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Objetivo: analizar la correlación entre el tiempo en rango y la hemoglobina glicosilada de personas que viven con diabetes mellitus y realizan la monitorización continua de la glucemia o el automonitoreo de la glucemia capilar Método: revisión sistemática de etiología y riesgo basada en las directrices del JBI e informada según los Preferred Reporting Items for Systematic Reviews and Meta-Analyses, abarcando seis bases de datos y la literatura gris. La muestra incluyó 16 estudios y la calidad metodológica fue evaluada utilizando las herramientas del JBI. Protocolo registrado en Open Science Framework, disponible en https://doi.org/10.17605/OSF.IO/NKMZB. Resultados: tiempo en rango (70-180 mg/dl) mostró una correlación negativa con la hemoglobina glicosilada, mientras que el tiempo por encima del rango (>180 mg/dl) mostró una correlación positiva. Los coeficientes de correlación variaron entre -0,310 y -0,869 para el tiempo en rango, y entre 0,66 y 0,934 para el tiempo por encima del rango. Un estudio se realizó en una población que hacía el automonitoreo. Conclusión: hay una correlación estadísticamente significativa entre el tiempo en rango y el tiempo por encima del rango con la hemoglobina glicosilada. Cuanto mayor sea la proporción en el rango glucémico adecuado, más cerca o por debajo del 7% estará la hemoglobina glicosilada. Se necesitan más estudios que evalúen esta métrica con datos del automonitoreo de la glucemia.
Objective: to analyze the correlation between time on target and glycated hemoglobin in people living with diabetes mellitus and carrying out continuous blood glucose monitoring or self-monitoring of capillary blood glucose. Method: systematic review of etiology and risk based on JBI guidelines and reported according to Preferred Reporting Items for Systematic Reviews and Meta- Analyses, covering six databases and grey literature. The sample included 16 studies and methodological quality was assessed using JBI tools. Protocol registered in the Open Science Framework, available at https://doi.org/10.17605/OSF.IO/NKMZB. Results: time on target (70-180 mg/dl) showed a negative correlation with glycated hemoglobin, while time above target (>180 mg/dl) showed a positive correlation. Correlation coefficients ranged between -0.310 and -0.869 for time on target, and between 0.66 and 0.934 for time above target. A study was carried out on a population that performed self-monitoring. Conclusion: there is a statistically significant correlation between time on target and time above target with glycated hemoglobin. The higher the proportion in the adequate glycemic range, the closer to or less than 7% the glycated hemoglobin will be. More studies are needed to evaluate this metric with data from self-monitoring of blood glucose.
Objetivo: analisar a correlação entre o tempo no alvo e a hemoglobina glicada de pessoas que vivem com diabetes mellitus e realizam a monitorização contínua da glicemia ou a automonitorização da glicemia capilar. Método: revisão sistemática de etiologia e de risco pautada nas diretrizes do JBI e reportada conforme Preferred Reporting Items for Systematic Reviews and Meta-Analyses, abrangendo seis bases de dados e a literatura cinzenta. A amostra incluiu 16 estudos e a qualidade metodológica foi avaliada utilizando as ferramentas do JBI. Registrado protocolo no Open Science Framework, disponível em https://doi.org/10.17605/OSF.IO/NKMZB. Resultados: tempo no alvo (70-180 mg/dl) apresentou correlação negativa com a hemoglobina glicada, enquanto o tempo acima do alvo (>180 mg/dl) mostrou correlação positiva. Os coeficientes de correlação variaram entre -0,310 e -0,869 para o tempo no alvo, e entre 0,66 e 0,934 para o tempo acima do alvo. Um estudo foi efetuado com população que realizava a automonitorização. Conclusão: há correlação estatisticamente significativa entre o tempo no alvo e o tempo acima do alvo com a hemoglobina glicada. Quanto maior a proporção na faixa glicêmica adequada, mais próxima ou inferior a 7% estará a hemoglobina glicada. São necessários mais estudos que avaliem essa métrica com dados da automonitorização da glicemia.
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Humans , Blood Glucose , Glycated Hemoglobin , Blood Glucose Self-Monitoring , Diabetes Mellitus, Type 2ABSTRACT
ABSTRACT Objectives: To evaluate the alternate use of flash glucose monitoring (FGM) with self-monitoring blood glucose (SMBG), in patients with type 1 diabetes (T1D). Materials and methods: Two weeks of open FGM (P2), both preceded (P1) and followed by 2 weeks (P3) of SMBG with a blinded FGM system. Mean absolute relative difference (MARD) was calculated by (-FGMi − SMBGi-) / SMBGi, where it was a paired data sample. Results: In total, 34 patients were evaluated. Time in range (TIR) did not change between P1 and P2. In 12 patients (35.3%), TIR increased from 40% at P1 to 52% at P2 (p = 0.002) and in 22 (64.7%), TIR decreased or did not change. FGM use resulted in decreased % time spent in hypoglycemia (<70 mg/dL) (6.5% vs. 5.0%; p = 0.005), increased % time spent in hyperglycemia (>180 mg/dL) (44.5% to 51%; p = 0.046) with no significant change in % TIR. The proportion of patients who reached sensor-estimated glycated hemoglobin (eA1c) < 7% decreased from 23.5% at P1 to 12.9% at P2, p = 0.028. For the whole sample, the MARD between the two methods was 15.5% (95% CI 14.5-16.6%). For normal glucose range, hyperglycemic levels and hypoglycemic levels MARD were 16.0% (95% CI 15.0-17.0%), 13.3% (95% CI 11.5-15.2%) and 23.4% [95% CI 20.5-26.3%)], respectively. Conclusion: FGM after usual SMBG decreased the % time spent in hypoglycemia concomitant with an undesired increase in % time spent in hyperglycemia. Lower accuracy of FGM regarding hypoglycemia levels could result in overcorrection of hypoglycemia.
