RU2746830C1 - Method for assessing glycemic variability to determine effectiveness of antihyperglycemic therapy in patients with mody2 diabetes - Google Patents

Abstract

FIELD: medicine.SUBSTANCE: invention relates to medicine, namely to endocrinology, and can be used to assess the variability of glycemia to determine effectiveness of the hypoglycemic therapy in patients with MODY2 diabetes. Continuous monitoring of glucose in the patient is carried out, followed by calculation of glycemic variability indicators using a computer program, their comparison with indicators corresponding to normoglycemia, and analysis of the effectiveness of the therapy. Continuous monitoring of glucose in the patient is carried out for 24 hours. The following indicators are calculated and evaluated: standard deviation (SD), coefficient of variation (CV), normative reference range (M-value), mean amplitude of glycemic fluctuations (MAGE), index of prolonged glycemic increase (CONGA), rate of change in glucose levels (MAG), hyperglycemia risk index (HBGI), hypoglycemia risk index (LBGI), average hypo / hyperglycemia risk index (ADRR). The processing of the obtained glycemic indicators can be carried out using the computer program "GLINVA". The calculated values ​​of the indicators after computer processing are compared with the indicators corresponding to normoglycemia. When values ​​of at least three analyzed indicators are increased, in comparison with the reference values, a conclusion is made about the ineffectiveness of the therapy being carried out and the need for its correction.EFFECT: method makes it possible to reduce the duration and increase efficiency of assessing the variability of glycemia to determine teffectiveness of the therapy in patients with MODY2 diabetes due to continuous monitoring of glucose in the patient, followed by the calculation of the optimal indicators of the variability of glycemia.1 cl, 6 dwg, 2 tbl, 3 ex

Description

The invention relates to medicine, mainly to endocrinology, and can be used to assess the variability of glycemia in order to determine the effectiveness of the therapy in young patients with MODY2 diabetes.

Diabetes mellitus (DM) is a chronic non-communicable disease, the prevalence of which is growing worldwide every year. The International Diabetes Federation (IDF) predicts 642 million people will have diabetes by 2045. In the Russian Federation, as in all countries of the world, there is a significant increase in the prevalence of diabetes. According to the federal register of diabetes mellitus in the Russian Federation in 2018, 3.1% of the population was registered at the dispensary, of which 92% were patients with type 2 diabetes mellitus (T2DM), 6% were patients with type 1 diabetes mellitus (T1DM) and type 2 % of patients with other, more rare types of diabetes [1]. Rare forms include "adult-type diabetes mellitus in the young" (Maturity Onset Diabetes of the Young - MODY diabetes). This type of diabetes is characterized by early onset (before 35 years of age), autosomal dominant inheritance, and a primary defect in insulin secretion. Currently, MODY diabetes is considered to be the result of a genetic disorder of the β-cell function of the pancreas.

There are 14 known types of MODY diabetes, which are verified depending on mutations in the associated genes: HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, ABCC8, KCNJ11, APPL1. All subtypes differ in the clinical course, the development of complications and approaches to therapy. Thus, patients with HNF1A-MODY (MODY3) and HNF4A-MODY (MODY1) diabetes are sensitive to sulfonylurea (SCU) preparations, and in GCK-MODY (MODY2) diabetes, disorders of carbohydrate metabolism in most cases are corrected by a balanced diet. With this type of diabetes, there is no absolute need for insulin therapy, which reduces the financial costs of therapy and improves the patient's quality of life [2, 3].

It is possible to personally study and evaluate the parameters of carbohydrate metabolism, their variability and the effectiveness of the therapy, it is possible by continuous monitoring of glucose (LMWH) using devices that can measure the level of glucose in the interstitial fluid of the subcutaneous fat quite often (usually every 5 minutes) for a long time (usually 3-7 days). There are two types of LMW: professional or "blind" and custom. While wearing professional devices, the patient does not see his readings and is guided by the data of his glucometer. The second type of LMWH systems is custom, allowing the patient to see the monitoring results in real time on the device screen. This monitoring is called real time monitoring (RT-CGM) or real-time continuous glucose monitoring (RW-LMWG). The monitor of the device for LMWH always allows you to determine the trend of glycemic changes - it gives an idea of how glycemia has changed over a long time. Thus, decoding of data from devices for LMWH allows you to analyze fluctuations in glucose levels after eating, during physical exertion, to identify the phenomenon of morning hyperglycemia, episodes of hypoglycemia (including nocturnal and asymptomatic).

