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AIMS: To assess the effects of IDegLira on glucometric indices deriving from intermittently scanned Continuous Glucose Monitoring (isCGM) in patients with type 2 diabetes (T2D). METHODS: Retrospective, observational, cohort, multi-center, "pre - post" study. All adults consecutively identified in the medical records who started treatment with IDegLira, and for whom an isCGM report before and after the initiation of IDegLira was available were included in the study. Time in range (TIR) represented the primary endpoint. Additional glucometric indices, insulin doses and body weight were also assessed. RESULTS: Overall, 87 patients were included by 5 diabetes centers [mean age 70.2 ± 11.0 years, mean duration of T2D 15.5 ± 9.6 years; BMI 29.4 ± 5.4 kg/m2, baseline HbA1c 9.1 ± 2.1%, 33% insulin naïve, 20.7% treated with basal-oral therapy (BOT), and 46% treated with multiple daily injections of insulin (MDI)]. After an average of 1.7 weeks from IDegLira initiation, TIR significantly increased from 56.8 ± 23.5% to 81.3 ± 13.5% (p < 0.0001), TAR decreased from 42.3 ± 24.2% to 17.1 ± 13.6% (p < 0.0001), while TBR remained steadily low (from 1.3 ± 2.3% to 1.4 ± 2.6%; p = 0.62). Estimated HbA1c decreased from 9.1 ± 2.1% to 6.7 ± 0.6% (p < 0.0001) and percentage of patients with a blood glucose coefficient of variation ≥ 36% dropped from 33.2 to 13.8% (p = 0.0005). In patients on MDI, the reduction in the total insulin dose was substantial (from 55.8 ± 31.2 IU to 27.2 ± 12.3 U). CONCLUSIONS: In T2D patients with poor metabolic control, either insulin naïve or treated with BOT or MDI, the introduction of IDegLira produces a significant increase in the time spent in good metabolic control and a marked reduction in glycemic fluctuations.
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AIM: To evaluate the efficacy of a fixed-ratio combination of insulin glargine 100 U/mL plus lixisenatide (iGlarLixi) in people with type 2 diabetes (T2D) using derived time-in-range (dTIR). METHODS: Participant-level data from LixiLan-L, LixiLan-O and LixiLan-G were pooled and dTIR (70-180 mg/dL), derived time-above-range (> 180 mg/dL) and derived time-below-range (dTBR; < 70 mg/dL) were calculated from participant seven-point self-monitored blood glucose profiles. RESULTS: This pooled analysis included data from 2420 participants receiving iGlarLixi (n = 1093), iGlar (n = 836), Lixi (n = 234) or a glucagon-like peptide-1 receptor agonist (GLP-1 RA) (n = 257). Numerically greater improvements in least square (LS) means dTIR were seen from baseline to end of treatment (EOT) with iGlarLixi (25.7%) versus iGlar (15.8%), Lixi (11.7%) or GLP-1 RA (16.2%). At EOT, the mean (standard deviation) dTBR was 0.71% ± 3.4%, 0.61% ± 3.2%, 0.08% ± 1.0% and 0.0% ± 0.0% for iGlarLixi, iGlar, Lixi and GLP-1 RA, respectively. In a subgroup analysis, participants aged younger than 65 years (n = 1690) and 65 years or older (n = 713) showed numerically greater improvements in LS means dTIR from baseline to EOT with iGlarLixi versus iGlar, Lixi or GLP-1 RA. CONCLUSIONS: iGlarLixi achieved improvements in dTIR, with low dTBR values, providing further evidence to inform clinical outcomes with the use of iGlarLixi.
