Glycemic Variability Research Articles

Multidimensional Sleep Health, Glycemic Control, and Self-Reported Outcomes in Type 1 Diabetes: A Cross-Sectional Study

Abstract Context Sleep health is multidimensional. While studies have shown associations between certain sleep dimensions and health in type 1 diabetes (T1D), global sleep health has rarely been considered. Objective To examine the associations between individual sleep dimensions and multidimensional sleep health (MSH) on glycemic control and self-reported outcomes in T1D. Methods Data from 116 adults with T1D participating in a sleep study (NCT04506151) were analyzed. Sleep satisfaction and alertness were assessed by questionnaires. Sleep timing, efficiency, duration, and regularity were derived from 7-day actigraphy. A composite MSH score was created by counting “healthy sleep” across these six measures. Glycemic control was assessed by 7-day continuous glucose monitoring and A1C. Self-reported outcomes were collected through questionnaires. Results After adjusting for covariates, greater sleep irregularity was associated with higher glycemic variability (b=5.048, p<0.01), less time in range (TIR) (b=-10.806, p<0.01), higher time above range (TAR) (b=7.40, p<0.05), and higher A1C (b=0.365, p<0.05)]. Poor sleep satisfaction was associated with higher diabetes distress and depression (b=0.29, p<0.05, b=3.59, p<0.05), respectively. Later sleep timing was associated with higher depression (b=1.545, p<0.05), while lower sleep efficiency was associated with higher depression (b=1.545, p<0.01). Worse MSH was significantly associated with lower TIR (b=2.376, p<0.05), higher TAR, A1C, and depression (b=-2.38, p<0.05; b=-0.177, p<0.01; b=-1.275, p<0.05, respectively). Conclusions Sleep irregularity likely drives the association between MSH and glycemic control, while poor sleep satisfaction, lower efficiency, and later timing contribute to the association between MSH and depression. These results highlight the importance of comprehensive sleep health evaluation in T1D.

A Narrative Review of the Interplay Between Carbohydrate Intake and Diabetes Medications: Unexplored Connections and Clinical Implications

This narrative review examines the dynamic interplay between carbohydrate intake and diabetes medications, highlighting their combined molecular and clinical effects on glycemic control. Carbohydrates, a primary energy source, significantly influence postprandial glucose regulation and necessitate careful coordination with pharmacological therapies, including insulin, metformin, glucagon-like peptide (GLP-1) receptor agonists, and sodium-glucose cotransporter-2 (SGLT2) inhibitors. Low-glycemic-index (GI) foods enhance insulin sensitivity, stabilize glycemic variability, and optimize medication efficacy, while high-GI foods exacerbate glycemic excursions and insulin resistance. Continuous glucose monitoring (CGM) offers real-time insights to tailor dietary and pharmacological interventions, improving glycemic outcomes and reducing complications. Despite advancements, gaps persist in understanding nutrient–drug interactions, particularly with emerging antidiabetic agents. This review underscores the need for integrating carbohydrate-focused dietary strategies with pharmacotherapy to enhance diabetes management. Future research should prioritize clinical trials leveraging CGM technology to explore how glycemic index, glycemic load, and carbohydrate quality interact with newer diabetes medications. Such studies can refine evidence-based recommendations, support individualized care plans, and improve long-term outcomes. Addressing systemic barriers, such as limited access to dietitians and CGM technology in underserved regions, is critical for equitable care. Expanding the roles of community health workers and training healthcare providers in basic nutrition counseling can bridge gaps, promoting sustainable and inclusive diabetes management strategies. These efforts are essential for advancing personalized, effective, and equitable care for individuals with diabetes.

Automated insulin delivery in pregnant women with type 1 diabetes mellitus: a systematic review and meta-analysis.