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This communication conceptualizes, defines and describes glucometric guardianship, as a means of ensuring optimal glycemic management. We define glucometric guardianship as the process of ensuring appropriate measurement, monitoring and analysis of glucose levels, so as to ensure alertness in glycemic management, and agility in anticipating and detecting suboptimal glycemic parameters, and responding to them. This paper hopes to draw attention to the need for glucometric science, encourage debate and discussion and facilitate research on the topic.
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Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual's health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique "continuous glucose monitoring" (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.
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Humans , Glucose , Blood Glucose , Insulin Resistance/physiology , Diabetes Mellitus, Type 2/diagnosis , Blood Glucose Self-Monitoring , Time Factors , InsulinABSTRACT
Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.
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Humans , Blood Glucose , Blood Glucose Self-Monitoring/methods , Diabetes Mellitus/diagnosis , Monitoring, Physiologic/methods , TearsABSTRACT
Continuous glucose monitoring (CGM) technology developed rapidly in recent years, and new products came out all the time. Nowadays, CGM plays an important role in diabetes management and has been recommended by various guideline all over the world. CGM equipment classification, progress on glucose sensor technology, and the new application and expansion of CGM technology in the field of diabetes and non-diabetes were briefly introduced in the study.
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Humans , Diabetes Mellitus, Type 1 , Blood Glucose , Blood Glucose Self-Monitoring , TechnologyABSTRACT
BACKGROUND@#Alcohol consumption is a prevalent behavior that is bi-directionally related to the risk of type 2 diabetes. However, the effect of daily alcohol consumption on glucose levels in real-world situations in the general population has not been well elucidated. This study aimed to clarify the relationship between alcohol consumption and all-day and time-specific glucose levels among non-diabetic individuals.@*METHODS@#We investigated 913 non-diabetic males and females, aged 40-69 years, during 2018-2020 from four communities across Japan. The daily alcohol consumption was assessed using a self-report questionnaire. All-day and time-specific average glucose levels were estimated from the interstitial glucose concentrations measured using the Flash glucose monitoring system for a median duration of 13 days. Furthermore, we investigated the association between all-day and time-specific average glucose levels and habitual daily alcohol consumption levels, using never drinkers as the reference, and performed multiple linear regression analyses after adjusting for age, community, and other diabetes risk factors for males and females separately.@*RESULTS@#All-day average glucose levels did not vary according to alcohol consumption categories in both males and females. However, for males, the average glucose levels between 5:00 and 11:00 h and between 11:00 and 17:00 h were higher in moderate and heavy drinkers than in never drinkers, with the difference values of 4.6 and 4.7 mg/dL for moderate drinkers, and 5.7 and 6.8 mg/dL for heavy drinkers. Conversely, the average glucose levels between 17:00 and 24:00 h were lower in male moderate and heavy drinkers and female current drinkers than in never drinkers; the difference values of mean glucose levels were -5.8 for moderate drinkers, and -6.1 mg/dL for heavy drinkers in males and -2.7 mg/dL for female current drinkers.@*CONCLUSIONS@#Alcohol consumption was associated with glucose levels in a time-dependent biphasic pattern.
Subject(s)
Humans , Male , Female , Diabetes Mellitus, Type 2 , Blood Glucose Self-Monitoring , Blood Glucose , Alcohol Drinking/epidemiology , Risk Factors , Alcoholic IntoxicationABSTRACT
Objective:To assess the effect of flash glucose monitoring (FGM) compared with self-monitoring of blood glucose (SMBG) on glycemic control, residual islet function, and patient-reported outcomes in children and adolescents with newly diagnosed type 1 diabetes within 1 year.Methods:133 children and adolescents with newly diagnosed T1DM in the T1D clinic of the Second Xiangya Hospital of Central South University from January 2016 to January 2020 were divided into two groups: FGM group ( n=82) and SMBG group ( n=51). The observation indexes included hemoglobin A1c (HbA 1c), fasting and postprandial blood glucose (FBG and 2 h BG), C-peptide (FCP and 2 h CP) during the one-year follow-up, Δ CP (2 h CP-FCP), patient-reported hypoglycemia and questionnaires regarding self-management of diabetes and quality of life. Results:At 6 months, HbA 1c in 2 groups was significantly decreased (all P<0.05); at 6 to 12 months, HbA 1c in FGM group tended to be stable ( P>0.05); at 12 months, HbA 1c in SMBG group was significantly increased compared with 6 months ( P=0.001). At 12 months, HbA 1c in SMBG group was higher than that in FGM group ( P=0.001). At 12 months, FBG in FGM group was equivalent to the baseline level ( P>0.05), while FBG in SMBG group was significantly higher than the baseline level ( P=0.006). 2 h BG only decreased at the 6th and 12th month in FGM group (all P<0.05). The FCP of SMBG group was significantly decreased at 12 months ( P<0.05), and the 2 h CP, Δ CP in the two groups decreased gradually (all P<0.05). FGM group had more hypoglycemic events at 6 and 12 months (all P<0.05). At 6 months, the score of Self-Management of T1D for Adolescents (SMOD-A) in FGM group was significantly improved ( P=0.001). During the follow-up period, the quality of life score of FGM group was stable ( P>0.05), while the quality of life score of SMBG group had a downward trend ( P=0.052). Conclusions:In newly diagnosed children and adolescents with T1DM, early application of FGM for blood glucose management will help to improve HbA 1c and reduce postprandial blood glucose. In addition, the self-management ability of children with FGM was improved after 6 months.