There is a known method for assessing the variability of glycemia (GV) in patients with MODY2 diabetes by conducting LMWH for 72 hours, followed by the determination of the following GV parameters: average glycemic level (MBG), average amplitude of glycemic fluctuations (MAGE). It was shown that in 50% of patients the glucose values during the day exceeded the normal ranges, which required correction of the prescribed therapy (recommendations on nutrition and lifestyle) [4].

The disadvantages of this method are the duration and insufficient efficiency associated with a small number of patients examined (8 patients in whom glycated hemoglobin did not exceed 7%) and the use of only 2 GV parameters for the assessment, which does not reveal all changes in glycemia and does not fully reflect the effectiveness ongoing therapy.

The closest prototype to the claimed method is a method for assessing glycemic variability (GV) in patients with HNF4A-MODY (MODY1) diabetes in 10 patients, whose average age was 21 years, by performing LMWH using a LMWH device, which was periodically set to 72 hours. The following GV parameters were assessed: mean glycemic level (MBG), standard deviation of glucose level (SD or SDBG), mean amplitude of glycemic fluctuations (MAGE), percentage of the patient being in a state of hypoglycemia (glucose level less than 3.9 mmol / L). The deviation in glucose levels in the observed group of patients was higher than in those with normoglycemia. There were episodes of asymptomatic hypoglycemia in the group with mutations in HNF4A that were not due to lack of food or exercise. The authors suggested that the prolonged hyperinsulinemic phase in adulthood is responsible for the marked hypoglycemic episodes [5].

The disadvantages of this method are the duration of the method (at least 72 hours) and low objectivity, since only 4 GV indicators were evaluated, which does not allow performing a deep analysis of carbohydrate metabolism indicators and assessing the effectiveness of the therapy.

Earlier in Russia, the study of GV using LMWH in patients with the most common type of MODY (MODY2 diabetes) was not carried out.

The objective of the invention is to develop a method for assessing glycemic variability by conducting LMWH with subsequent calculation of the most important and optimal GV parameters to determine the effectiveness of the therapy in patients with MODY2 diabetes.

EFFECT: reduced duration and increased efficiency of the method.

The task is achieved by the proposed method, which consists in the fact that in young patients with MODY2 diabetes, daily LMWH is performed, followed by the calculation of the most important and optimal GV parameters presented in Table 1. LMWH indications are processed using a computer program and compared with GV indices in individuals with normoglycemia. With an increase in the values of the indicators, a conclusion is made about the ineffectiveness of the hypoglycemic therapy in patients with MODY2 diabetes and correction of therapy is carried out.

The claimed method is carried out as follows.

In the examined patient of a young age (up to 35 years old) with MODY2 diabetes, daily LMWH is performed using a device for LMWH, then the readings from the device are transmitted to a personal computer in the form of graphic images. To convert graphic images into digital ones, a computer program is used that automatically substitutes the obtained data into mathematical formulas and calculates them. The GLINVA program is mainly used as a computer program (Certificate No. 2019660636, registered 08/09/2019).

At the same time, the following glycemic indicators are assessed: SD (Standard Deviation) - standard deviation, CV (Coefficient of variation) - coefficient of variation, (M-value) - normative reference range, MAGE (Mean Amplitude of Glycemic Excurtion) - average amplitude of glycemic fluctuations, CONGA (Continuous Overlapping NetGlycemic Action) - index of prolonged increase in glycemia, MAG (Mean Absolut Glucose) - assessment of the rate of change in glucose levels, HBGI (Hight Blood Glucose Index) - index of risk of hyperglycemia, LBGI (Low Blood Glucose Index) - index of risk of hypoglycemia, ADRR (Average Daily Rick Range) - the average risk of hypo / hyperglycemia (table 1). Further, the GV values calculated by the program are compared with those of Caucasians up to 35 years old with normoglycemia: SD - up to 3.0 mmol / L, CV - up to 20%, M - up to 6.0, MAGE - up to 2.8 mmol / L , CONGA - 3.6-5.5 mmol / L, MAG - 0.5-2.2 mmol / L / h, HBGI - up to 7.7, LBGI - up to 6.9, ADRR - up to 8.7 and with an increase in the values, in comparison with the reference values, a conclusion is made about the ineffectiveness of the therapy and the need for its correction.

The defining difference between the proposed method and the prototype is that a patient with MODY diabetes is given daily LMWH, followed by the calculation of the most important and optimal GH parameters, which makes it possible to more objectively make a conclusion about the effectiveness of the hypoglycemic therapy and, if necessary, correct the therapy.

The proposed method is easy to use both at the outpatient and hospital stages, is easily tolerated by patients, the interpretation of the results does not require a long investment of time and does not depend on changing environmental conditions.

