are performed, and the step of administering and / or adjusting an insulin dose, a glycation drug dose, an exercise regime, dietary intake, or a combination thereof; element 32: the method displays the aHbA1c level (e.g., on system 310, on system 410, on a glucose metering device, and / or on a plurality of first and / or second element 33: the method further includes deriving a personalized-target glucose range based on the aHbA1c level and the test HbA1c (e.g., using Equations 13 and 15), deriving a personalized upper glucose limit (e.g., using Equation 15), and / or deriving a personalized lower glucose limit (e.g., using Equation 13); element 34: the method includes combining element 33 and the method to derive a personalized-target glucose range based on the aHbA1c level and the test HbA1c (e.g., using Equation 14), and further comprising diagnosing, treating, and / or monitoring the subject based on the personalized target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit; element 35: the feature where element 34 and treating the subject are performed and include administering and / or adjusting an insulin dose, a glycolytic drug dose, an exercise regime, a dietary intake, or a combination thereof; element 36: element 33 and the method further comprising displaying (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the plurality of first and / or second glucose levels are measured, etc.); element 37: element 36 and the method further comprising receiving a glucose level for the subject after deriving the personalized target glucose range, the personalized upper glucose limit, and / or the personalized lower glucose limit; andand / or displaying an alarm (visually, audibly, and / or tactilely (touch-related)) when the glucose level is below the personalized glucose lower limit; element 38: the method further includes deriving a personalized-target average glucose (e.g., using Equation 18, Equation 19, or Equation 20); element 39: element 38 and the method further include diagnosing, treating, and / or monitoring the subject based on the personalized-target average glucose; element 40: element 39 and the step of treating the subject is performed, and includes administering and / or adjusting an insulin dose, a glycation drug dose, an exercise regime, dietary intake, or a combination thereof; element 41: element 38 and the method further includes displaying the personalized-target average glucose (e.g., by displaying the personalized-target average glucose on the system); element 42: the method further includes one or more of the steps of deriving a personalized therapy for subject triage, deriving a personalized therapy for diabetic drug titration, deriving a personalized closed-loop or hybrid closed-loop control system, deriving a personalized therapy using glycation medication, identifying abnormal or pathological physiological conditions, identifying nutritional supplements and / or medications present during the test, and identifying physiological age based at least in part on the aHbA1c level; element 43: the method further includes one or more of the steps of: gly The standard k is set as gly (k ref gly) and the measured glucose level (e.g., using Equation 16 or Equation 17); element 44: element 43 and the method further includes diagnosing, treating, and / or monitoring the subject based on the personalized glucose level (e.g., the personalized glucose level compared to a current acceptable glucose range or the intracellular glucose level compared to a current acceptable intracellular glucose level range (i.e., LIGL-UIGL)); element 45: element 44 and the step of treating the subject are performed, and the step of treating the subject is performed by adjusting the insulin dosage, glycation drug dosage, exercise regime, dietary intake, or a combination thereof. The method may further include one or more of the following features: the step of administering and / or adjusting the glucose level; element 46: element 43 and the method further including a step of displaying the personalized glucose level (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the multiple first and / or second glucose levels are measured); and element 47: element 43 and the method further including a step of displaying an alert (visually, audibly, and / or tactilely (touch-related)) when the personalized glucose level is outside of each current acceptable glucose range.

[0182] A sixth non-limiting exemplary embodiment includes receiving (and / or measuring) a test HbA1c level for a subject (e.g., one or more test HbA1c levels), determining an apparent glycation constant (K) for the subject (e.g., using a model that accounts for transmembrane glucose transport and glycation), and comparing the HbA1c level with a reference K (K) defined as K. ref and calculating (e.g., using Equation 11) an adjusted HbA1c (aHbA1c) for the subject based on the HbA1c (aHbA1c) and the ...

[0183] A seventh non-limiting exemplary embodiment includes receiving (and / or measuring) a plurality of first glucose levels for a subject over a first time period; receiving (and / or measuring) a first glycated hemoglobin (HbA1c) level for the subject corresponding to the end of the first time period; and determining a red blood cell glycation rate constant (k ) based on (1) the plurality of first glucose levels and (2) the first test HbA1c level using a model that accounts for intermembrane glucose transport and glycation. gly ), the erythrocyte development rate constant (k gen ), red blood cell removal constant (k age determining at least one physiological parameter for the subject selected from the group consisting of HbA1c level and k age The standard k is set as age (k ref age and calculating (e.g., using Equation 10) an adjusted HbA1c (aHbA1c) for the subject based on the HbA1c (aHbA1c) and the adjusted HbA1c (aHbA1c) for the subject based on the HbA1c (aHbA1c). Measuring the glucose level may include collecting a body fluid from the subject using an analyte sensor, and measuring a plurality of first glucose levels using the analyte sensor. A second non-limiting exemplary embodiment may further include one or more of elements 30 through 47.