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AIM: To map the glycaemic variabilities and insulin requirements across different phases of the menstrual cycle and assess the efficacy and performance of the MiniMed 780G system on mitigating glycaemic variabilities during phases of the menstrual cycle. MATERIALS AND METHODS: A pilot study recruiting 15 adolescent and young adult females with type 1 diabetes was conducted. Only females with regular spontaneous menstruation were enrolled in the current study. Phases of each menstrual cycle were determined as either follicular phase or luteal phase. The study analysed continuous glucose monitoring metrics during two study periods: the open loop period (OLP) and the advanced hybrid closed-loop (AHCL) period; each period lasted 3 consecutive months. RESULTS: During the OLP, the mean time in range (TIR) significantly decreased during the luteal phase compared with the follicular phase (65.13% ± 3.07% vs. 70.73% ± 2.05%) (P < .01). The mean time above range significantly increased from 21.07% ± 2.58% during the follicular phase to 24.87% ± 2.97% during the luteal phase (P < .01). After initiating the AHCL period, TIR was comparable during both phases of the menstrual cycle (P = .72), without increasing the time spent below 70 mg/dL (P > .05). Regarding insulin delivery during the AHCL period, the percentage of Auto basal and Auto correction delivered by the algorithm increased by 13.55% and 30.6%, respectively (P < .01), during the luteal phase. CONCLUSIONS: The fully automated adaptive algorithm of the MiniMed 780G system mitigated menstrual cycle-dependent glycaemic variability, successfully attaining the recommended glycaemic outcomes with a TIR greater than 70% throughout the entire menstrual cycle.
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Introduction: It is challenging for pregnant women with type 1 diabetes to maintain optimum glucose level to attain good neonatal outcomes. This study evaluated the efficacy of sensor-augmented insulin pump (SAP) with a predictive low-glucose suspend (PLGS) system in pregnant Japanese women with type 1 diabetes. Materials and methods: SAP with PLGS was used in 11 of the 22 women with type 1 diabetes who delivered between 2011 and 2021 at the two medical institutions in Japan. Glucose management, insulin delivery suspension time (IST) and neonatal outcomes were retrospectively studied. Results: In SAP with PLGS cases (n = 11), average glycated hemoglobin levels were < 6.5% throughout the pregnancy, and the time in range (TIR, 63-140 mg/dl) was > 70% in the second and third trimesters. PLGS was safely used without inducing ketoacidosis. Positive correlation was observed between IST and TIR (r = 0.62, p < 0.01). Negative correlation was observed between IST and time below range (TBR) (r = - 0.40, p = 0.02), and IST and time above range (TAR) (r = - 0.45, p = 0.01). Total daily insulin dose was adequately increased without increasing hypoglycemia. There was only one heavy-for-date HFD) infant among the 11 newborns in SAP with PLGS cases. In cases without SAP (n = 11), target glycemic levels were difficult to achieve and there were 5 HFD infants among the 11 newborns. Conclusion: SAP with PLGS was safely and effectively used in pregnant women with type 1 diabetes to achieve target glucose levels without increasing the risk of hypoglycemia, which may have led to good neonatal outcomes. Supplementary Information: The online version contains supplementary material available at 10.1007/s13340-024-00716-7.
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AIMS: Continuous glucose monitoring (CGM) systems are standard of care for youth with type 1 diabetes with the goal of spending >70% time in range (TIR; 70-180 mg/dL, 3.9-10 mmol/L). We aimed to understand paediatric CGM user experiences with TIR metrics considering recent discussion of shifting to time in tight range (TITR; >50% time between 70 and 140 mg/dL, 3.9 and 7.8 mmol/L). METHODS: Semi-structured interviews and focus groups with adolescents with type 1 diabetes and parents of youth with type 1 diabetes focused on experiences with TIR goals and reactions to TITR. Groups and interviews were audio-recorded, transcribed and analysed using content analysis. RESULTS: Thirty participants (N = 19 parents: age 43.6 ± 5.3 years, 79% female, 47% non-Hispanic White, 20 ± 5 months since child's diagnosis; N = 11 adolescents: age 15.3 ± 2 years, 55% female, 55% non-Hispanic White, 16 ± 3 months since diagnosis) attended. Participants had varying levels of understanding of TIR. Some developed personally preferred glucose ranges. Parents often aimed to surpass 70% TIR. Many described feelings of stress and disappointment when they did not meet a TIR goal. Concerns about TITR included increased stress and burden; risk of hypoglycaemia; and family conflict. Some participants said TITR would not change their daily lives; others said it would improve their diabetes management. Families requested care team support and a clear scientific rationale for TITR. CONCLUSIONS: The wealth of CGM data creates frequent opportunities for assessing diabetes management and carries implications for management burden. Input from people with type 1 diabetes and their families will be critical in considering a shift in glycaemic goals and targets.