Justification of the choice of experimentally selected optimal and sufficient indicators of GH, which are calculated on the basis of the conducted LMW:

1) the SD indicator characterizes the degree of dispersion of glycemic values;

2) the CV indicator (coefficient of variation) shows what percentage of the average glycemic value is SD;

3) the indicator (M-value) characterizes the quality of glycemic control;

4) MAGE (mean amplitude of glycemic fluctuations) is an important metric developed for the assessment of postprandial hyperglycemia using the results of multiple glucose measurements. When calculating the MAGE, all oscillations with an amplitude less than 1 SD are ignored. Normally, in persons without a violation of carbohydrate metabolism, this indicator exceeds the value equal to 1 SD and ranges from 0 to 2.8 mmol / L.

5) MAG (Rate of Change in Glucose) is the sum of successively measured glucose levels divided by the total measurement time in hours. The temporal aspect of the measurement is taken into account, therefore, the rate of change in glucose level is reflected in mmol / l / h. MAG, calculated during the daytime, allows to assess the risk of hypoglycemia in patients on the following night [5].

6) Indicator CONGA (prolonged increase in glycemia), the calculation of which determines the absolute differences in glycemic values at a given time and n hours ago. Glycemic differences are calculated for each determination after n hours of monitoring, so CONGA is the variance (standard deviation) of the differences found.

The ability to assess the risks of hypo / hyperglycemia is presented by calculating the following indicators (indices):

7) risk of hyperglycemia (HBGI),

8) risk of hypoglycemia (LBGI),

9) average risk value (ADRR).

A value of 6.25 mmol / L is taken as a risk of 0. The risk of hyperglycemia increases as the HGBI rises above 6.25 mmol / L. Likewise, the risk of hypoglycemia increases progressively when the LGBI index tends to values below 6.25 mmol / L. The average daily range of all risks reflects the ADRR indicator. In contrast to the risks of hypo / hyperglycemia, ADRR helps to successfully predict excessively high or low glycemia, but does not always respond to delicate deviations from the target level [6].

The proposed method for assessing the variability of glycemia in patients with MODY2 diabetes to determine the effectiveness of antihyperglycemic therapy was developed on the basis of research conducted at the Research Institute of Therapy and Preventive Medicine - a branch of the ICG SB RAS. All patients underwent collection and assessment of anamnesis, clinical examination, determination of the main biochemical and hormonal parameters of blood. Confirmation of the diagnosis of MODY2 diabetes was carried out by next generation sequencing and Sanger direct auto sequencing. Determination of the level of daily glucose was carried out by the LMWG method.

The study included patients who met the following criteria:

1. Signing informed consent to participate in the study

2. Moderate fasting hyperglycemia (up to 8 mmol / l)

3. Debut of the disease before 35 years

4. The presence in the pedigree of relatives of 1-2 degrees of kinship with impaired carbohydrate metabolism

5. Absence of obesity (abdominal circumference in women less than 80 cm, in men less than 94 cm or BMI up to 29.9 kg / m2)

6. Absence of characteristic symptoms of type 1 diabetes mellitus (ketoacidosis, weight loss at the onset)

7. Long-term (at least 1 year) remission without periods of decompensation (stable value of HbA1c level ≤ 7.5%)

8. Preservation of the secretory activity of beta cells (the level of C-peptide is slightly reduced or within normal limits)

9. Lack of markers of autoimmune response (AT to beta cells, GAD, insulin, tyrosine phosphatase).

The exclusion criteria for participation in the study were:

1. Presence of HIV in anamnesis;

2. History of viral hepatitis;

3. A positive result of at least one autoantibody.

Taking into account the inclusion and exclusion criteria, 66 patients who are observed at the NIITPM-branch of the ICG SB RAS with clinical and laboratory signs of MODY2 diabetes were subjected to molecular genetic analysis using targeted high-throughput next-generation sequencing (NGS) technology, the identified mutations were verified by direct automatic sequencing by Sanger. According to the results of the study, GCK-MODY (MODY2) diabetes was confirmed in 43 (65%) patients out of 66 examined. A sample of 20 people was formed from this group of patients for LMWH (the main criteria for the sample were informing the patient's consent to participate in the study). The study included 14 females and 6 males, the median age at diagnosis verification was 28 [18; 35 years. All patients underwent LMWH using a Medtronic MiniMade device (USA). To convert the graphical values of LMWH indicators into digital ones, calculate the main indicators of carbohydrate metabolism and compare them with normal values (for young people), a specialized computer program ("GLINVA") in Russian was used.