[0184] An eighth non-limiting exemplary embodiment includes receiving (and / or measuring) a plurality of first glucose levels for a subject over a first time period; receiving (and / or measuring) a first glycated hemoglobin (HbA1c) level for the subject corresponding to the end of the first time period; and determining a red blood cell glycation rate constant (k ) based on (1) the plurality of first glucose levels and (2) the first test HbA1c level using a model that accounts for intermembrane glucose transport and glycation. gly ), the erythrocyte development rate constant (k gen ), red blood cell removal constant (k age determining at least one physiological parameter for the subject selected from the group consisting of HbA1c level and a reference K (K) defined as K; refand calculating (e.g., using Equation 11) an adjusted HbA1c (aHbA1c) for the subject based on the HbA1c (aHbA1c) and the adjusted HbA1c (aHbA1c) for the subject based on the HbA1c (aHbA1c). Measuring the glucose level may include collecting a body fluid from the subject using an analyte sensor and measuring a plurality of first glucose levels using the analyte sensor. A second non-limiting exemplary embodiment may further include one or more of elements 30 through 47.

[0185] A ninth non-limiting exemplary embodiment of the present disclosure is a monitor device including an analyte sensor configured to measure glucose levels in a bodily fluid, one or more processors, and a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of the fifth, sixth, seventh, or eighth non-limiting exemplary embodiment (optionally including one or more of elements 30 through 47).

[0186] A tenth non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system including an analyte sensor configured to measure glucose levels in a bodily fluid, an insulin pump, one or more processors, and a monitor device including a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of the fifth, sixth, seventh, or eighth non-limiting exemplary embodiment (optionally including one or more of elements 30 through 47), wherein, when a therapy is administered, the therapy includes administering an insulin dose through the closed-loop insulin pump system.

[0187] An eleventh non-limiting exemplary embodiment of the present disclosure uses a model that accounts for intermembrane glucose transport and glycation to calculate a red blood cell glycation rate constant (k ) based on (1) a plurality of first glucose levels and (2) test HbA1c levels (e.g., one or more test HbA1c levels). gly ), the erythrocyte development rate constant (k gen ), red blood cell removal constant (k agedetermining at least one physiological parameter for the subject selected from the group consisting of: a glucose concentration (C), an apparent glycation constant (K), and an apparent glycation constant (K); receiving (and / or measuring) a plurality of second glucose levels for the subject over a period of time; and k gly The standard k is set as gly (k ref gly deriving a personalized glucose level based on the measured glucose level (e.g., using Equation 16 or Equation 17). An eleventh non-limiting exemplary embodiment can further include one or more of the following features: element 50: the method further includes diagnosing, treating, and / or monitoring the subject based on the personalized glucose level (e.g., the personalized glucose level compared to a current acceptable glucose range or the intracellular glucose level compared to a current acceptable intracellular glucose level range (i.e., LIGL-UIGL)); element 51: the feature where element 50 and treating the subject are performed and include administering and / or adjusting an insulin dose, a glycation drug dose, an exercise regime, dietary intake, or a combination thereof; element 52: the method further includes displaying the personalized glucose level (e.g., on system 310, on system 410, on a glucose metering device, and / or on a closed-loop insulin pump system where the multiple first and / or second glucose levels are measured, etc.); element 53: the method further includes displaying an alert (visually, audibly, and / or tactilely (touch-related)) when the personalized glucose level is outside each of the current acceptable glucose ranges.