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OBJECTIVES: This study aimed to assess the correlation between glycated hemoglobin A1 (HbA1c), time in range (TIR), and glycemic management indicator (GMI) in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) who were using a flash glucose monitoring (FGM) device (FreeStyle Libre; Abbott Diabetic Care, Witney, UK). METHODS: This was a retrospective study that looked at T1D and T2D FreeStyle Libre users' LibreView database in the period between January 2020 to June 2022. The study was conducted at the diabetes department at the King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia, following Institutional Review Board (IRB) approval. Data were collected from the LibreView website, as well as from the electronic privacy information center (EPIC) hospital records. RESULTS: Data were available for 327 patients, mean age of 33.08(±17.1) years old, and 55.7% were females. HbA1c had a statistically significant correlation with both TIR and GMI with coefficient of correlation (r) values of 0.78 (p<0.001) and 0.82 (p<0.001), respectively. A linear regression model between TIR and Hb1Ac was also developed and found to be statistically significant (p<0.001) with an acceptable R2 value (0.60). CONCLUSION: Study findings revealed that the %TIR could be a reliable predictor of Hb1Ac. Thus, Freestyle Libre was able to determine Hb1Ac as close to the lab results as possible. Therefore, it is necessary to encourage diabetes patients to achieve at least 70% TIR in order to keep Hb1Ac within the desired range.
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Background: Glycosylated hemoglobin (HbA1c) variability is a risk factor for cardiovascular complications in patients with Type 2 diabetes mellitus (T2DM), but its relationship with the severity of coronary artery disease (CAD) is unclear. Methods: Patients with T2DM who underwent coronary angiography due to angina were enrolled. HbA1c variability was expressed as coefficient of variation (CV), standard deviation (SD), variability independent of mean (VIM), and time in range (TIR). The severity of CAD was expressed by the number of involved vessels and Gensini score. Multivariate regression models were constructed to test the relationship between HbA1c variability, number of involved vessels, and the Gensini score, followed by linear regression analysis. Results: A total of 147 patients were included. In multivariate analysis, VIM-HbA1c (OR = 2.604; IQR: 1.15, 5.90; r = 0.026) and HbA1cTIR (OR = 0.13; IQR: 0.04, 0.41; r < 0.001) were independent risk factors for the number of involved vessels. After adjustment, HbA1cTIR (OR = 0.01; IQR: 0.002, 0.04; r < 0.001), SD-HbA1c (OR = 4.12, IQR: 1.64, 10.35; r = 0.001), CV-HbA1c (OR = 1.41, IQR: 1.04, 1.92; r = 0.007), and VIM-HbA1c (OR = 3.26; IQR: 1.43, 7.47; r = 0.003) were independent risk factors for the Gensini score. In the linear analysis, the Gensini score was negatively correlated with HbA1cTIR (ß = -0.629; r < 0.001) and positively correlated with SD-HbA1c (ß = 0.271; r = 0.001) and CV-HbA1c (ß = 0.176; r = 0.033). After subgroup analysis, HbA1cTIR was a risk factor for the number of involved vessels. The Gensini score was negatively correlated with HbA1cTIR and positively correlated with SD-HbA1c at subgroups of subjects with a mean HbA1c ≤ 7%. Conclusions: Our analysis indicates that HbA1c variability, especially HbA1cTIR, plays a role for the severity of CAD in patients with T2DM. HbA1c variability may provide additional information and require management even at the glycemic target. Translational Aspects: Studies have shown that HbA1c variability is related to cardiovascular complications. Further, we explore the correlation between HbA1c variability and the severity of CAD. HbA1c variability is a risk factor for coronary stenosis in T2DM. It may be a potential indicator reflecting glycemic control for the prevention and treatment of cardiovascular complications.
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Angiografía Coronaria , Enfermedad de la Arteria Coronaria , Diabetes Mellitus Tipo 2 , Hemoglobina Glucada , Índice de Severidad de la Enfermedad , Humanos , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/sangre , Hemoglobina Glucada/metabolismo , Hemoglobina Glucada/análisis , Masculino , Enfermedad de la Arteria Coronaria/sangre , Enfermedad de la Arteria Coronaria/epidemiología , Femenino , Persona de Mediana Edad , Anciano , Factores de Riesgo , Análisis MultivarianteRESUMEN
The new method of monitoring patients with diabetes using continuous glucose sensors allows for a more intimate understanding of the patient. Continuous glucose monitoring also enables the immediate adjustment of treatment. This editorial encourages community pharmacists to adapt and evolve, embracing the new paradigm that allows for closer connection with the patient and helps them interpret the data generated.