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Objective:Continuous glucose monitoring (CGM) technology is used to compare the advantages of insulin degludec (IDeg) as a basal insulin regimen compared with insulin glargine (IGlar) in the treatment of adult type 1 diabetes mellitus.Methods:30 adult patients with T1DM admitted to Heji Hospital Affiliated to Changzhi Medical College from September 2019 to December 2020 were screened. According to the random number table method, the patients were randomly divided into two groups (insulin degludec group and insulin glargine group) at a ratio of 1∶1, respectively treated with IDeg, IGlar and aspartate insulin for 12 weeks. The main outcome measures were the coefficient of variation of blood glucose (CV), mean amplitude of glycemic excursions (MAGE), time in range (TIR), time above range (TAR) and time below range (TBR). The secondary outcome measures were mean blood glucose (MBG), standard deviation of blood glucose (SD), fasting blood glucose (FPG), 2 h postprandial blood glucose (2 h BG), hemoglobin A1c (HbA 1c), means of daily differences (MOOD), and the frequency of hypoglycemic events. Results:At 12 weeks of treatment, the HbA 1c, FPG, 2 h BG, MBG, SD, CV and MAGE of insulin degludec group were lower than those of insulin glargine group, with statistically significant difference (all P<0.05). The TIR in the insulin degludec group was significantly higher than that in the insulin glargine group [73(63, 75)% vs 43(28, 63)%, P<0.001], and the TAR was lower than that in the glycerine group [25(17, 23)% vs 35(33, 64)%, P=0.003]. From the curve spectrum of blood glucose level of the two groups, the stability of blood glucose in the insulin degludec group was better than that in the insulin glargine group. After 12 weeks of treatment, 8 cases (8/15) in insulin degludec group had HbA 1c<7.0%, and 4 cases (4/15) in insulin glargine group had HbA 1c<7.0%, without statistically significant difference ( P=0.264). There were 7 cases (7/15) in the insulin degludec group and 1 case (1/15) in the insulin glargine group who achieved high quality blood glucose control, with statistically significant difference ( P=0.035). At the 12th week of outpatient follow-up, the incidence of nocturnal hypoglycemic events in insulin degludec group was significantly lower than that in insulin glargine group (4/15 vs 11/15, P=0.027). Conclusions:Compared with insulin glargine, insulin degludec can achieve higher blood glucose compliance rate, lower blood glucose level and reduce blood glucose fluctuations in patients with type 1 diabetes.
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Objective:To investigate the association between time in target range and risk of vertebral fracture in patients with type 2 diabetes.Methods:The clinical data of 1 032 patients with type 2 diabetes who were hospitalized in endocrine department of Henan Provincial People′s Hospital from June 2017 to July 2021 were collected. Among which 632 patients were included into final analysis. The diabetes-specific risk score for vertebral fracture was used to assess the risk of vertebral fracture. Multivariate linear regression analysis was used to test the association between time in target range and risk score of vertebral fracture. Risk score≥9 was defined as increased risk of vertebral fracture. Multivariate logistic regression was used to estimate the association between time in target range and risk of vertebral fracture. Results:Among the included patients, mean age was(55.0±12.4) years and the percent of male was 72.5%. The mean course of diabetes was(9.4±8.0) years, and mean score of risk of vertebral fracture was 5.6±4.3. Time in target range was negatively correlated with risk score of vertebral fracture( P for trend <0.001), which was independent of potential confounders and continuous glucose monitoring parameters. The included patients were divided into four groups based on quartiles of time in target range. Multivariate logistic regression indicated that the risk of vertebral fracture in the first quartile of time in target range was 4.6 times higherthanthatinthe4thquartile, and the significance remained adjusted for potential confounders, s, CV, or meanamplitudeofglycemicexcursions(MAGE), respectively. Conclusion:Timein target rangewasnegativelycorrelatedwithriskscoreofvertebralfracturein patient with type 2 diabetes. Low time in range level was an independent risk factor for increased risk of vertebral fracture.