[0188] A twelfth non-limiting exemplary embodiment of the present disclosure includes receiving (and / or measuring) a plurality of first glucose levels for a subject over a first period of time; receiving (and / or measuring) a first glycated hemoglobin (HbA1c) level for the subject corresponding to the end of the first period of time; and determining a red blood cell glycation rate constant (k ) based on (1) the plurality of first glucose levels and (2) the first test HbA1c level using a model that accounts for transmembrane glucose transport and glycation. gly), the erythrocyte development rate constant (k gen ), red blood cell removal constant (k age determining at least one physiological parameter for the subject selected from the group consisting of: a glucose concentration (K), an apparent glycation constant (K), and an apparent glycation constant (K); receiving (and / or measuring) a measured glucose level; and k gly The standard k is set as gly (k ref gly and deriving a personalized glucose level based on (e.g., using Equation 16 or Equation 17) the measured glucose level. Measuring the glucose level can include collecting bodily fluid from the subject using an analyte sensor and measuring a plurality of first glucose levels using the analyte sensor. A second non-limiting exemplary embodiment can further include one or more of elements 50 through 53.

[0189] A thirteenth non-limiting exemplary embodiment of the present disclosure is a monitor device including an analyte sensor configured to measure glucose levels in a bodily fluid, one or more processors, and a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of the eleventh or twelfth non-limiting exemplary embodiment, optionally including one or more of elements 50 through 53.

[0190] A fourteenth non-limiting exemplary embodiment of the present disclosure is a closed-loop insulin pump system including an analyte sensor configured to measure glucose levels in a bodily fluid, an insulin pump, one or more processors, and a monitor device including a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of the eleventh or twelfth non-limiting exemplary embodiment (optionally including one or more of elements 50 through 53), wherein, when a therapy is administered, the therapy includes administering an insulin dose through the closed-loop insulin pump system.

[0191] Unless otherwise indicated, all numbers expressing quantities and the like in the specification and appended claims are to be understood as being modified in all instances by the term "about." Accordingly, unless indicated to the contrary, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the embodiments of the present disclosure. At the very least, and without intending to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques.

[0192] This specification provides one or more exemplary embodiments incorporating various features. For purposes of clarity, this application does not describe or show all features of a physical implementation. It is understood that in developing a physical implementation incorporating an embodiment of the present disclosure, many implementation-specific decisions must be made to achieve the developer's goals, such as compliance with system-related, business-related, government-related, and other constraints that vary from implementation to implementation and change from time to time. While the developer's efforts may be time-consuming, such efforts are nevertheless routine for one of ordinary skill in the art having the benefit of this disclosure.

[0193] Although various systems, tools, and methods are described herein in terms of "comprising" various components or steps, the systems, tools, and methods may "essentially consist of" or "consist of" the various components and steps.

[0194] As used herein, the phrase "at least one of," preceding a series of items with the word "and" or "or" separating any of the items, modifies the list as a whole, rather than each member (i.e., each item) of the list. The phrase "at least one of" allows for a meaning including at least one of any one of the items, at least one of any combination of the items, and / or at least one of each of the items. As an example, "at least one of A, B, and C" or "at least one of A, B, or C" each means A only, B only, or C only, any combination of A, B, and C, and / or at least one of each of A, B, and C.

[0195] In order to facilitate a clearer understanding of embodiments of the present invention, the following examples of preferred or representative embodiments are provided. The following examples should not be read in any way as limiting or defining the scope of the present invention. [Example]

[0196] Example 1 The model described herein was validated using 200 days of glucose monitoring data and three HbA1c values ​​for a single patient. Figure 10 is a plot of 200 days of glucose monitoring data (right y-axis), three HbA1c values ​​(left y-axis), and estimated HbA1c values ​​(left y-axis) based on the 14-day eHbA1c model. As shown, the estimated HbA1c derived from the 14-day HbA1c model changed very dramatically over time. However, it is unlikely that HbA1c can change at this rate.

[0197] FIG. 11 shows the results of the method described herein. gly and k age FIG. 11 is the plot of FIG. 10 with cHbA1c (left y-axis) over the first 100 days determined using

[0198] FIG. 12 shows the k determined in relation to FIG. 11 by the method described herein. gly and kage 12 is a plot of the plot of FIG. 11 with cHbA1c over the next 100 days (extending from day 100 to day 200, left y-axis) using the method described herein. In this manner, the third HbA1c value is not taken into account, and the model described herein predicts the measured value of the third HbA1c value, thereby illustrating that the model described herein closely matches reality.