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INTRODUCTION: Imeglimin is a novel antidiabetic drug with insulinotropic and insulin-sensitizing effects that targets mitochondrial bioenergetics. We investigated acute effects of add-on therapy with imeglimin to preceding metformin on the 24-h glucose profile and glycemic variability assessed by continuous glucose monitoring (CGM) in patients with type 2 diabetes. METHODS: We studied 30 outpatients with type 2 diabetes inadequately controlled with metformin. CGM was used for 14 days straight during the research period. Imeglimin 2,000 mg/day was started on day 7 after initiating CGM. Several CGM parameters were compared between days 4-6 (prior to imeglimin treatment) and 11-13 (following the initiation of imeglimin treatment). RESULTS: After treatment with imeglimin, 24-h mean glucose was acutely decreased from 161.6 ± 48.0 mg/dL to 138.9 ± 32.2 mg/dL (p < 0.0001), while time in range (i.e., at a glucose level of 70-180 mg/dL) was significantly increased from 69.9 ± 23.9% to 80.6 ± 21.0% (p < 0.0001). Addition of imeglimin to metformin significantly decreased the standard deviation (SD) of 24-h glucose and mean amplitude of glycemic excursions, 2 indexes of glycemic variability. Baseline serum high-density lipoprotein (HDL) cholesterol was negatively correlated with changes in mean 24-h glucose (r = -0.3859, p = 0.0352) and those in SD (r = -0.4015, p = 0.0309). CONCLUSIONS: Imeglimin add-on therapy to metformin acutely lowered 24-h glucose levels and improved glycemic variability in patients with type 2 diabetes on metformin. A higher serum HDL cholesterol at baseline was associated with a better response to acute effects of imeglimin on 24-h glucose levels and glycemic variability.
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Continuous glucose monitoring (CGM) systems, including real-time CGM and intermittently scanned CGM, have revolutionized diabetes management, particularly in children and adolescents with type 1 diabetes (T1D). These systems provide detailed insights into glucose variability and detect asymptomatic and nocturnal hypoglycemia, addressing limitations of traditional self-monitoring blood glucose methods. CGM devices measure interstitial glucose concentrations constantly, enabling proactive therapeutic decisions and optimization of glycemic control through stored data analysis. CGM metrics such as time in range, time below range, and coefficient of variation are crucial for managing T1D, with emerging metrics like time in tight range and glycemia risk index showing potential for enhanced glycemic assessment. Recent advancements suggest the utility of CGM systems in monitoring the early stages of T1D and individuals with obesity complicated by pre-diabetes, highlighting its therapeutic versatility. This review discusses the current CGM systems for T1D during the pediatric age, established and emerging metrics, and future applications, emphasizing the critical role of CGM devices in improving glycemic control and clinical outcomes in children and adolescents with diabetes.
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INTRODUCTION: Continuous glucose monitoring (CGM) devices allow for 24-h real-time measurement of interstitial glucose levels and have changed the interaction between people with diabetes and their health care providers. The large amount of data generated by CGM can be analyzed and evaluated using a set of standardized parameters, collectively named glucometrics. This review aims to provide a summary of the existing evidence on the use of glucometrics data and its impact on clinical practice based on published studies involving adults and children with type 1 diabetes (T1D) in Spain. METHODS: The PubMed and MEDES (Spanish Medical literature) databases were searched covering the years 2018-2022 and including clinical and observational studies, consensus guidelines, and meta-analyses on CGM and glucometrics conducted in Spain. RESULTS: A total of 16 observational studies were found on the use of CGM in Spain, which have shown that cases of severe hypoglycemia in children with T1D were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Real-world data from Spain shows that CGM is associated with improved glycemic markers (increased time in range, reduced time below and above range, and glycemic variability), and that there is a relationship between glycemic variability and hypoglycemia. Also, CGM and analysis of glucometrics proved highly useful during the COVID-19 pandemic. New glucometrics, such as the glycemic risk index, or new mathematical approaches to the analysis of CGM-derived glucose data, such as "glucodensities," could help patients to achieve better glycemic control in the future. CONCLUSION: By using glucometrics in clinical practice, clinicians can better assess glycemic control and a patient's individual response to treatment.
