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*Only for medical professionals to read for reference.
Simplify postprandial blood glucose monitoring and help meet the standard and reduce blood sugar
.
Type 2 diabetes (T2DM) has become one of the main chronic diseases in China
.
According to statistics, the number of T2DM patients in China has reached 116 million in 2019 [1]
.
Most Chinese patients with T2DM have elevated postprandial blood glucose (PBG) [2]
.
In the management of T2DM patients, PBG is one of the important parameters of the blood glucose profile, and monitoring and control of PBG is very important
.
Professor Yang Wenying of China-Japan Friendship Hospital and Professor Ji Linong of Peking University People's Hospital jointly constructed a PBG estimation model suitable for Chinese T2DM patients based on glycosylated hemoglobin (HbA1c) and fasting blood glucose (FBG)
.
"Medical Endocrinology Channel" is fortunate to invite Professor Yang Wenying to share about the construction of the PBG estimation model and the application of this model in clinical practice, hoping to help clinicians understand the overall blood sugar control and better manage diabetes
.
Postprandial blood glucose not to be underestimated "PBG is an important blood glucose indicator for the management of T2DM patients, and it is of great significance in diagnosis and management!" Professor Yang Wenying emphasized the importance of PBG at the beginning of this interview
.
Among Chinese diabetic patients diagnosed by epidemiological screening, the proportion of patients with elevated PBG alone is 50% [2], and more than 80% of newly diagnosed T2DM have postprandial hyperglycemia [3]
.
Early FBG is not elevated and PBG is elevated has become a significant feature of newly diagnosed T2DM in China
.
In the management of T2DM patients, high PBG is one of the main reasons that lead to the failure of HbA1c
.
Studies have shown that in T2DM patients treated with basal insulin plus oral medications, when FBG meets the standard but PBG does not meet the standard, more than half of the patients fail to meet the HbA1c standard [4]
.
The 2021 American Diabetes Association (ADA) guidelines recommend that T2DM patients whose HbA1c does not meet the standard but FBG meets the standard should be tested for PBG, and pointed out that controlling the PBG level below 10.
0 mmol/L can help reduce HbA1c[1]
.
Postprandial hyperglycemia is closely related to microvascular and macrovascular complications and increased risk of death in patients with T2DM.
The increase in its level is independently related to retinopathy, carotid artery intima-media thickening, and reduction of myocardial blood volume and blood flow
.
PBG is an independent risk factor for all-cause death and cardiovascular death, as well as a predictor of cardiovascular disease and all-cause death [1]
.
Therefore, effective control of postprandial hyperglycemia can not only improve the overall blood glucose control level, but also help reduce the occurrence of cardiovascular events and improve the prognosis of patients with T2DM
.
Models help simple prediction of PBG Active monitoring and control of PBG is an important strategy to promote HbA1c control to prevent chronic complications of diabetes
.
But Professor Yang said: “In clinical practice, since most patients’ self-monitoring of blood glucose and routine hospital monitoring are FBG and HbA1c, daily monitoring of PBG is difficult and data acquisition is relatively small
.
Therefore, it is more difficult to use easily accessible indicators to calculate.
Difficult to obtain indicators will help PBG monitoring and compliance
.
"
The PBG prediction model uses the relevant data provided by the CLASSIFY study to construct a prediction model for the PBG of Chinese T2DM patients based on HbA1c and FBG, and finally found that there is a certain linear relationship between FBG and HbA1c and PBG levels, namely [PBG(mmol/L) = 1.
5 × HbA1c (%) + 0.
5 × FBG (mmol/L)-4.
1]
.
Then, the CLASSIC study was used as a validation cohort to verify the accuracy of the model, and the predicted PBG was compared with the measured PBG, and it was found that the average value of the two was very close and only differed by 0.
1 mmol/L [1]
.
The PBG prediction model can be subsequently applied to the APP or simple small tools in the clinic for chronic disease management.
The clinician calculates the result through a formula to prompt the clinician or patient whether there is a problem of high blood glucose after a meal, and take corresponding treatment measures to further improve blood glucose.
Control
.
The "practical" points of the PBG model The PBG prediction model provides a simple and reliable PBG estimation method for T2DM patients receiving oral hypoglycemic drugs or insulin therapy
.
In practice, how should clinicians use the predictive model and what are the precautions in using it? Professor Yang gave detailed answers
.
Since the modeling cohort (CLASSIFY study) and the verification cohort (CLASSIC study) use HbA1c, FBG and PBG data sets, it is necessary to pay attention to the closeness of HbA1c and the average FBG time when using this model, for example, use the HbA1c and 3 measured today.
The average FBG one month ago will have an impact on the accuracy of data prediction [1]
.
Professor Yang suggested using HbA1c and the average value of FBG in the previous month to calculate the average PBG for that month
.