[0199] The same procedure as above was performed on the larger dataset of Table 1, and the 14-day glucose model also predicted HbA1c levels. Figure 13A is a cross-plot comparison of predicted HbA1c levels (by the 14-day glucose model) compared to test HbA1c levels, and Figure 13B is a cross-plot comparison of cHbA1c levels (by the method described herein) compared to test HbA1c levels. The 14-day glucose model had an R 2 value, whereas the method described herein has an R value of 0.88. 2 values, thereby illustrating a reduction in variation of about 50%. TIFF0007770316000029.tif50161

[0200] Example 2 HbA1c was calculated using continuous glucose monitor (CGM) and laboratory HbA1c data from 139 patients with type 1 diabetes and 148 patients with type 2 diabetes enrolled in two previous European clinical studies, as detailed below. Both studies were conducted after appropriate ethical approval, and participants provided written informed consent. A total of 6 months of CGM data was collected using a sensor-based intermittent glucose monitoring system (FREESTYLE LIBRE®, Abbott Diabetes Care, Witney, UK), while HbA1c was measured by a central laboratory (ICON Laboratories, Dublin, Ireland) at 0, 3, and 6 months of the study. Analysis was performed with a minimum of 80% CGM coverage and no glucose data gaps longer than 12 hours.

[0201] RBC clearance due to aging and eryptosis is a complex process known to vary within and between individuals. Previous studies have attempted to address mean RBC age variation to accurately reflect HbA1C. However, these studies did not adjust for potential differences in RBC transmembrane glucose absorption rates. The inventors constructed a model that considers both RBC turnover rate and RBC transmembrane glucose absorption rate by applying a recently published model (Xu Y, Dunn TC, Ajjan RA. "A kinetic model for glucose levels and hemoglobin A1C provides a novel tool for individualized diabetes management." J Diab Sci Tech. 2020, DOI: 10.1177 / 1932296819897613, hereinafter "Xu Y et al. 2020"). For all analyses, the inventors used the Python / SciPy software package to calculate the RBC glucose transmembrane absorption rate (k) as previously described in Xu Y et al. 2020. gly ) and RBC turnover (k age The inventors then adapted this model for potential clinical use by constructing aHbA1c that takes into account RBC turnover rate according to Equation 1 above.

[0202] Under the assumption of an individually constant RBC lifespan, the RBC turnover rate (k age ) and RBC lifespan (L RBC ) and mean RBC age (MA RBC ) the relationship between them can be expressed by a simple formula: Interconversions can be made using JPEG0007770316000030.jpg1150. Thus, a standard RBC turnover rate of 1% / day is equivalent to an RBC lifespan of 100 days and a mean RBC age of 50 days. Note that modulation is not symmetric; shortening RBC lifespan corresponds to a greater aHbA1c modulation than an equivalent increase in RBC lifespan.

[0203] Figure 14 is a plot comparing test HbA1c with aHbA1c ("aA1c") due to RBC lifespan. Each individual (circle: type 1 diabetes, n=18; diamond: t, n=32) is represented by two dots, one hollow (test HbA1c) and one solid (aHbA1c). Hollow squares represent similar test A1c but different aA1c with variable RBC lifespan (solid squares). Conversely, hollow stars represent different test HbA1c but similar aHbA1c (solid star).

[0204] A dataset from 50 individuals (18 with type 1 diabetes and 32 with type 2 diabetes) met the specified criteria for calculating RBC lifespan. The mean age of participants was 54 years (range 21-77 years), and 18 of these participants (36%) were women. The mean RBC lifespan was 92 days, ranging from 56 to 166 days. Of the individuals surveyed, 68% had aHbA1C values ​​that differed from their laboratory HbA1C by more than 1.0% (11.0 mmol / mol) (Figure 14). At the individual level, two similar laboratory HbA1C values ​​(7.7% and 7.6% squares) showed aHbA1C values ​​of 6.5% and 10.2%, respectively (along with different RBC lifespans), indicating different future diabetic complication risks. In contrast, individuals with different test HbA1c values ​​(8.8% and 6.6% asterisks) revealed identical aHbA1c values ​​of 7.9%, placing them at similar risk for diabetic complications but potentially different risk of hypoglycemia secondary to treatment escalation, which is likely in patients with a test HbA1c of 8.8%. Generally, individuals with an RBC lifespan of 86–113 days show relatively small differences between adjusted and test HbA1c (<1.0% when test HbA1c is <8%). However, in individuals with an RBC lifespan of <83 days, aHbA1c values ​​were higher than test HbA1c by a median of 2.6%, indicating that these individuals may be undertreated and therefore at higher risk for non-transient hyperglycemia and diabetic complications. Conversely, individuals with an RBC lifespan >113 days had aHbA1c that was a median of 1.4% lower than the laboratory value, thus placing some of these patients at risk for overtreatment and acute onset of hypoglycemia (Figure 14).