To assess the efficacy and safety of automated insulin delivery (AID) systems compared to standard care in managing glycaemic control during pregnancy in women with Type 1 Diabetes Mellitus (T1DM). We searched MEDLINE, Cochrane Library, registries and conference abstracts up to June 2024 for randomized controlled trials (RCTs) and observational studies comparing AID to standard care in pregnant women with T1DM. We conducted random effects meta-analyses for % of 24-h time in range of 63-140mg/dL (TIR), time in hyperglycaemia (> 140mg/dl and > 180mg/dL), hypoglycaemia (< 63mg/dl and < 54mg/dL), total insulin dose (units/kg/day), glycemic variability (%), changes in HbA1c (%), maternal and fetal outcomes. Thirteen studies (450 participants) were included. AID significantly increased TIR (Mean difference, MD 7.01%, 95% CI 3.72-10.30) and reduced time in hyperglycaemia > 140mg/dL and > 180mg/dL (MD -5.09%, 95% CI -9.41 to -0.78 and MD -2.44%, 95% CI -4.69 to -0.20, respectively). Additionally, glycaemic variability was significantly reduced (MD -1.66%, 95% CI -2.73 to -0.58). Other outcomes did not differ significantly. AID systems effectively improve glycaemic control during pregnancy in women with T1DM by increasing TIR and reducing hyperglycaemia without any observed adverse short-term effects on maternal and fetal outcomes.

The sleep health composite and chronotype among children and adolescents with type 1 diabetes compared to case-control peers without diabetes.

Our objectives were to compare sleep health composite dimensions and chronotype in children and adolescents with and without type 1 diabetes (T1D) and to explore the relationship between sleep and glycemic variability in T1D. The study comprised 84 participants with T1D aged between 6 to 18 years, and age and sex matched by controls. The sleep health composite (SHC) was measured using actigraphy, sleep diaries, and self or parental reports. Sleep disturbance was evaluated using the DSM-5 Level 2 Sleep Disorders Scale Short Form. Chronotype was determined using the Children's Chronotype Questionnaire. The median total SHC score for both the T1D and control groups was 3.0 (3.0-4.0) (p=0.485). Sleep quality was reported as good by 89.3% of participants with T1D and 96.4% of controls (p=0.072). Objective data from actigraphy indicated poor sleep quality in 56% of participants with T1D and 59.5% of controls (p=0.639). Additionally, 88% of participants with T1D and 84.5% of controls had inadequate total age-appropriate sleep duration (p=0.501). Among participants with T1D, those with a stable glycemic variability (coefficient of variation [CV] <%36) had an earlier midpoint sleep (p=0.008). Our study indicates that there are no significant differences in the SHC and chronotype between children and adolescents with and without T1D. Although most participants reported good sleep quality, objective assessments indicated poor sleep quality. These findings suggest that children and adolescents may overestimate their sleep quality. Sleep patterns and chronotype in children with and without type 1 diabetes clinical Trails.gov identifier (https://www.clinicaltrials.gov), NCT06318611 (Registration Date: March 15, 2024).

Quinoa is more effective than other whole grains in the management of impaired glucose tolerance: a randomized controlled trial.

The purpose of this study was to compare the effects of quinoa versus multigrain supplementation on glycemia and lipid metabolism among individuals with impaired glucose tolerance (IGT). In total, 207 participants diagnosed with IGT were randomly assigned to the quinoa group (QG; 100 g day-1, replacing about half of the total daily staple food), multiple whole grain group (WGG; 100 g day-1), or control group (CG) and followed for one year. Biomarkers were measured before and after the intervention. At the efficacy endpoint, the quinoa group (QG) demonstrated significantly longer time in range (TIR) and normal glucose tolerance (NGT) conversion rate, along with lower rates of 2-hour postprandial glucose (2hPG), fasting insulin (FINS), homeostatic model assessment of insulin resistance (HOMA-IR), 14-day mean blood glucose (14dMBG), and diabetes mellitus development compared to those of the multigrain and control groups (P < 0.05). Significant improvements in glycated hemoglobin (HbA1c) were also found in both the quinoa and multigrain groups compared to the control group (P < 0.05). No significant difference in glycemic variability (CV) was observed between the quinoa and control groups, while a significant difference was observed between the quinoa and multigrain groups (P < 0.05). These results suggest that quinoa consumption is significantly more effective than a multiple whole-grain diet in controlling IGT by reducing postprandial glucose and HbA1c levels, improving insulin resistance, and enhancing lipid profiles, making it a superior dietary choice for managing IGT.