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Objective:This study aimed to investigate the effect of lipohypertrophy induced by insulin injection on blood glucose fluctuation in patients with type 1 diabetes mellitus.Methods:A total of 80 patients with type 1 diabetes mellitus were recruited between June 2021 and December 2021 from the First Affiliated Hospital of Nanjing Medical University. And these patients all received insulin injection more than six months. Lipohypertrophy was assessed by ultrasound scanning, and blood glucose fluctuation was evaluated using the flash glucose monitoring system(FGM). Univariate analysis and multivariate linear regression were used to analyze the relationship of lipohypertrophy and and core indicators of blood glucose fluctuation.Results:Compared with patients without lipohypertrophy, patients with lipohypertrophy had higher mean amplitude of glycemic excursions(MAGE), coefficient of variation(CV), mean of daily differences(MODD), standard deviation(SD) of blood glucose, time above range(TAR), and high blood glucose index(HBGI; all P<0.05), while time in range(TIR) of glucose markedly become lower( P<0.01). Moreover, multivariate linear regression analysis showed that lipohypertrophy detected by ultrasound was an independent influencing factor of TIR( β=-9.423, P=0.032), MAGE( β=1.114, P=0.039), CV( β=4.304, P=0.041), MODD( β=0.717, P=0.046) after adjusting for age at diagnosis, duration of insulin injection, fasting C-peptide, and daily dose of insulin per unit weight. Conclusion:Lipohypertrophy increases glycemic variability and imposes negative impact on glycemic control rate in patients type 1 diabetes mellitus.
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Objective To design a remote diabetes management system based on dynamic blood glucose monitoring to solve the problems of traditional diabetes patient management in glucose data manual collection,unidirectional information flow and out-hospital glucose management.Methods A remote diabetes management system was developed with Java EE distributed microservices-based architecture and front-end and back-end separation mode,which used Vue for the front-end user interface design and IntelliJ IDEA development tools supporting Java language for the backend.The system developed was composed of a doctor App,a patient App and a background management terminal.The doctor App had three modules for user management,data viewing and intervention follow-up,the patient App had three modules for data monitoring,event recording and doctor-patient communication and the background management terminal had three modules for user management,data management and device management.Results The system developed realized individualized intervention and long-term glucose control based on real-time data acquisition of patient glucose fluctuation,diet,medication,exercise and other conditions.Conclusion The system developed can be used for the centralized online and offline management for in-hospital and out-hospital diabetes patients,which reduces the incidence of adverse events due to high or low blood glucose and improves the efficiency of medical staffs.[Chinese Medical Equipment Journal,2023,44(9):42-48]
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Objective:To analyze and compare the effects of conventional treatment and the dynamic 3C therapy, continuous glucose monitoring system, and on outcomes, length of hospital stay and medical costs in patients with type 2 diabetes mellitus.Methods:A total of 122 type 2 diabetes mellitus patients who visited the Department of Endocrinology of Shanxi Baiqiu'en Hospital between June 2022 and December 2022 were selected and randomized at 1:1 into the control group and the experimental group using the randomized numerical table method. The t-test and non-parametric test were used as appropriate to compare the glycemic control, length of hospital stay and medical costs of the two groups.Results:Before treatment, there was no significant difference in the indicators for blood glucose levels and fluctuations between the two groups ( P>0.05). After treatment, the glycosylated hemoglobin, fasting plasma glucose, and 2-hour postprandial blood glucose decreased in both groups. Moreover, the glycosylated hemoglobin, fasting plasma glucose, and 2-hour postprandial blood glucose showed more significant decreases in the experimental group compared with the control group after treatment. The glycemic variability indicators, including the time out of range, standard deviation of blood glucose, and the largest amplitude of glycemic excursion, decreased after treatment in both groups. The time in range increased after treatment. After treatment, the standard deviation of blood glucose and the largest amplitude of glycemic excursion in the experimental group were lower than those in the control group, and the length of hospital stay in the experimental group was shortened (all P<0.05). Conclusion:3C therapy contributes to better glycemic control and shorter hospital stay in patients with type 2 diabetes mellitus.
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Objective:To study the correlation between the time within the target range of blood glucose and the reduction of muscle mass in middle-aged and elderly patients with type 2 diabetes (T2DM).Methods:A total of 245 middle-aged and elderly T2DM patients admitted to the Second People′s Hospital of Hefei from December 2020 to December 2021 were selected. All enrolled patients wore MeiQi blood glucose monitor to obtain time in range (TIR), time above range (TAR), time below range (TBR), mean amplitude of glycemic excursions (MAGE), coefficient of variation (CV), blood glucose standard deviation (SD), largest amplitude of glycemic excursions (LAGE), which was for assessing blood sugar fluctuation. The incidence of muscle mass reduction and sarcopenia was statistically analyzed, and the differences invarious observation indicators between the muscle mass reduction group and the non muscle mass reduction group were compared. Spearman correlation analysis was used to investigate the correlation between clinical indicators and limb skeletal muscle mass index (ASMI), and logistic regression was used to analyze the influencing factors of muscle mass reduction in middle-aged and elderly T2DM patients.Results:The prevalence of muscle mass loss in 245 T2DM patients was 25.71%(63/245), and the prevalence of sarcopenia was 13.06%(32/245). There were statistically significant differences in age, gender, body mass index (BMI), blood phosphorus, homeostatic model assessment of insulin resistance (HOMA-IR), urine albumin creatine ratio (ACR), 25 hydroxyvitamin D, diabetes nephropathy (DN) patient proportion, ASMI, grip strength, and 5 sit up test times between the muscle mass reduction group and the non muscle mass reduction group (all P<0.05). The TIR of the muscle mass reduction group was lower than that of the non muscle mass reduction group, while the TAR and mean blood glucose (MG) were higher than those of the non muscle mass reduction group, with statistically significant differences (all P<0.05). ASMI was negatively correlated with age, males, and HOMA-IR (all P<0.05), but positively correlated with BMI and 25 hydroxyvitamin D (all P<0.05). ASMI was positively correlated with SD and TIR (mean P<0.05), and negatively correlated with CV, LAGE, TAR, and MG (all P<0.05). The results of univariate regression analysis showed that age, male gender, DN, and TAR were risk factors for muscle mass reduction, while BMI, 25 hydroxyvitamin D, and TIR were protective factors for muscle mass reduction (all P<0.05). After adjusting for other related factors, TIR remained a protective factor for decreased muscle mass (all P<0.05). Conclusions:TIR is an independent protective factor for muscle mass loss in middle-aged and elderly T2DM patients, and the incidence of muscle mass loss can be reduced by increasing TIR levels in clinical practice.