[0205] Variations in RBC lifespan and transmembrane glucose absorption rates between individuals can lead to different test HbA1c values ​​despite similar hyperglycemic exposure of organs affected by diabetic complications. To personalize care and assess individual risk of hyperglycemic complications, test HbA1c levels must be adjusted to account for variations in RBC turnover using the aHbA1c proposed by the inventors. Without this adjustment, there is a risk of overestimating glucose levels, which could lead to hypoglycemia through unnecessary intensification of diabetic treatment, or alternatively, underestimating glucose levels, which could result in undertreatment and subsequent higher risk of complications. In addition, when diagnosis is based solely on test HbA1c, misclassification can occur due to variable RBC lifespan across individuals, making prediabetes and diabetes diagnosis more likely.

[0206] In conclusion, quantitative aHbA1c derived from laboratory HbA1c and CGM readings has the potential to more accurately assess intracellular blood glucose exposure and provide safer and more effective blood glucose guidance for the management of individuals with diabetes. In this study, the inventors chose a standard RBC age of 100 days to adjust laboratory HbA1c, but further studies are needed to improve the accuracy of this adjustment and establish the best means. Clinical studies using a larger number of individuals are needed to further validate the accuracy of the model and correlate aHbA1c with diabetic complications and hypoglycemic exposure.

[0207] Example 3 To calculate aHbA1c, we evaluated continuous glucose monitor (CGM) and laboratory HbA1c data from 139 patients with type 1 diabetes and 148 patients with type 2 diabetes enrolled in two previous European clinical studies [10, 11], as detailed below. Both studies were approved by appropriate ethical review, and participants provided written informed consent. A total of 6 months of CGM data was collected using a sensor-based intermittent glucose monitoring system (FreeStyle Libre®, Abbott Diabetes Care, Witney, UK), while HbA1c was measured by a central laboratory (ICON Laboratories, Dublin, Ireland) at 0, 3, and 6 months of the study. For T1D participants, the mean age was 44 years (range 18–70 years), and 17 (33%) of these participants were women. For T2D, the mean age was 59 years (range 33–77 years), and 28 (35%) of these participants were women.

[0208] To support high-quality estimation of the dynamic model parameters, the analysis required a minimum of 70% CGM coverage and no gaps in the glucose data longer than 48 hours. Each had at least one data section consisting of two HbA1c measurements connected by CGM data. Furthermore, parameters were successfully estimated for individuals with sufficient daily glucose variability as evidenced by convergence of the model fit of RBC lifespan between 50 and 180 days.

[0209] RBC clearance due to aging and red blood cell eryptosis is a complex process known to vary within and between individuals. Previous studies have attempted to address mean RBC age variation to accurately reflect HbA1C. However, these studies did not adjust for potential differences in RBC transmembrane glucose absorption rates. We constructed a model that takes into account both RBC turnover rate and RBC transmembrane glucose absorption rates by adapting our recently published model. We used the Python / SciPy software package for all analyses to calculate the RBC transmembrane glucose absorption rate (k) as previously described in [9]. gly ) and RBC turnover (k age ) was determined. Then, the inventors determined that HbA1c (%) is the test HbA1c and k age is the individual's RBC turnover rate (% / day), and k ref age This model was adapted for potential clinical use by constructing aHbA1c as a function of RBC turnover rate as in Equation 1 above, where aHbA1c is the standard RBC turnover rate (1% / day).

[0210] Under the assumption of an individually constant RBC lifespan, the RBC turnover rate (k age ) and RBC lifespan (L RBC ) and mean RBC age (MA RBC ) can be expressed by a simple formula: Interconversions can be made using JPEG0007770316000031.jpg1150. Thus, a standard RBC turnover rate of 1% / day is equivalent to an RBC lifespan of 100 days and a mean RBC age of 50 days. Note that modulation is not symmetric; shortening RBC lifespan corresponds to a greater aHbA1c modulation than an equivalent increase in RBC lifespan.

[0211] Of the 287 subjects in the initial study, 218 had sufficient CGM coverage between at least two HbA1c measurements. Among these subjects, 131 individuals (51 with type 1 diabetes and 80 with type 2 diabetes) had sufficient glucose differentials for the model to determine estimates for RBC lifespan and transmembrane glucose transport rates. The mean (median, range) RBC lifespan was 94 (100, 57–125) days for individuals with T1D and 92 (100, 56–151) days for individuals with T2D (Figure 15). In this homogeneous population, the mean difference between aHbA1c and laboratory HbA1c was 6.6 mmol / mol (0.60%) for T1D subjects and 9.7 mmol / mol (0.88%) for T2D subjects. The corresponding standard deviations were 17 mmol / mol (1.5%) and 19 mmol / mol (1.7%), respectively.