The mean and standard deviation of GV parameters in patients with GCK-MODY (MODY2) diabetes were calculated. GV indices in the study group of patients with MODY2 diabetes in comparison with GV indices in individuals without diabetes are presented in Table 2.

The average daily glucose level is 7.5 mmol / L, which confirms moderate hyperglycemia in patients with GCK-MODY diabetes. The calculated MAGE and MAG values were within the reference values, which is comparable to the values in individuals without impaired carbohydrate metabolism. In individuals with GCK-MODY diabetes, the risk of hyperglycemia is in the normal range, as in individuals without diabetes. The LGBI index is increased and, probably, due to it, the ADRR is also increased, which may indicate the possibility of hypoglycemia in the studied group of patients. Analyzing the GV parameters of all 20 patients, it turned out that they are not characterized by nocturnal episodes of hypoglycemia (00: 00-06: 00).

Thus, evaluating the LMWH indices, it was found that in most, but not all, patients, the state of carbohydrate metabolism was within the target values. These patients underwent a correction of therapy, according to the results of which a different treatment strategy was chosen in 7 patients. After receiving these GV parameters, two out of seven patients were transferred from insulin therapy to oral hypoglycemic drugs (PSP), which improved the patient's quality of life and reduced the cost of diabetes treatment. Three patients were discontinued PSP because of the high risk of hypoglycemia, which reduced the number of episodes of asymptomatic hypoglycemia and increased the activity of these people. The classes of antihyperglycemic drugs were changed in two patients with the achievement of the target values of carbohydrate metabolism.

After the LMWH, the assessment of the selected (necessary and sufficient) GV parameters using the "GLINVA" program allows the doctor to receive the GV result within a minute during a therapeutic appointment, conduct a more in-depth analysis of the state of carbohydrate metabolism and adjust the therapy in a particular patient.

The essence of the claimed method is illustrated by the following examples.

Example 1.

Patient S., male, born in 2002, was referred for a consultation at NIITPM with suspected MODY diabetes. The parents of the proband, who were diagnosed with carbohydrate metabolism disorders during the examination, were also sent.

At the age of 5, the patient had thirst, itching of the skin, and the examination revealed hyperglycemia. Patient S. was diagnosed with impaired carbohydrate tolerance; in 2009, he was diagnosed with diabetes type, which requires clarification. After the diagnosis of diabetes mellitus was determined, prolonged insulin was prescribed to correct fasting hyperglycemia at a minimum dose of 6 U. With this therapy, the patient experienced frequent episodes of hypoglycemia.

Since the patient has a course of diabetes atypical for "classic" type 1 diabetes (no ketoacidosis, weight loss, antibodies, need for exogenous insulin) and type 2 diabetes (normal BMI, no signs of insulin resistance, early age of onset), the proband was assumed to have MODY diabetes. Fasting hyperglycemia prevailed in the patient, a stable course of diabetes was observed, the father had asymptomatic hyperglycemia, and a preliminary diagnosis of MODY2 diabetes was made.

Patient S. underwent direct automatic sequencing of 12 exons of the glucokinase gene. A missense mutation CTG> GTG was found in exon 4 at nucleotide position 146 (146C> G), leading to the replacement of the amino acid leucine with valine (Leul46Val). This mutation is characteristic of MODY2 diabetes. The father also had a missense mutation Leul46Val, identical to the mutation of the proband.

After verification of the MODY of diabetes in the patient, the variability of glycemia was assessed by the claimed method by performing LMWH on a Medtronic MiniMade device (USA) with further assessment of GV using 9 indicators presented in Table 1.

When evaluating the indicators obtained, frequent episodes of hypoglycemia were identified. The patient was switched from insulin therapy to oral medications with a positive effect (he felt better, no hypoglycemia was noted). The results of the GPS patient C after correction of therapy are presented in Fig. 1, the calculation of the parameters of the glycemic variability of the patient C. using the "GLINVA" program is presented in FIG. 2. Normative reference range (M), the program calculates automatically in accordance with the formula for calculation by the value method.

According to the graphical results of LMWH (Fig. 1), an even glycemic profile is visible. After processing the LMWH data, the program revealed a low daily variability of glycemia, the state of carbohydrate metabolism was compensated. There are no episodes of hypoglycemia. There were two episodes of postprandial hyperglycemia. Thus, the visual data of the graph correspond to the numerical indicators of the VG. This conclusion corresponds to all the characteristics of the course of the monogenic form of diabetes mellitus in patients with a mutation in the glucokinase gene and shows the high efficiency of oral glucose-lowering therapy, in contrast to insulin therapy for this patient.