Continuous glucose monitoring (CGM) devices are used to monitor glucose levels in real time over 24 h. This has changed the way people with diabetes and their health care providers interact. These devices produce a large amount of data that can be analyzed and evaluated using standardized parameters called glucometrics, which include the time a patient's glucose is in range, below range, and above range, and how much it varies over 24 h. Clinicians can use these data to better assess glycemic control and a patient's individual response to treatment. In this article, we summarize evidence from published studies involving adults and children with type 1 diabetes in Spain to look at how the use of these data has affected clinical practice. Studies have shown that cases of severe low blood glucose in children with diabetes were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Data from clinical practice in Spain show that CGM is associated with improved blood glucose markers. Many studies analyzed these data during the COVID-19 pandemic and showed that CGM and analysis of glucometrics were highly useful during this time. New glucometrics and approaches to the analysis of data from CGM could help patients achieve better blood glucose control.
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Automonitorización de la Glucosa Sanguínea , Glucemia , Diabetes Mellitus Tipo 1 , Humanos , Diabetes Mellitus Tipo 1/sangre , España , Glucemia/análisis , COVID-19 , Hipoglucemia , Niño , Adulto , SARS-CoV-2 , Monitoreo Continuo de GlucosaRESUMEN
AIMS: To compare the time in range (TIR) obtained from self-monitoring of blood glucose (SMBG) with that obtained from continuous glucose monitoring (CGM), and explore the relationship of TIR with microalbuminuria outcome, HOMA-IR and HOMA-ß test. METHODS: We recruited 400 patients with type 2 diabetes to carry out blood glucose monitoring by both SMBG and CGM for 3 consecutive days. TIR, TAR, TBR and other blood glucose variation indices were calculated respectively through the glucose data achieved from SMBG and CGM. The HOMA-IR and HOMA-ß test was evaluated by an oral glucose tolerance test. Urinary microalbumin-to-creatinine ratio completed in the laboratory. RESULTS: The median (25 %, 75 % quartile) of TIRCGM and TIRSMBG were 74.94(44.90, 88.04) and 70.83(46.88, 87.50) respectively, and there was no significant difference, p = 0.489; For every 1 % increase in TIRCGM, the risk of microalbuminuria decreased by 1.6 % (95%CI:0.973, 0.995, p = 0.006) and for every 1 % increase in TIRSMBG, the risk of microalbuminuria decreased by 1.3 % (95%CI:0.975, 0.999, p = 0.033). Stepwise multiple linear regression analysis showed an independent positive correlation between TIR (including TIRCGM and TIRSBMG) and LnDI30 and LnDI120 levels (p = 0.000). CONCLUSIONS: The TIR calculated by SMBG was highly consistent with that reported by CGM and was significantly associated with the risk of microalbuminuria and the HOMA-ß. Higher TIR quartiles were associated with lower incidence of microalbuminuria as well as higher lever of HOMA-ß. For patients with limited CGM application, SMBG-derived TIR may be an alternative to CGM-derived TIR, to assess blood glucose control.
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Albuminuria , Automonitorización de la Glucosa Sanguínea , Glucemia , Diabetes Mellitus Tipo 2 , Resistencia a la Insulina , Humanos , Albuminuria/diagnóstico , Femenino , Masculino , Persona de Mediana Edad , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/diagnóstico , Glucemia/análisis , Glucemia/metabolismo , Anciano , Resistencia a la Insulina/fisiología , Nefropatías Diabéticas/diagnóstico , Nefropatías Diabéticas/sangre , Nefropatías Diabéticas/epidemiología , Adulto , Factores de Tiempo , Prueba de Tolerancia a la Glucosa , Monitoreo Continuo de GlucosaRESUMEN
Background and Objective: In recent years, there has been growing interest in glycemic variability within the scientific community, particularly regarding its potential as an independent risk factor for diabetes-related long-term complications. This narrative review aimed to provide a comprehensive overview of short-term glycemic variability in children and adolescents with type 1 diabetes (T1D). Methods: We performed a search of published literature on the PubMed MEDLINE database using the following combination of search terms: "glycemic variability", "pediatric", "type 1 diabetes", and "children". Key Content and Findings: The widespread use of continuous glucose monitoring (CGM) systems has facilitated the characterization and quantification of glycemic fluctuations. Over the years, several metrics for assessing glycemic variability have been developed. Children and adolescents with T1D often experience wide and frequent glycemic excursions due to behavioral and hormonal factors. Several studies suggest a potential link between glycemic variability and an increased risk of diabetes-related complications. Conclusions: Glycemic variability has become an integral aspect of the routine clinical management of youths with T1D, serving as a valuable therapeutic target. However, achieving recommended glycemic targets in this population remains challenging. Further long-term data are needed to definitively establish the role of glycemic variability in the development of complications.