[0212] Translating these results into a clinical context, Figure 15 shows the adjustment for test HbA1c with various RBC life spans. Near the boundaries of the interquartile range, two subjects with identical test HbA1c of 63 mmol / mol (7.9%) but different RBC life spans of 84 and 101 days would have RBC life span-adjusted aHbA1c values ​​of 78 mmol / mol (9.3%) and 62 mmol / mol (7.8%), respectively, and would be considered to have different future diabetic complication risks. In contrast, multiple individuals with different test HbA1c values ​​of 60 mmol / mol (7.6%) and 75 mmol / mol (9.0%) and RBC life spans of 84 and 101 days would be considered to have identical aHbA1c values ​​of 74 mmol / mol (8.9%). This would place these individuals at similar risk of diabetic complications but potentially different risks of hypoglycemia secondary to treatment escalation, with patients with higher test HbA1c likely to be at higher risk. Generally, in individuals with an RBC lifespan of approximately 86 to 113 days, the difference between adjusted and test HbA1c is relatively small (<11 mmol / mol or 1% when test HbA1c is <64 mmol / mol or 8%). In this homogeneous cohort, 90 subjects (69%) were in this RBC lifespan range. However, greater adjustment is possible at more extreme RBC lifespans. In individuals with an RBC lifespan of <83 days, aHbA1c was a median of 35 mmol / mol (3.2%) higher than test HbA1c, indicating that these individuals may be undertreated and therefore at higher risk for non-transient hyperglycemia and diabetic complications. Conversely, individuals with an RBC lifespan >113 days had aHbA1c that was a median of 13 mmol / mol (1.2%) lower than test values, thus placing some of these patients at risk for overtreatment and acute onset of hypoglycemia.

[0213] Variations in RBC lifespan and transmembrane glucose absorption rates between individuals can result in different test HbA1c values ​​despite similar hyperglycemic exposure of organs affected by diabetic complications. To personalize care and assess individualized risk of hyperglycemic complications, test HbA1c levels must be adjusted to address variability in RBC turnover using the aHbA1c proposed by the inventors. Without this adjustment, there is a risk of overestimating glucose levels, which could lead to hypoglycemia through unnecessary intensification of diabetic treatment, or alternatively, underestimating glucose levels, which could result in undertreatment and subsequent higher risk of complications. Furthermore, when diagnosis is based solely on test HbA1c, misclassification can occur due to variable RBC lifespan across individuals, making prediabetes and diabetes diagnosis more likely.

[0214] Several mathematical models have been developed to estimate laboratory HbA1c from glucose or TIR, highlighting the importance of this field. A unique advantage of our model is the explicit inclusion of individual-specific RBC lifespan and glycation rate within the calculation. Therefore, our method allows for the estimation of RBC lifespan from CGM and HbA1c data without interference from glycation rate variations due to individual GLUT1 levels. We have presented a formula for calculating adjusted HbA1c from laboratory HbA1c and RBC lifespan. While RBC lifespan can be measured directly, this measurement requires complex RBC labeling and tracking, a difficult process to implement in routine clinical practice (6). In this study, we applied a previously published dynamic model (9) to estimate RBC lifespan using high-quality CGM and HbA1c data.

[0215] In conclusion, quantitative aHbA1c derived from laboratory HbA1c and CGM readings has the potential to more accurately assess glycemic exposure in various organs and provide safer and more effective glycemic guidance for the management of individuals with diabetes. In this study, the inventors chose a standard RBC age of 100 days to adjust laboratory HbA1c, but further studies are needed to improve the accuracy of this adjustment and establish the best approach in different populations. Clinical studies using a larger number of individuals are needed to further validate the accuracy of the model and correlate aHbA1c with diabetic complications and glycemic exposure.

[0216] Example 4 Continuous glucose monitor (CGM) data and test HbA1c data were obtained from 31 type 1 diabetes patients. All of these individuals had type 1 diabetes managed with a sensor-equipped pump system. The dataset contained an average of approximately 10 test HbA1c values ​​for each individual, spaced approximately one month apart, with continuous glucose monitoring throughout. A total of 304 test HbA1c values ​​were available using CGM over a paired 14-day period for analysis. Intracellular glucose (IG) was determined throughout using Equation 17.