Relationship between glycemic variability and the incidence of postoperative atrial fibrillation following cardiac Surgery: A retrospective study from MIMIC-IV database.

This study aimed to explore the association between glycemic variability (GV) and postoperative atrial fibrillation (POAF) incidence. In this retrospective study, we included patients undergoing cardiac surgeries. GV was calculated as the coefficient of variation of blood glucose and categorized into tertiles based on its distribution. The primary endpoint was the incidence of POAF. Logistic regression and restricted cubic splines were used to assess the relationship between GV and POAF. 5365 patients were included, with a median age of 68.3 years, and 25.5 % were female. 1056 (19.7 %) patients developed new-onset POAF. Compared with the low GV group, moderate GV group (odds ratio [OR], 1.82; 95 % confidence interval [CI]: 1.49-2.22) and high GV group (OR, 2.25; 95 % CI, 1.80-2.82) were significantly associated with a higher incidence of POAF. The area under the receiver operating characteristic curve of GV in predicting POAF incidence was 0.77 (95 % CI: 0.76-0.79). There is a threshold-based nonlinear relationship between GV and the incidence of POAF: when GV was < 24 %, the likelihood of POAF increases with higher GV, whereas when GV ≥ 24 %, further increases did not significantly affect the risk of POAF. Increased GV is associated with higher incidence of POAF.

Comparative Effectiveness of Oral Hypoglycemic Agents for Glycemic Control and Glycemic Variability in Patients with Type 2 Diabetes Mellitus: Using Flash Glucose Monitoring.

The study aimed to compare the effectiveness of oral hypoglycemic agents (OHAs) as monotherapy, dual and quadruple therapy for glycemic control (GC) and glycemic variability (GV) in patients with type 2 diabetes (T2DM) using flash glucose monitoring system (FGM). Diabetes management largely relies on HbA1c monitoring. Glycemic variability has been an evolving glycemic target for preventing complications related to type 2 diabetes mellitus. The purpose of the study was to compare glycemic control measures and glycemic variability measures among study groups and to study the relationships between GC and GV indices. Retrospectively, FGM data were collected from 50 T2DM patients. The patients were classified based on prescribed number of OHAs as monotherapy [group 1: Dipeptidyl peptidase- 4 (DPP-4) inhibitors (n=10), group 2: Sodium-glucose co-transporter-2 (SGLT2) inhibitors (n=10), group 3: Sulphonylureas (n=10), group 4: Dual therapy (n=10), and group 5: Quadruple therapy (n=10)]. Measures of GC and GV were evaluated. Significant differences between study groups were observed in GC and GV measurements. The SGLT2 inhibitors monotherapy group demonstrated optimal GC [eA1c (%): 6.5 ± 2.2; MBG: 140.80 ± 63.94; TIR: 60.60 ± 19.96] and GV (SD: 42.38 ± 34.57; CV: 27.85 ± 6.68; MAGE: 96.76 ± 52.47; MODD: 33.96 ± 22.91) in comparison to other study groups. On using Pearson correlation analysis, mean blood glucose (MBG) and mean amplitude of glycemic excursion (MAGE) showed moderate correlation (r = 0.742)(r2 = 0.551), depicting distinct glucose variabilities at the same mean blood glucose levels. The monotherapy group of SGLT2 inhibitors demonstrated glucose-lowering effects with reduced glycemic variability. Hence, optimum glycemic control is associated with decreased glycemic variability.