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BACKGROUND: The objective of this work is to document performance of automated insulin delivery (AID) during real-life use in type 2 diabetes (T2D). METHODS: A retrospective analysis was performed of continuous glucose monitoring and insulin delivery data from 796 individuals with T2D, who transitioned from 1-month predictive low-glucose suspend (PLGS) use to 3-month AID use, in real-life settings. Primary outcome was change of time in range (TIR = 70-180 mg/dL) from PLGS to AID. Secondary outcomes included time above/below range (TAR/TBR) and total daily insulin (TDI). RESULTS: Compared with PLGS, AID increased TIR on average from 63.2% to 72.6%, decreased TAR from 36.2% to 26.8%, and increased TDI from 70.2 to 76.3 U (all P < .001), without significant change to TBR. Glycemic improvements were more pronounced in those with worse glycemic control during PLGS use (P < .001). CONCLUSIONS: Real-life use of AID led to a rapid and sustained improvement of glycemic control in individuals with T2D.
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BACKGROUND: Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis. METHODS: This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree. RESULTS: Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor. CONCLUSIONS: Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.
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Biomarcadores , Automonitorización de la Glucosa Sanguínea , Glucemia , Valor Predictivo de las Pruebas , Índice de Severidad de la Enfermedad , Humanos , Estudios Transversales , Masculino , Persona de Mediana Edad , Femenino , Glucemia/metabolismo , China/epidemiología , Anciano , Factores de Tiempo , Automonitorización de la Glucosa Sanguínea/instrumentación , Biomarcadores/sangre , Factores de Riesgo , Enfermedad del Hígado Graso no Alcohólico/sangre , Enfermedad del Hígado Graso no Alcohólico/epidemiología , Enfermedad del Hígado Graso no Alcohólico/diagnóstico , Factores de Edad , Medición de Riesgo , Aprendizaje Automático , Hígado Graso/sangre , Hígado Graso/diagnóstico , Hígado Graso/epidemiología , Monitoreo Continuo de Glucosa , Pueblos del Este de AsiaRESUMEN
AIMS/HYPOTHESIS: The aim of this work was to investigate the association between macronutrient intakes and continuous glucose monitoring (CGM) metrics in individuals with type 1 diabetes. METHODS: In 470 individuals with type 1 diabetes of the GUTDM1 cohort (65% female, median age 40 [IQR 28-53] years, median diabetes duration 15 [IQR 6-29] years), we used logistic regression to establish associations between macronutrient intakes and the CGM metrics time in range (TIR, time spent between 3.9-10.0 mmol/l blood glucose, optimally set at ≥70%) and time below range (TBR, <3.9 mmol/l blood glucose, optimally set at <4%). ORs were expressed per 1 SD intake of nutrient and were adjusted for other macronutrient intakes, age, sex, socioeconomic status, BMI, duration of type 1 diabetes, pump use, insulin dose and alcohol intake. RESULTS: The median (IQR) TIR was 67 (51-80)% and TBR was 2 (1-4)%; the mean ± SD energy intake was 6879±2001 kJ, fat intake 75±31 g, carbohydrate intake 162±63 g, fibre intake 20±9 g and protein intake 70±24 g. A higher fibre intake and a lower carbohydrate intake were associated with higher odds of having a TIR≥70% (OR [95% CI] 1.64 [1.22, 2.24] and 0.67 [0.51, 0.87], respectively), whereas solely a higher carbohydrate intake was associated with TBR<4% (OR 1.34 [95% CI 1.02, 1.78]). CONCLUSIONS/INTERPRETATION: A higher fibre intake is independently associated with a higher TIR. A higher carbohydrate intake is associated with less time spent in hypoglycaemia, a lower TIR and a higher time above range. These findings warrant confirmatory (interventional) investigations and may impact current nutritional guidelines for type 1 diabetes.