Since the calculated PBG is the average range, the measured PBG is the point blood sugar, and there are many influencing factors, such as time, mood, and diet
.
Therefore, the predicted value of PBG cannot be simply understood as a point blood glucose detected randomly
.
Studies have shown that when HbA1c<7.
3%, PBG's contribution to HbA1c accounts for 70%; when HbA1c is between 7.
3% and 9.
2%, PBG's contribution to HbA1c accounts for about 50% [2]
.
In the low HbA1c range, PBG contributes more to it
.
In the model construction study, the average HbA1c of the enrolled patients was 8.
5%, and the results showed that the degree of fit was relatively high
.
Professor Yang suggested that this model can be used to predict PBG in patients with HbA1c within 9%
.
As Asian T2DM patients suffer from high-carbohydrate diets or more serious damage to islet function, the problem of postprandial hyperglycemia is particularly prominent for Chinese people, and routine monitoring of PBG is required
.
The PBG prediction model provides a simple and reliable PBG estimation method for T2DM patients receiving oral hypoglycemic drugs or insulin therapy
.
Studies have shown that even if basal insulin is used to strictly control fasting blood glucose, the average increase in blood glucose 2h after a meal in Chinese patients is still about 4 mmol/L, while the HbA1c compliance rate is only about 40% [5]
.
It can be seen that in basal insulin therapy, PBG has become the main obstacle to achieving HbA1c standards [5]
.
Predicting PBG through the PBG model helps patients understand the PBG level in time, reduces the burden of blood glucose measurement for patients, and helps improve monitoring compliance
.
The 4200 study also confirmed that for patients who did not meet the standard of basal insulin + oral drug treatment, after adjusting to 2 times a day premixed insulin analog treatment, HbA1c, FPG, and blood glucose after morning and dinner in T2DM patients were significantly lower than baseline [6], which was comprehensively significant Improve blood sugar control
.
For patients with poor blood glucose control after meals, premixed insulin analogs can be used in time for treatment
.
In conclusion, Professor Yang said that the problem of blood sugar after meals is particularly prominent for Chinese people, and PBG is related to macrovascular and microvascular complications
.
However, it is difficult to obtain PBG data for a period of time in clinical practice
.
The PBG prediction model can be applied to the comprehensive management of T2DM.
Doctors can remotely monitor the patient's omni-directional blood glucose indicators, which helps to help patients in clinical practice to achieve full glucose control, especially for patients with elevated blood glucose after meals, and to improve PBG Measurement of blood glucose management in T2DM patients with poor compliance
.
Expert Profile Professor Yang Wenying, Chief Physician, Professor, and Doctoral Supervisor Current: Vice Chairman of the Asian Diabetes Association (AASD), Central Health Consultation Expert, Current Honorary Editor-in-Chief of Chinese Journal of Diabetes Director of Internal Medicine, Director of Teaching and Research Section of Internal Medicine, Director of Hospital Academic Committee, Chairman of Diabetes Branch of Chinese Medical Association, Honorary Chairman, Founding Editor-in-Chief of "Chinese Journal of Diabetes" • In 2012, he won the first prize of Beijing Municipal Science and Technology Progress Award and the second prize of Chinese Medical Association Science and Technology Progress Awards • 2012 National Health System Advanced Individual, Female Hero and other titles • 2013 Asian Diabetes Society (AASD) First Diabetes Epidemiology Award • 2015 Chinese Medical Association Diabetes Branch Scientific Contribution Award • 2015 Chinese Medical Doctor Association-Physician Medical Contribution Expert • Won the First National Famous Doctor-Excellence Achievement Award in 2017 References: [1] Zhang Xuelian, et al.
Chinese Journal of Diabetes.
2021,13(7):702-707.
[2] Mu Yiming, Ji Linong, Yang Wenying , Etc.
Expert consensus on management of postprandial hyperglycemia in Chinese type 2 diabetes patients[J].
Chinese Journal of Diabetes, 2016, 024(005):385-392.
[3]Yang W, et al.
N Engl J Med.
2010, 362:1090-101.
[4]Woerle HJ, Neumann C, Zschau S, et al.
Impact of fasting and postprandial glycemia on overall glycemic control in type 2 diabetes: Importance of postprandial glycemia to achieve target HbA1c levels[J].
diabetes res clin pract, 2007, 77(2):0-285.
[5]Yang W, et al.
Diabetes Obes Metab.
2019 Aug;21(8): 1973-1977.
[6]Yang W,et al.
Diabetes Res Clin Pract.
2019 Mar 11;150:158-166.
-End-Approval code: PP-HI-CN-5364 "This article is only used to provide scientific information to medical and health professionals, and does not represent the platform's position.