[0217] Figure 16A is a cross-plot and correlation diagram of 14-day IG mean values ​​when aHbA1c was given, and Figure 16B is a cross-plot diagram of the original collected data of 14-day mean plasma glucose (PG) and laboratory HbA1c. The IG method had an R of 0.93. 2 value, whereas the unadjusted data had an R 2 This resulted in a significant reduction in variability.

[0218] Example 5 Continuous glucose monitor (CGM) data and test HbA1c data were obtained from 31 type 1 diabetes patients. All of these individuals had type 1 diabetes managed with a sensor-equipped pump system. The dataset contained an average of approximately 10 test HbA1c values, spaced approximately one month apart, for each individual with continuous glucose monitoring throughout. A total of 304 test HbA1c values ​​were available using CGM for the paired 14-day period for analysis. Validated plasma glucose (PG) was used. eff ) was determined using Equation 16 throughout.

[0219] 17A and 17B show measured plasma glucose (PG) and PG eff PG is an example of a glucose pattern insight report for the same subject (an individual with stage 2 mild kidney loss) using eff indicates excessive glucose exposure in organs and tissues and therefore a potential cause for kidney damage. The time above the 180 mg / dL target ranged from 6.7% for PG to 1.5% for PG. eff The change in blood glucose level from 0.7% to 37.2% and the time below the 70 mg / dL target from 3.3% to 0.7%. These changes alter the clinical interpretation of the field of glucose control that needs to be addressed to optimize the reduction of short-term and long-term risks attributable to diabetes.

[0220] Thus, the systems, tools, and methods of the present disclosure are adapted to fully achieve the stated aims and advantages, as well as those inherent therein. The specific embodiments disclosed above are illustrative only, as the teachings of the present disclosure may be modified and practiced using different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. Furthermore, no limitations to the details of construction or design shown herein are intended, other than as set forth in the claims below. Accordingly, it will be apparent that the specific exemplary embodiments disclosed above may be altered, combined, or modified, and all such variations are considered to be within the present disclosure. The systems, tools, and methods illustratively disclosed herein may suitably be practiced without any element not specifically disclosed herein and / or without any optional element disclosed herein. Although systems, tools, and methods are described in terms of "comprising," "containing," or "including" various components or steps, the systems, tools, and methods may "consist essentially of" or "consist of" the various components and steps. All of the numbers and ranges disclosed above may vary by some amount. Whenever a numerical range with a lower and upper limit is disclosed, every number within that range and every encompassed range is specifically disclosed. Specifically, all value ranges disclosed herein ("from about a to about b," or, equivalently, "from about a to b," or, equivalently, "about a to b") should be understood to represent every number and range subsumed within that broad value range. Similarly, terms in the claims have their plain, ordinary meaning unless expressly and unambiguously defined otherwise by the patent owner. Furthermore, non-plural nouns when used in the claims mean one or more than one. In the event of any conflict between the use of a word or term in this specification and the use of that word or term in one or more patents or other documents that may be incorporated herein by reference, the non-conflicting definition in this specification shall control.

Claims

1. 1. A computer-implemented method comprising: The computer calculates the red blood cell glycation rate constant (k gly ), erythrocyte development rate constant (k gen ), red blood cell removal constant (k age determining at least one physiological parameter for the subject selected from the group consisting of: a first glucose level (HbA1c), and an apparent glycation constant (K), said determining being based on (1) a plurality of first glucose levels and (2) a test HbA1c level adjusted using a model that accounts for transmembrane glucose transport and glycation; receiving, by a computer, a plurality of second glucose levels for the subject over a period of time; and deriving, by a computer, a calculated HbA1c (cHbA1c) level for the subject based on the at least one physiological parameter and the plurality of second glucose levels, the deriving comprising: identifying a plurality of time intervals having corresponding glucose levels from the plurality of second glucose levels; calculating, for each time interval, an equilibrium HbA1c value from the corresponding glucose level and applying a term dependent on at least one physiological parameter to the equilibrium HbA1c value to calculate the interval HbA1c; and combining the interval HbA1c values ​​over a plurality of intervals to obtain a cHbA1c. A method characterized by:

2. the plurality of second glucose levels are measured by an analyte sensor in contact with a bodily fluid of the subject; 10. The computer-implemented method of claim 1.