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Introduction: From the introduction of continuous glucose monitoring (CGM) in treatments of type 1 diabetes, particularly its integration with insulin pumps, there has been a quest for new parameters that describe optimal glycemic control. As of the consensus reached in 2019, the ambulatory glucose profile (AGP) has become the standard, with time in range (TIR) emerging as a fundamental parameter for metabolic control assessment. However, with technological advancements, new parameters, such as the glycemia risk index (GRI), have been introduced and clinically utilized. Therefore, exploring the relationships between traditional and novel parameters to understand metabolic control comprehensively is imperative. Materials and methods: This study was conducted at the Pediatric Clinic of the University Hospital of the Republic of Srpska Banja Luka between January and July 2023. The participants were randomly selected, with the inclusion criteria specifying an age greater than eight years and a diabetes type 1 duration exceeding two years. All participants were required to use a sensor-augmented insulin pump for the next three months (90 days), irrespective of prior use, with the suspend-before-low option activated. Results: Of the 35 participants, 30 completed the study, 14 (46.7%) of whom were male. The mean age of the subjects was 14.90 ± 2.88 years, and the mean duration of diabetes was 7.83 ± 4.76 years. Over the 90-day period, HbA1c increased to an average of 7.31%. The analysis revealed significant effects of TIR (ß=-0.771) and GRI (ß=0.651) on HbA1c. Furthermore, GRI and TIR strongly correlated (ß=-0.953). Discussion and conclusion: New parameters generated from the ambulatory glucose profile (AGP) can help clinicians create a complete picture of a patient's metabolic control in relation to HbA1c levels. Additionally, the GRI is a mathematically tailored parameter that incorporates all components of the ambulatory glucose profile and demonstrates strong correlations with laboratory-measured HbA1c and TIR. The GRI potentially can become a valuable statistical parameter for evaluating and managing patients in routine clinical practice.
Asunto(s)
Automonitorización de la Glucosa Sanguínea , Glucemia , Diabetes Mellitus Tipo 1 , Hemoglobina Glucada , Sistemas de Infusión de Insulina , Humanos , Hemoglobina Glucada/análisis , Masculino , Diabetes Mellitus Tipo 1/tratamiento farmacológico , Diabetes Mellitus Tipo 1/sangre , Femenino , Niño , Glucemia/análisis , Adolescente , Automonitorización de la Glucosa Sanguínea/métodos , Insulina/administración & dosificación , Insulina/uso terapéutico , Hipoglucemiantes/administración & dosificación , Hipoglucemiantes/uso terapéutico , Control Glucémico/métodosRESUMEN
Background and aims: Cystic fibrosis related diabetes (CFRD) is correlated with worsening of nutritional status and greater deterioration of lung function. The role of new technologies for the treatment of CFRD is little explored. The aim of the study was to evaluate the efficacy of Advanced Hybrid Closed Loop (AHCL) systems on glycemic control in CF patients. Methods: A single-center retrospective study on CFRD patients using AHCL systems was performed. Glycated hemoglobin (HbA1c) values and Continuous Glucose Monitoring (CGM) metrics were collected at T0 (AHCL placement), T1 (1-month), T2 (6-months) and T3 (1-year) to evaluate glycemic control. Results: 10 patients were included in the study. Data showed a reduction of HbA1c value (7.31 ± 0.34 to 6.35 ± 1.00; p=0.03), glycemic variability (p=0.05) and insulin requirement (p=0.03). The study population reached American Diabetes Association (ADA) recommended glycemic targets at 1-year. An increase in the Time in Range (TIR) and a reduction in time in hyperglycemia were also observed, although not statistically significant. Conclusions: In patients with CFRD, the use of AHCL leads to an improvement in glycemic control in terms of HbA1c and glycemic variability. The increase in TIR and the reduction of time in hyperglycemia, although not statistically significant, are extremely encouraging from a clinical point of view. Further studies with a larger population and a longer follow-up are needed. The results of this study demonstrate the importance of proposing the use of AHCL even in CF patients, who could benefit from glycemic improvement also in terms of nutritional status and respiratory function.