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OBJETIVO: Evaluar el tiempo en rango de glucosa y su asociación con otras medidas del control glicémico establecidas por el consenso internacional del tiempo en rango en usuarios de vida real del sistema flash de monitorización de glucosa FreeStyle LibreTM en Chile. MÉTODOS: Se analizaron los datos provenientes de la base de datos Freestyle Libre™ entre diciembre de 2014 y enero de 2022. Las lecturas se dividieron en 10 grupos (deciles) del mismo tamaño (cada decil contenía aproximadamente 498 usuarios) en función del tiempo en rango. Para cada decil se calculó la media de determinaciones diarias, el promedio de glucosa, la HbA1c, la desviación estándar de glucosa, el coeficiente de variación de la glucosa, el tiempo en rango, el tiempo de glucosa (porcentaje) por encima de 250 mg/dL (TA250), el tiempo de glucosa (porcentaje) por encima de 180 mg/dL (TA180), el tiempo por debajo (porcentaje) de 70 mg/dL (TB70) y el tiempo por debajo (porcentaje) de 54 mg/dL (TB54). RESULTADOS: Desde diciembre de 2014 hasta enero de 2022 hubo 4984 lectores. El grupo con el mayor tiempo en rango mostró significativamente una menor glucosa promedio que el grupo con el tiempo en rango más bajo (decil 1: media 248,3 mg/dL, decil 10: media 113,2 mg/L, diferencia 135,1 mg/dL, p<0.05). Asimismo, el mayor tiempo en rango se asoció con una menor desviación estándar (decil 1: media 93,7mg/dL, decil 10: media 26,7mg/L, diferencia: -67,0 mg/ dL, p<0,05), menor coeficiente de variación (decil 1: media 37,8%, decil 10: media 23,3%, diferencia: -14,5%, p<0,05), menor TA250 (decil 1: media 46,5%, decil 10: media 0,2%, diferencia: -46,3%, p<0.05), menor TA180 (decil 1: media 73,9%, decil 10: media 3,8%, diferencia: -70,1%, p<0.05), menor TB70 (decil 5: mediana 6,13%, decil 10: mediana 1,70%, diferencia: -4,43%, p<0.05) y menor TB54 (decil 5: mediana 1,79%, decil 10: mediana 0,12%, diferencia: -1,67%, p<0.05). El mayor tiempo en rango se asoció también significativamente con más determinaciones diarias (decil 1: media 11,4, decil 10: media 16,6, diferencia: 5,2, p<0,05). La frecuencia media de las determinaciones entre todos los lectores fue de 14,7 determinaciones diarias. CONCLUSIONES: En los pacientes con diabetes en Chile, el empleo del sistema flash de monitorización demuestra la asociación entre el mayor tiempo en rango, la reducción de la variabilidad de la glucosa y un menor riesgo de hiperglucemias e hipoglicemias y también con un mayor compromiso.
OBJECTIVE: To evaluate glucose time in range and its association with other metrics of glucose control established by the International Consensus on TIR amongst real-life patients using the Flash Glucose Monitoring system FreeStyle LibreTM in Chile. METHODS: Data from the Freestyle Libre™ database between December 2014 and January 2022 were analyzed. Readers were divided into 10 groups (deciles) of the same size (each decile had approximately 498 users) according to time in range. For each decile of time in range, the mean of daily scans, average glucose, estimated HbA1c, glucose standard deviation, glucose coefficient of variation, time in range, glucose time (percentage) above 250 mg/dL (TA250), and glucose time (percentage) above 180 mg/dL (TA180), and the median of glucose time (percentage) below 70 mg/dL (TB70) and glucose time (percentage) below 54 mg/dL (TB54), were calculated. RESULTS: From December 2014 to January 2022, there were 4984 readers. The group with the highest TIR showed significantly lower average glucose than the group with the lowest TIR (decile 1: mean 248.3 mg/dL, decile 10: mean 113.2 mg/L, difference: 135.1 mg/dL, p<0.05). In addition, more time in range was associated with a lower glucose standard deviation (decile 1: mean 93.7 mg/dL, decile 10: mean 26.7 mg/L, difference: -67.0 mg/dL, p<0.05), lower glucose coefficient of variation (decile 1: mean 37.8%, decile 10: mean 23.3%, difference: -14.5%, p<0.05), lower TA250 (decile 1: mean 46.5%, decile 10: mean 0.2%, difference: -46.3%, p<0.05),lower TA180 (decile 1: mean 73.9%, decile 10: mean 3.8%, difference: -70.1%, p<0.05), lower TB70 (decile 5: median 6.13%, decile 10: median 1.70%, difference: -4.43%, p<0.05) and lower TB54 (decile 5: median 1.79%, decile 10: median 0.12%, difference: -1.67%, p<0.05). Greater TIR was also associated with significantly more daily scans (decile 1: mean 11.4, decile 10: mean 16.6, difference: 5.2, p<0.05). Mean scan frequency amongst all readers was 14.7 daily scans. CONCLUSIONS: In patients with diabetes from Chile, the use of the flash glucose monitoring system demonstrates the association between greater TIR, reduced glucose variability, and reduced risk of hyperglycemia and hypoglycemia, and also its association with greater engagement.