3. and a computer displaying the cHbA1c level on a display of a system including the analyte sensor.

3. The computer-implemented method of claim 2.

4. and a computer determining a treatment for the subject based on the cHbA1c level; The treatment includes managing and / or adjusting insulin dosage, glycation drug dosage, exercise regime, dietary intake, or a combination thereof; 10. The computer-implemented method of claim 1.

5. The computer calculates the value by using the following formula 1: Formula 1 the cHbA1c level, the k age , and the defined criterion k age (k ref age calculating an adjusted HbA1c (aHbA1c) level for the subject based on the 10. The computer-implemented method of claim 1.

6. The computer calculates the value using the following formula 2: Formula 2 The cHbA1c level, the K, and the defined reference K (K ref calculating an adjusted HbA1c (aHbA1c) level for the subject based on the 10. The computer-implemented method of claim 1.

7. 1. A system comprising: an analyte sensor configured to measure a glucose level in a bodily fluid; one or more processors; and a monitor device operatively coupled to the one or more processors and having a memory storing instructions that, when executed by the one or more processors, cause the system to perform the method of claim 1; A system comprising:

8. a computer measuring a plurality of first glucose levels for the subject over a first period of time; receiving a test glycated hemoglobin (HbA1c) level for the subject; (1) determining a red blood cell turnover rate (k) for the subject based on the plurality of first glucose levels and (2) the test HbA1c level using a model that accounts for intermembrane glucose transport and glycation; age ) determining Using the following formula 3, Formula 3 The computer determines the test HbA1c level, the k age , and the defined criterion k age (k ref age and calculating an adjusted HbA1c (aHbA1c) level for the subject based on the 10. A computer-implemented method comprising:

9. The test HbA1c level is a test HbA1c level of 2 or 3 or more; 9. The method of claim 8.

10. the plurality of first glucose levels are measured by an analyte sensor in contact with a bodily fluid of the subject; 9. The computer-implemented method of claim 8.

11. and a computer displaying the aHbA1c level on a display of a system including the analyte sensor.

11. The computer-implemented method of claim 10.

12. and a computer determining a treatment for the subject based on the aHbA1c level; The treatment further comprises managing and / or adjusting insulin dosage, glycation drug dosage, exercise regime, dietary intake, or a combination thereof.

9. The computer-implemented method of claim 8.

13. a computer receiving a plurality of second glucose levels; the plurality of second glucose levels are measured by an analyte sensor in contact with a bodily fluid of the subject; 9. The computer-implemented method of claim 8.

14. 1. A system comprising: an analyte sensor configured to measure a glucose level in a bodily fluid; one or more processors; and a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the system to perform the computer-implemented method of claim 9; a monitor device comprising: A system comprising:

15. receiving, by a computer, a plurality of first glucose levels for the subject over a first period of time; receiving, by a computer, a test glycated hemoglobin (HbA1c) level for the subject; a computer determining an apparent glycation constant (K) for the subject based on (1) the plurality of first glucose levels and (2) the test HbA1c level using a model that accounts for transmembrane glucose transport and glycation; Using the following formula 4, Formula 4 A computer calculates the test HbA1c level, the K, and a defined standard K (K ref and calculating an adjusted HbA1c (aHbA1c) level for the subject based on the 10. A computer-implemented method comprising:

16. The test HbA1c level is a test HbA1c level of 2 or 3 or more; 16. The method of claim 15.

17. the plurality of first glucose levels are measured by an analyte sensor in contact with a bodily fluid of the subject; 16. The computer-implemented method of claim 15.

18. a computer receiving a plurality of second glucose levels; the plurality of second glucose levels are measured using an analyte sensor of a closed-loop or hybrid closed-loop insulin pump system in contact with the subject's bodily fluid; 16. The computer-implemented method of claim 15.

19. 1. A system comprising: an analyte sensor configured to measure a glucose level in a bodily fluid; one or more processors; and a memory operatively coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the system to perform the computer-implemented method of claim 16; a monitor device comprising: A system comprising:

20. and a computer diagnosing and / or monitoring the subject and / or making a treatment decision based on the cHbA1c level.

10. The computer-implemented method of claim 1.

21. a computer diagnosing and / or monitoring the subject and / or making a treatment decision based on the aHbA1c level.

9. The computer-implemented method of claim 8.

22. a computer diagnosing and / or monitoring the subject and / or making a treatment decision based on the aHbA1c level.

16. The computer-implemented method of claim 15.

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