" For submission/reprint/business cooperation, please contact: pengsanmei@yxj.
org.
cn
Simplify postprandial blood glucose monitoring and help meet the standard and reduce blood sugar
.
Type 2 diabetes (T2DM) has become one of the main chronic diseases in China
.
According to statistics, the number of T2DM patients in China has reached 116 million in 2019 [1]
.
Most Chinese patients with T2DM have elevated postprandial blood glucose (PBG) [2]
.
In the management of T2DM patients, PBG is one of the important parameters of the blood glucose profile, and monitoring and control of PBG is very important
.
Professor Yang Wenying of China-Japan Friendship Hospital and Professor Ji Linong of Peking University People's Hospital jointly constructed a PBG estimation model suitable for Chinese T2DM patients based on glycosylated hemoglobin (HbA1c) and fasting blood glucose (FBG)
.
"Medical Endocrinology Channel" is fortunate to invite Professor Yang Wenying to share about the construction of the PBG estimation model and the application of this model in clinical practice, hoping to help clinicians understand the overall blood sugar control and better manage diabetes
.
Postprandial blood glucose not to be underestimated "PBG is an important blood glucose indicator for the management of T2DM patients, and it is of great significance in diagnosis and management!" Professor Yang Wenying emphasized the importance of PBG at the beginning of this interview
.
Among Chinese diabetic patients diagnosed by epidemiological screening, the proportion of patients with elevated PBG alone is 50% [2], and more than 80% of newly diagnosed T2DM have postprandial hyperglycemia [3]
.
Early FBG is not elevated and PBG is elevated has become a significant feature of newly diagnosed T2DM in China
.
In the management of T2DM patients, high PBG is one of the main reasons that lead to the failure of HbA1c
.
Studies have shown that in T2DM patients treated with basal insulin plus oral medications, when FBG meets the standard but PBG does not meet the standard, more than half of the patients fail to meet the HbA1c standard [4]
.
The 2021 American Diabetes Association (ADA) guidelines recommend that T2DM patients whose HbA1c does not meet the standard but FBG meets the standard should be tested for PBG, and pointed out that controlling the PBG level below 10.
0 mmol/L can help reduce HbA1c[1]
.
Postprandial hyperglycemia is closely related to microvascular and macrovascular complications and increased risk of death in patients with T2DM.
The increase in its level is independently related to retinopathy, carotid artery intima-media thickening, and reduction of myocardial blood volume and blood flow
.
PBG is an independent risk factor for all-cause death and cardiovascular death, as well as a predictor of cardiovascular disease and all-cause death [1]
.
Therefore, effective control of postprandial hyperglycemia can not only improve the overall blood glucose control level, but also help reduce the occurrence of cardiovascular events and improve the prognosis of patients with T2DM
.
Models help simple prediction of PBG Active monitoring and control of PBG is an important strategy to promote HbA1c control to prevent chronic complications of diabetes
.
But Professor Yang said: “In clinical practice, since most patients’ self-monitoring of blood glucose and routine hospital monitoring are FBG and HbA1c, daily monitoring of PBG is difficult and data acquisition is relatively small
.
Therefore, it is more difficult to use easily accessible indicators to calculate.
Difficult to obtain indicators will help PBG monitoring and compliance
.
"
The PBG prediction model uses the relevant data provided by the CLASSIFY study to construct a prediction model for the PBG of Chinese T2DM patients based on HbA1c and FBG, and finally found that there is a certain linear relationship between FBG and HbA1c and PBG levels, namely [PBG(mmol/L) = 1.
5 × HbA1c (%) + 0.
5 × FBG (mmol/L)-4.
1]
.
Then, the CLASSIC study was used as a validation cohort to verify the accuracy of the model, and the predicted PBG was compared with the measured PBG, and it was found that the average value of the two was very close and only differed by 0.
1 mmol/L [1]
.
The PBG prediction model can be subsequently applied to the APP or simple small tools in the clinic for chronic disease management.
The clinician calculates the result through a formula to prompt the clinician or patient whether there is a problem of high blood glucose after a meal, and take corresponding treatment measures to further improve blood glucose.
Control
.
The "practical" points of the PBG model The PBG prediction model provides a simple and reliable PBG estimation method for T2DM patients receiving oral hypoglycemic drugs or insulin therapy
.
In practice, how should clinicians use the predictive model and what are the precautions in using it? Professor Yang gave detailed answers
.
Since the modeling cohort (CLASSIFY study) and the verification cohort (CLASSIC study) use HbA1c, FBG and PBG data sets, it is necessary to pay attention to the closeness of HbA1c and the average FBG time when using this model, for example, use the HbA1c and 3 measured today.
The average FBG one month ago will have an impact on the accuracy of data prediction [1]
.
Professor Yang suggested using HbA1c and the average value of FBG in the previous month to calculate the average PBG for that month
.