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Humans , Blood Glucose Self-Monitoring/methods , Diabetes Mellitus , Glycemic Control/methods , Time Factors , Blood Glucose , Chile , Patient Compliance , Extracellular Fluid , Data AccuracyABSTRACT
La última década se ha destacado por los importantes avances en el desarrollo de nuevas tecnologías para pacientes que viven con diabetes mellitus (DM). Las innovaciones han estado orientadas principalmente a: mejorar la calidad de vida, reducir el impacto que genera la ocurrencia de hipoglucemias y reducir la carga de la enfermedad colaborando en la toma diaria de decisiones1. El monitoreo continuo de glucosa (MCG) es una herramienta que ha experimentado un importante avance al aportar información dinámica del estado metabólico en los pacientes y permitir la toma de decisiones, demostrado por un control metabólico estable, menores excursiones glucémicas, y una reducción significativa en la aparición y gravedad de las hipoglucemias2-5. Las presentes recomendaciones tienen como objetivo brindar herramientas rápidas para la interpretación de datos metabólicos y la consiguiente toma de decisiones terapéuticas. A tal fin se realizó una exhaustiva revisión de las principales guías y recomendaciones vigentes; posteriormente, el Grupo de Trabajo adaptó esa información según una serie de preguntas con criterio clínico práctico. El avance de los MCG es innegable, no solo en el desarrollo tecnológico, sino que se han convertido en una herramienta educativa para las personas con DM, su entorno y el equipo de salud al posibilitar un ajuste dinámico del tratamiento, prevenir complicaciones agudas y mejorar la calidad de vida. En esta ecuación enfatizamos la importancia de la educación diabetológica continua de la persona con DM y su entorno, participando activamente en la toma de decisiones para, de esta manera, cumplir con los objetivos propuestos: mejorar la calidad de vida, reducir la carga de la enfermedad y disminuir las excursiones glucémicas agudas.
The last decade has been highlighted by important advances in the development of new technologies for patients living with diabetes. The innovations have been oriented above all to improve the quality of life, reduce the impact generated by the occurrence of hypoglycemia and reduce the burden of the disease by collaborating in daily decision-making1. Continuous glucose monitoring (CGM) is a tool that has undergone significant progress, providing dynamic information on the metabolic status of patients, allowing decision making, demonstrated by stable metabolic control, lower glycemic excursions and a significant reduction in the occurrence and severity of hypoglycemia2-5. The purpose of these recommendations, developed by members of the Innovation Committee of the Argentine Society of Diabetes, is to provide rapid tools for the interpretation of metabolic data and the subsequent therapeutic decisionmaking. To this end, an exhaustive review of the main current guidelines and recommendations has been carried out, later the working group adapted this information according to a series of questions with practical clinical criteria. The progress of CGMs is undeniable, not only in technological development, but it has become an educational tool for people with diabetes, their environment, and the health team, offering the possibility of a dynamic adjustment of treatment, prevention of acute complications and improving quality of life. In this equation, we emphasize the importance of continuous diabetes education for the person with diabetes and their environment, actively participating in decision-making, and in this way, meeting the proposed objectives: improving quality of life, reducing the burden of disease, and decreasing acute glycemic excursions.
Subject(s)
Hypoglycemia , Blood Glucose , Glycemic Index , Glycemic Control , GlucoseABSTRACT
Abstract Introduction: in Colombia, the Clinical Practice Guidelines for the treatment of patients with type 1 (DM1) and type 2 (DM2) diabetes do not mention the use of flash glucose monitoring, as this system was not available. The objective of this study was to establish a set of recommendations for the use of intermittent flash monitoring in Colombia. Methods: the group of experts consisted of eight Colombian physicians from different cities within Colombia, with expertise in the management of patients with DM1 and DM2; a certified diabetes nurse educator; a patient with DM1; and a methodological expert. Using the Zoom Enterprise video conferencing application (Zoom Video Communications, San Jose, California), the group generated questions through the Metaplan method, then carried out a systematic literature search and evidence review. The recommendations were made according to the degree of evidence and strength of the recommendation, following the GRADE method. Results: clinical recommendations were made for: a) patients with DM1 and hypoglycemia; b) patients with DM1 and poor metabolic control; c) patients with insulin-treated DM2; d) pregestational diabetes; e) quality of life; and f) inpatient use. Conclusions: this consensus's clinical recommendations guide clinical decision making with regard to the use of intermittent flash monitoring in patients with diabetes in various clinical settings. (Acta Med Colomb 2022; 47. DOI:https://doi.org/10.36104/amc.2022.2239).