Example 2.

Patient N, born in 1985, was sent to the NIITPM branch of the ICG SB RAS to verify the type of diabetes mellitus. Hyperglycemia was detected during pregnancy, insulin therapy was prescribed, which was canceled after childbirth, normoglycemia was achieved by rational nutrition. A year later, the patient showed an increase in glycemia and she began taking oral antihyperglycemic drugs with a positive effect. The patient had symptoms atypical for type 1 and type 2 diabetes: absence of overweight and manifestations of insulin resistance, negative autoantibodies, normal C-peptide levels, so she underwent a molecular genetic study of the GCK gene. A pathogenic mutation associated with MODY2 diabetes was verified in patient N.

After MODY verification of diabetes in the patient, the glycemic variability was assessed by 9 indicators presented in Table 1 by performing LMWH on a Medtronic MiniMade device (USA). The results of the GPS of patient N. are presented in Fig. 3, the calculation of glycemic variability indicators using the "GLINVA" program is shown in FIG. four.

The graphical results of LMWH show an even glycemic profile, but several episodes of hyperglycemia have been recorded. After converting the graphical values to digital using the program, it is seen that the indicators of long-term increase in glycemia (CONGA) and the average risk of hypo / hyperglycemia (ADDR) are higher than the target. The obtained digital values of the variability of glycemia indicate the need for correction of therapy for the relief of prolonged hyperglycemia.

Example 3.

Patient V., born in 1973, was referred for consultation to the NIITPM branch of the ICG SB RAS. Hyperglycemia was detected at the age of 32 during clinical examination, she had no complaints, followed a diet for 3 years, but then an increase in glycemia was revealed, oral hypoglycemic therapy was prescribed. The patient had symptoms atypical for type 1 and type 2 diabetes: absence of overweight and manifestations of insulin resistance, negative autoantibodies, normal C-peptide levels, burdened heredity for disorders of carbohydrate metabolism; therefore, she underwent a molecular genetic study of the GCK gene. A pathogenic mutation associated with MODY2 diabetes was verified in patient B.

After MODY verification of diabetes in the patient, the glycemic variability was assessed by 9 indicators presented in Table 1, by performing LMWH on the Medtronic MiniMade device. The LMWH results of patient B. are shown in FIG. 5, and the calculation of glycemic variability indicators using the "GLINVA" program is shown in FIG. 6.

According to the graphical results of LMWH (Fig. 5), hyperglycemia is observed. After converting the graphical values of MMG into digital ones using the program (Fig. 6), a twofold increase in the index of duration of increase in glycemia (COGNA), rate of increase in hyperglycemia (MAG), risk index for hypoglycemia (LBGI) is determined, which is not detected on the graph and the average value is significantly increased risks of hypo / hyperglycemia (ADDR). Thus, after analyzing the GV parameters, it can be concluded that this patient has a high glycemic level, episodes of glucose decrease and a significant rate of glucose change from low to high values, which requires correction of therapy, taking into account the possibility of hypoglycemia development.

The method allows to identify a risk group for the occurrence of asymptomatic hypoglycemia and prolonged hyperglycemia, i.e. decompensation of carbohydrate metabolism in young people with MODY diabetes. The use of the proposed method for assessing the variability of glycemia makes it possible to assess the effectiveness of the therapy and to correct it in a timely manner.

Bibliography

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Claims (2)

1. A method for assessing glycemic variability to determine the effectiveness of antihyperglycemic therapy in patients with MODY2 diabetes, including continuous monitoring of glucose in a patient with subsequent calculation of glycemic variability indicators using a computer program, their comparison with indicators corresponding to normoglycemia, and analysis of the effectiveness of therapy, which differs the fact that continuous monitoring of glucose in a patient is carried out for 24 hours, while the following indicators are calculated and evaluated: standard deviation (SD), coefficient of variation (CV), normative reference range (M-value), mean amplitude of glycemic fluctuations (MAGE) , index of prolonged increase in glycemia (CONGA), rate of change in glucose levels (MAG), index of risk of hyperglycemia (HBGI), index of risk of hypoglycemia (LBGI), average risk of hypo / hyperglycemia (ADRR), further calculated values of indicators, after computer processing, compared with indicators, respectively with normoglycemia, and with an increase in the values of at least three analyzed indicators, in comparison with the reference values, a conclusion is made about the ineffectiveness of the therapy and the need for its correction. 2. The method according to claim. 1, characterized in that the processing of the obtained glycemic parameters is carried out using the computer program "GLINVA".

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