NLRP3 Inhibitor Alleviates Glycemic Variability-Induced Cognitive Impairment in Aged Rats with Type 2 Diabetes Mellitus

Glycemic variability (GV) markedly exacerbates cognitive impairment in elderly patients with type 2 diabetes mellitus (T2DM), in part through chronic inflammation. This study investigated the therapeutic efficacy of the NLRP3 inflammasome inhibitor MCC950 in mitigating GV-induced cognitive impairment in an aged rat model of T2DM. Aged Sprague-Dawley rats with induced T2DM were subjected to GV conditions, and the effects of MCC950 were evaluated through measurement of body weight, blood glucose, lipid profiles, insulin level, inflammatory markers, and cognitive function. Transcriptomic analysis was performed on the hippocampus and prefrontal cortex. Treatment with MCC950 significantly alleviated weight loss and hyperglycemia in the GV group compared with the control group. MCC950 also reduced the levels of cholesterol, triglycerides, and pro-inflammatory markers (interleukin-1β (IL-1β) and interleukin-18 (IL-18)). Most notably, MCC950 improved spatial learning and memory retention in the GV group. Immunohistochemical analysis indicated a reduction in inflammasome activation and an increase in the expression level of the neuronal marker NeuN in the hippocampus. Transcriptomic analysis revealed that MCC950 altered neuroactive ligand-receptor interaction pathways in the hippocampus and influenced receptor binding and cell adhesion processes in the prefrontal cortex. These findings validated the efficacy of NLRP3 inhibitor in mitigating GV-induced cognitive impairment in elderly rats with T2DM and provided the basis for subsequent clinical studies exploring the broader potential of NLRP3-targeted interventions in addressing diabetes-associated cognitive impairment.

Intermittent Use of Flash Glucose Monitoring Improves Glycemic Control in Chinese Older Patients with Type 2 Diabetes Mellitus.

To explore the efficacy and safety of intermittent use of flash glucose monitoring (FGM) for improving glycemic control in Chinese elderly patients with type 2 diabetes mellitus (T2DM). This is a prospective observational study involving patients with T2DM aged ≥60 years. The study period spans 12weeks, with participants wearing FGM at weeks 0, 5, and 10. Participants were divided into two subgroups based on HbA1c at enrollment: < 7.0% and ≥7.0%. The primary outcome of the study was HbA1c level. Secondary outcomes included time in range (3.9-10mmol/L) (TIR), time below range (<3.9mmol/L) (TBR), time above range (>10.0mmol/L) (TAR), and glycemic variability (GV). A total of 68 patients completed the 12-week FGM follow-up (age 67.9 ± 5.2 years; BMI 25.4 ± 3.3kg/m²). Overall findings revealed that compared to baseline, HbA1c decreased from 7.81 ± 1.25% to 7.44±1.10% after 12weeks of intermittent wearing of FGM (p <0.001). In the subgroup analysis with HbA1c ≥7.0%, the results showed a significant reduction in HbA1c of 0.51mmol/L after 12weeks (8.36 ± 0.95% vs 7.75 ± 0.97%, p < 0.001). And there was a significant reduction in TBR in the subgroup with HbA1c < 7% (p = 0.028). Multiple linear regression analysis showed that the baseline HbA1c (β = -0.529, P<0.001), duration of T2DM (β = 0.341, P = 0.001), and the frequency of sensor use (β = -0.269, P = 0.043) were associated with the reduction in HbA1c level. Intermittent use of FGM is associated with an improvement in glycemic outcomes and reduces the risk of hypoglycemia in Chinese elderly patients with T2DM.

Association of Glycemic Variability with Outcomes in Non-diabetic Sepsis Patients: A Prospective Observational Study.