Resumen Introducción: en Colombia las Guías de Práctica Clínica para el manejo del paciente con diabetes tipo 1 (DM1) y tipo 2 (DM2) no mencionan el uso del monitoreo de glucosa flash dado que dicho sistema no estaba disponible. El objetivo del presente trabajo fue establecer un grupo de recomendaciones sobre el uso del monitoreo intermitente flash en Colombia. Métodos: el grupo de expertos estuvo conformado por ocho médicos colombianos expertos en el manejo de pacientes con DM1 y DM2 de diversas ciudades de Colombia, una enfermera licenciada educadora en diabetes, una paciente con diagnóstico de DM1 y un experto metodológico. A través de Zoom Enterprise versión de la aplicación de videoconferencia Zoom (Zoom Video Communications, San Jose, California) el grupo generó las preguntas con metodología Metaplan. Posteriormente, se realizó una búsqueda sistemática de la literatura y análisis de la evidencia. Las recomendaciones se generaron mediante grupo nominal según el grado de evidencia y la formaleza de la recomendación siguiendo la metodología GRADE. Resultados: se generaron recomendaciones clínicas enfocadas a: a) paciente con diagnóstico de DM1 e hipoglucemia; b) paciente con diagnóstico de DM1 y mal control metabólico, c) paciente con diagnóstico de DM tipo 2 tratado con insulina, d) diabetes pregestacional, e) calidad de vida y f) uso intrahospitalario. Conclusiones: las recomendaciones clínicas del presente consenso orientan la toma de decisiones clínicas con respecto al uso de monitoreo intermitente flash en el paciente con diagnóstico de diabetes en diferentes escenarios clínicos. (Acta Med Colomb 2022; 47. DOI:https://doi.org/10.36104/amc.2022.2239).
ABSTRACT
La última década se ha destacado por los importantes avances en el desarrollo de nuevas tecnologías para pacientes que viven con diabetes mellitus (DM). Las innovaciones han estado orientadas principalmente a: mejorar la calidad de vida, reducir el impacto que genera la ocurrencia de hipoglucemias y reducir la carga de la enfermedad colaborando en la toma diaria de decisiones1. El monitoreo continuo de glucosa (MCG) es una herramienta que ha experimentado un importante avance al aportar información dinámica del estado metabólico en los pacientes y permitir la toma de decisiones, demostrado por un control metabólico estable, menores excursiones glucémicas, y una reducción significativa en la aparición y gravedad de las hipoglucemias2-5. Las presentes recomendaciones tienen como objetivo brindar herramientas rápidas para la interpretación de datos metabólicos y la consiguiente toma de decisiones terapéuticas. A tal fin se realizó una exhaustiva revisión de las principales guías y recomendaciones vigentes; posteriormente, el Grupo de Trabajo adaptó esa información según una serie de preguntas con criterio clínico práctico. El avance de los MCG es innegable, no solo en el desarrollo tecnológico, sino que se han convertido en una herramienta educativa para las personas con DM, su entorno y el equipo de salud al posibilitar un ajuste dinámico del tratamiento, prevenir complicaciones agudas y mejorar la calidad de vida. En esta ecuación enfatizamos la importancia de la educación diabetológica continua de la persona con DM y su entorno, participando activamente en la toma de decisiones para, de esta manera, cumplir con los objetivos propuestos: mejorar la calidad de vida, reducir la carga de la enfermedad y disminuir las excursiones glucémicas agudas.
The last decade has been highlighted by important advances in the development of new technologies for patients living with diabetes. The innovations have been oriented above all to improve the quality of life, reduce the impact generated by the occurrence of hypoglycemia and reduce the burden of the disease by collaborating in daily decision-making1. Continuous glucose monitoring (CGM) is a tool that has undergone significant progress, providing dynamic information on the metabolic status of patients, allowing decision making, demonstrated by stable metabolic control, lower glycemic excursions and a significant reduction in the occurrence and severity of hypoglycemia2-5. The purpose of these recommendations, developed by members of the Innovation Committee of the Argentine Society of Diabetes, is to provide rapid tools for the interpretation of metabolic data and the subsequent therapeutic decisionmaking. To this end, an exhaustive review of the main current guidelines and recommendations has been carried out, later the working group adapted this information according to a series of questions with practical clinical criteria. The progress of CGMs is undeniable, not only in technological development, but it has become an educational tool for people with diabetes, their environment, and the health team, offering the possibility of a dynamic adjustment of treatment, prevention of acute complications and improving quality of life. In this equation, we emphasize the importance of continuous diabetes education for the person with diabetes and their environment, actively participating in decision-making, and in this way, meeting the proposed objectives: improving quality of life, reducing the burden of disease, and decreasing acute glycemic excursions.