Since the calculated PBG is the average range, the measured PBG is the point blood sugar, and there are many influencing factors, such as time, mood, and diet
.
Therefore, the predicted value of PBG cannot be simply understood as a point blood glucose detected randomly
.
Studies have shown that when HbA1c<7.
3%, PBG's contribution to HbA1c accounts for 70%; when HbA1c is between 7.
3% and 9.
2%, PBG's contribution to HbA1c accounts for about 50% [2]
.
In the low HbA1c range, PBG contributes more to it
.
In the model construction study, the average HbA1c of the enrolled patients was 8.
5%, and the results showed that the degree of fit was relatively high
.
Professor Yang suggested that this model can be used to predict PBG in patients with HbA1c within 9%
.
As Asian T2DM patients suffer from high-carbohydrate diets or more serious damage to islet function, the problem of postprandial hyperglycemia is particularly prominent for Chinese people, and routine monitoring of PBG is required
.
The PBG prediction model provides a simple and reliable PBG estimation method for T2DM patients receiving oral hypoglycemic drugs or insulin therapy
.
Studies have shown that even if basal insulin is used to strictly control fasting blood glucose, the average increase in blood glucose 2h after a meal in Chinese patients is still about 4 mmol/L, while the HbA1c compliance rate is only about 40% [5]
.
It can be seen that in basal insulin therapy, PBG has become the main obstacle to achieving HbA1c standards [5]
.
Predicting PBG through the PBG model helps patients understand the PBG level in time, reduces the burden of blood glucose measurement for patients, and helps improve monitoring compliance
.
The 4200 study also confirmed that for patients who did not meet the standard of basal insulin + oral drug treatment, after adjusting to 2 times a day premixed insulin analog treatment, HbA1c, FPG, and blood glucose after morning and dinner in T2DM patients were significantly lower than baseline [6], which was comprehensively significant Improve blood sugar control
.
For patients with poor blood glucose control after meals, premixed insulin analogs can be used in time for treatment
.
In conclusion, Professor Yang said that the problem of blood sugar after meals is particularly prominent for Chinese people, and PBG is related to macrovascular and microvascular complications
.
However, it is difficult to obtain PBG data for a period of time in clinical practice
.
The PBG prediction model can be applied to the comprehensive management of T2DM.
Doctors can remotely monitor the patient's omni-directional blood glucose indicators, which helps to help patients in clinical practice to achieve full glucose control, especially for patients with elevated blood glucose after meals, and to improve PBG Measurement of blood glucose management in T2DM patients with poor compliance
.
Expert Profile Professor Yang Wenying, Chief Physician, Professor, and Doctoral Supervisor Current: Vice Chairman of the Asian Diabetes Association (AASD), Central Health Consultation Expert, Current Honorary Editor-in-Chief of Chinese Journal of Diabetes Director of Internal Medicine, Director of Teaching and Research Section of Internal Medicine, Director of Hospital Academic Committee, Chairman of Diabetes Branch of Chinese Medical Association, Honorary Chairman, Founding Editor-in-Chief of "Chinese Journal of Diabetes" • In 2012, he won the first prize of Beijing Municipal Science and Technology Progress Award and the second prize of Chinese Medical Association Science and Technology Progress Awards • 2012 National Health System Advanced Individual, Female Hero and other titles • 2013 Asian Diabetes Society (AASD) First Diabetes Epidemiology Award • 2015 Chinese Medical Association Diabetes Branch Scientific Contribution Award • 2015 Chinese Medical Doctor Association-Physician Medical Contribution Expert • Won the First National Famous Doctor-Excellence Achievement Award in 2017 References: [1] Zhang Xuelian, et al.
Chinese Journal of Diabetes.
2021,13(7):702-707.
[2] Mu Yiming, Ji Linong, Yang Wenying , Etc.
Expert consensus on management of postprandial hyperglycemia in Chinese type 2 diabetes patients[J].
Chinese Journal of Diabetes, 2016, 024(005):385-392.
[3]Yang W, et al.
N Engl J Med.
2010, 362:1090-101.
[4]Woerle HJ, Neumann C, Zschau S, et al.
Impact of fasting and postprandial glycemia on overall glycemic control in type 2 diabetes: Importance of postprandial glycemia to achieve target HbA1c levels[J].
diabetes res clin pract, 2007, 77(2):0-285.
[5]Yang W, et al.
Diabetes Obes Metab.
2019 Aug;21(8): 1973-1977.
[6]Yang W,et al.
Diabetes Res Clin Pract.
2019 Mar 11;150:158-166.
-End-Approval code: PP-HI-CN-5364 "This article is only used to provide scientific information to medical and health professionals, and does not represent the platform's position.
" For submission/reprint/business cooperation, please contact: pengsanmei@yxj.
org.
cn