Glycemic variability (GV) is the third domain of sepsis-induced dysglycemia, after hyperglycemia and hypoglycemia, potentially leading to adverse outcomes. This study analyzed the association of GV with in-hospital mortality and length of stay (LOS) in non-diabetic sepsis patients. In this prospective observational study, non-diabetic sepsis patients were followed till day 14 of hospital stay, and blood glucose levels were assessed by finger-prick method (seven times per day) daily; clinico-laboratory and GV parameters [standard deviation (SD), coefficient of variation (CV), mean amplitude of glycemic excursion (MAGE)] were assessed on days 1, 3, 5, 7, 10, and 14 of admission. Two hundred thirteen patients were screened and 80 (mean age 45.6 ± 15.37 years; 50% men) were included in the final analysis. Patients with in-hospital mortality had significantly higher GV when compared to patients without in-hospital mortality [SD: 37.57 vs 25.21, adjusted odds ratio (aOR) 1.13, 95% confidence interval (CI) 1.02-1.24, p = 0.013; CV: 24.91 vs 16.88, aOR 1.19, 95% CI: 1.03-1.38, p = 0.016; MAGE: 73.13 vs 48.03, aOR 1.05, 95% CI: 1.01-1.11, p = 0.014], independent of illness severity (APACHE II), mean blood glucose and hypoglycemia on multivariate regression analysis. There was no significant correlation between GV and LOS. Multivariate analysis showed a significant independent association between CV and ventilator requirement (aOR 1.15, 95% CI: 1.03-1.29, p = 0.017) and between SD and need for renal replacement therapy (aOR 1.04, 95% CI: 1-1.09, p = 0.044). This study demonstrated that GV is independently associated with increased in-hospital mortality in non-diabetic sepsis patients. Further studies are required to investigate whether targeting lower GV in septic patients would translate to better outcomes. Glycemic variability in sepsis is controversial, with discordant results and a paucity of studies on the Indian population in the literature. Despite blood sugar monitoring being routinely done in sepsis patients, GV is rarely measured and the results of our study indicate that it may be worthwhile to estimate GV in sepsis. This may aid in identifying a subset of patients with increased mortality risk, who may benefit from intensive glucose monitoring and modification of insulin regimen. Prakash P, Sethi P, Vikram N, Khan M, Gupta Y, Jadon RS, et al. Association of Glycemic Variability with Outcomes in Non-diabetic Sepsis Patients: A Prospective Observational Study. Indian J Crit Care Med 2025;29(1):27-35.

How Might We Tell if Advances in Diabetes Care and Technology are Helping People to Feel Less Constrained? Introducing the Diabetes Constraints Scale.

Recent advances in diabetes care and technology, such as real-time continuous glucose monitoring, can help people live more freely, with more flexibility and fewer constraints, thereby enhancing quality of life (QOL). To date, there has been no validated means for measuring this key psychological dimension. We developed the Diabetes Constraints Scale (DCS) to assess perceived constraints pertaining to diabetes self-management. Six items were developed from qualitative interviews (20 adults with type 2 diabetes [T2D], 8 adults with type 1 diabetes [T1D]). Items were included in one study with T2D adults (N = 458) and one with T1D adults (N = 574). Scale reliability was analyzed for each study using exploratory factor analyses. Associations between DCS and key psychosocial and glycemic variables were assessed. In both studies, factor analyses revealed a single factor, with adequate internal reliability (Cronbach's alpha >.80). Both studies demonstrated significant associations in the expected direction between DCS and overall well-being, diabetes-specific QOL, and diabetes distress (all P < .001). In both studies, DCS was positively linked with the number of missed insulin boluses and the frequency of severe hypoglycemic episodes (T1D both P < .001; T2D both P < .005) and-in the T1D group only-with HbA1c (P < .001). The DCS is a reliable and valid method to determine the degree to which adults with diabetes feel constrained or limited by the disease. It may serve as a useful tool for assessing how new interventions can help individuals feel freer in the face of the demands of diabetes.

Effect of medium-chain triglycerides and whey protein isolate preloads on glycaemia in type 2 diabetes: a randomized crossover study.