Subject(s)
Blood Glucose , Glycemic ControlABSTRACT
OBJECTIVES@#Patients with classical type 1 diabetes mellitus (T1DM) require lifelong dependence on exogenous insulin therapy due to pancreatic beta-cell destruction and absolute insulin deficiency. T1DM accounts for about 90% of children with diabetes in China, with a rapid increase in incidence and a younger-age trend. Epidemiological studies have shown that the overall glycated haemoglobin (HbA1c) and compliance rate are low in Chinese children with T1DM. Optimal glucose control is the key for diabetes treatment, and maintaining blood glucose within the target range can prevent or delay chronic vascular complications in patients with T1DM. Therefore, this study aims to investigate the glycemic control of children with T1DM from Hunan and Henan Province with flash glucose monitoring system (FGMS), and to explore factors associated with glycemic variability.@*METHODS@#A total of 215 children with T1DM under 14 years old were enrolled continuously in 16 hospitals from August 2017 to August 2020. All subjects wore a FGMS device to collect glucose data. Correlation of HbA1c, duration of diabetes, or glucose scan rates with glycemic variability was analyzed. Glucose variability was compared according to the duration of diabetes, HbA1c, glucose scan rates and insulin schema.@*RESULTS@#HbA1c and duration of diabetes were positively correlated with mean blood glucose, standard deviation of glucose, mean amplitude of glucose excursions (MAGE), and coefficient of variation (CV) of glucose (all P<0.01). The glucose scan rates during FGMS wearing was significantly positively correlated with time in range (TIR) (P=0.001) and negatively correlated with MAGE and mean duration of hypoglycemia (all P<0.01). Children with duration ≤1 year had lower time below range (TBR) and MAGE when compared with those with duration >1 year (all P<0.05). TIR and TBR in patients with HbA1c ≤7.5% were higher (TIR: 65% vs 45%, TBR: 5% vs 4%, P<0.05), MAGE was lower (7.0 mmol/L vs 9.4 mmol/L, P<0.001) than those in HbA1c >7.5% group. Compared to the multiple daily insulin injections group, TIR was higher (60% vs 52%, P=0.006), MAGE was lower (P=0.006) in the continuous subcutaneous insulin infusion group. HbA1c was lower in the high scan rates (≥14 times/d) group (7.4% vs 8.0%, P=0.046), TIR was significantly higher (58% vs 47%, P<0.001), and MAGE was lower (P<0.001) than those in the low scan rate (<14 times/d) group.@*CONCLUSIONS@#The overall glycemic control of T1DM patients under 14 years old in Hunan and Henan Province is under a high risk of hypoglycemia and great glycemic variability. Shorter duration of diabetes, targeted HbA1c, higher glucose scan rates, and CSII are associated with less glycemic variability.
Subject(s)
Adolescent , Child , Humans , Blood Glucose , Blood Glucose Self-Monitoring , Diabetes Mellitus, Type 1/drug therapy , Glucose , Glycated Hemoglobin/analysis , Hypoglycemia/prevention & control , Hypoglycemic Agents/therapeutic use , Insulin/therapeutic useABSTRACT
Background@#Among the various glycemic indices in current use, glycemic variability has the greatest contribution in the development of microvascular and macrovascular complications in Type 2 Diabetes mellitus (T2DM). Most metrics that are currently used to measure glycemic variability are derived from continuous glucose monitoring (CGM) data. However, CGM is burdensome to the patient due to its relatively high cost as well as the need for multiple visits with the health care provider. With the use of serum 1,5-anhydroglucitol (1,5-AG) as a biomarker of glucose fluctuations, physicians and patients alike could have an easier surrogate measure of glycemic variability thus aiding in achieving target glucose control. This study aims to determine the diagnostic accuracy of 1,5-AG as compared to the glycemic variability metrics derived from CGM as a surrogate measure of glycemic variability among adult Filipinos with T2DM.@*Methods@#Retrospective analysis of data of adult patients aged 20 years old and above diagnosed with T2DM referred for CGM at the Diabetes, Endocrine, Metabolic, and Nutrition Center of Cardinal Santos Medical Center from January 2017 to October 2021 who underwent serum 1,5-AG level determination within 2 weeks of CGM were collected. Diagnostic accuracy was obtained by computing the sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and Youden index. Pearson correlation coefficient was used to determine the correlation of 1,5-AG and the different metrics. Analysis of variance (ANOVA) was used to check for statistical significance with 99% confidence interval and a p < 0.05 considered as statistically significant.@*Results@#This study involving 37 subjects showed a good diagnostic accuracy of serum 1,5-AG levels with the different measures of glycemic variability derived from CGM namely mean amplitude of glycemic excursion (MAGE), continuous overlapping net glycemic action at 1-hour intervals (CONGA-1), and mean of daily differences (MODD) with significant correlation among patients with HbA1c ≤ 7%. Subjects were on CGM for approximately 6 ± 1 day with statistically significant difference between the good and poor glucose control group (p<0.05). Determination of diagnostic accuracy between 1,5- AG and MAGE showed good accuracy (Sensitivity = 95.3%, Specificity = 100%, PPV = 100%, NPV = 75.43%, Diagnostic accuracy 96%, and a Youden Index of 92.3) with a statistically significant correlation among subjects with HbA1c level ≤ 7% (p=0.021). There is likewise good diagnostic accuracy between CONGA-1 and 1,5-AG level (Sensitivity = 99%, Specificity = 75.29%, PPV = 89.1%, NPV = 97%, Accuracy = 89.50% and Youden index of 58.41) with a statistically significant correlation among subjects with HbA1c ≤ 7% (p=0.038). Comparison with interday glycemic variability showed fair diagnostic accuracy between MODD and 1,5-AG (Sensitivity = 79.17%, Specificity = 78%, PPV = 97%, NPV = 32%, Accuracy = 76.89%, and Youden index of 49.07) and a statistically significant correlation among subjects with HbA1c ≤ 7% (p=0.009).@*Conclusion@#There is good diagnostic accuracy of serum 1,5-AG levels with the different measures of glycemic variability derived from CGM namely MAGE, CONGA-1, and MODD with significant correlation among patients with HbA1c ≤ 7%. Among diabetics with HbA1c ≤7%, 1,5-AG could be used as a surrogate measure of glycemic variability and excursions.