Small nutritional preloads can reduce postprandial glucose excursions in individuals with and without metabolic syndrome or type 2 diabetes (T2D). However, most studies have focused on preloads administered before single meals and have predominantly used protein-based preloads. To investigate the effects of sequential consumption of medium-chain triglycerides (MCT) and whey protein isolate (WPI) preloads before breakfast, lunch, and dinner on postprandial, diurnal, and 24-h glycaemia in individuals with T2D. Participants with T2D were studied over 3 randomized 24-h periods. They consumed either water before standardized breakfast, lunch, and dinner (CONTROL), 15 g MCT before breakfast and water before lunch and dinner (MCT), or 15 g MCT before breakfast and 10 g WPI before lunch and dinner (MCT + WPI). Diurnal (08:00-23:00 h) and 24 h (08:00-08:00 h) glycaemia (incremental AUC [Iauc]) and glycemic variability (%coefficient of variation [%CV]) were evaluated by continuous glucose monitoring. Postprandial glycaemia (PPG) after breakfast and lunch was assessed by arterialized blood glucose iAUC. In 21 enrolled patients (8 males/13 females, mean ± standard deviation age 55.1 ± 8.5 y, body mass index 31.7 ± 4.3 kg·m-2, glycated hemoglobin 59 ± 12 mmol·mol-1) diurnal and 24-h iAUC were similar across interventions, whereas 24-h %CV was lower in MCT (16.8 ± 0.8%, P = 0.033) and MCT + WPI (16.1 ± 0.9%, P = 0.0004) than CONTROL (18.7 ± 0.9%). PPG iAUC was ∼17% lower after breakfast in MCT and MCT + WPI compared with CONTROL, but only the MCT + WPI lowered glucose by 20% (P = 0.002) over the entire day (08:30-17:30 h). Gastric inhibitory polypeptide (GIP) (P = 0.00004), peptide YY (PYY) (P = 0.01), and β-hydroxybutyrate (P = 0.0001) were higher in MCT and MCT + WPI than CONTROL. Subjective appetite ratings were lower after breakfast and lunch in MCT + WPI (P = 0.001). Sequential consumption of MCT and WPI preloads did not affect diurnal or 24-h glycaemia but lowered PPG and 24-h glycemic variability in individuals with T2D. These effects were associated with increased circulating β-hydroxybutyrate, PYY, and GIP, and suppression of appetite. This trial was registered at clinicaltrials.gov as NCT04905589 (https://clinicaltrials.gov/study/NCT04905589).

Glycated Haemoglobin (HbA1C) in Cardiac Surgery: A Narrative Review

Background: Perioperative dysglycaemia in cardiac surgery is associated with poor outcomes. Glycaemic variability rather than glucose levels is a predictor of the length of an ICU stay, a rise in creatinine and acute kidney injury after cardiac surgery. Glycated haemoglobin (HbA1C) values correspond closely to average blood glucose levels and cut-off values can be used to define a diabetic and pre-diabetic status. These have been correlated with perioperative events. Methods: In this narrative review, MEDLINE (via PubMed) and the Cochrane Library were used to search for the effects of different preoperative HbA1C levels on the postoperative outcomes after cardiac surgery. HbA1C values correspond closely with average blood glucose levels and cut-off values can be used to define a diabetic and pre-diabetic status; these have been correlated with perioperative events. This narrative review discusses the role of HbA1C in cardiac surgery. Discussion: The scientific data show controversial results: some systematic reviews and randomised control trials demonstrated that a high level of HbA1C seems to be an indicator for postoperative complications in cardiac surgery; other studies dissented and reported that mortality and morbidity cannot be directly attributed to HbA1c levels. Conclusions: The scientific community seems to be in general agreement that high levels of HbA1C are prognostic markers of adverse outcomes post cardiac surgery, but it has also been proved that there could be multiple underlying factors contributing to them.

Metabolic Disturbances Associated with In-Hospital Complication and Mortality in Different Types of Pneumonia.

Bakground: The mortality rate from community-acquired pneumonia (CAP) or coronavirus disease 19 (COVID-19) is high, especially in hospitalized patients. This study aimed to assess the disturbances of glucose and lipid metabolism with in-hospital complications and short-term outcomes for patients with pneumonia with different etiologies. Methods: This observational study comprised 398 patients divided as follows: 155 with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, 129 participants with viral CAP, and 114 with bacterial pneumonia. Results: Fasting plasma glucose (FPG) at admission and glycemic variation during hospitalization was linked with acute kidney injury (AKI) in bacterial CAP. Compared with a value <110 mg/dL for FPG at admission, levels between 110 and 126 mg/dL are associated with mortality in both COVID-19 (OR = 3.462, 95% CI: 1.275-9.398, p = 0.015) and bacterial CAP participants (OR = 0.254; 95% CI: 0.069-0.935, p = 0.039), while a value ≥126 mg/dL was linked with mortality only in patients with SARS-CoV-2 (OR = 3.577, 95% CI: 1.166-10.976, p = 0.026). No relation between lipid biomarkers and complications or in-hospital outcomes was observed in all three participant groups. Conclusions: Patients with bacterial CAP are more prone to developing AKI due to increased FBG at admission and glycemic variations during hospitalization, while elevated FBG values at admission are associated with mortality in both COVID-19 and bacterial CAP.

Enhanced Metabolic Control in a Pediatric Population with Type 1 Diabetes Mellitus Using Hybrid Closed-Loop and Predictive Low-Glucose Suspend Insulin Pump Treatments.

Insulin pumps coupled with continuous glucose monitoring sensors use algorithms to analyze real-time blood glucose levels. This allows for the suspension of insulin administration before hypoglycemic thresholds are reached or for adaptive tuning in hybrid closed-loop systems. This longitudinal retrospective study aims to analyze real-world glycemic outcomes in a pediatric population transitioning to such devices. We evaluated children with type 1 diabetes mellitus (T1D) admitted to the Pediatric Diabetes Department from a major University Hospital in Bucharest, Romania, who transitioned to hybrid closed-loop or predictive low-glucose suspend system from either non-automated insulin pumps or multiple daily injections. The primary outcome was assessing the change in glycated hemoglobin (HbA1c) after initiating these devices. Secondary outcomes analyzed changes in glucose metrics from the 90 days prior to the baseline and follow-up visit. 51 children were included (58.8% girls), the mean age was 10.3 ± 3.7 years, and the mean follow-up duration was 13.2 ± 4.5 months. The analyzed parameters, such as HbA1c (6.9 ± 0.7% vs. 6.7 ± 0.6%, p = 0.023), time in range (69.3 ± 11.2% vs. 76 ± 9.9%, p < 0.001), time in tight range (47.4 ± 10.9% vs. 53.7 ± 10.7%, p < 0.001), time below range (5.6 ± 2.9% vs. 3.5 ± 1.9%, p < 0.001), time above range (25 ± 11.2% vs. 20.4 ± 9.4%, p = 0.001), and coefficient of variation (37.9 ± 4.8% vs. 35.6 ± 4.6%, p = 0.001), showed significant improvements. The application of these sensor-integrated insulin pumps can significantly enhance metabolic control in pediatric populations, minimizing glycemic variations to mitigate complications and enrich the quality of life.

Association Between Glycemia, Glycemic Variability, and Pregnancy Complications in Early GDM.

To investigate the association of timing of commencing glucose management with glycemia, glycemic variability, and pregnancy outcomes among women with early gestational diabetes mellitus (GDM). In this substudy among participants of a trial of immediate vs delayed treatment of early GDM diagnosed by 2013 World Health Organization criteria, all women treated immediately and those with delayed diagnosis at 24-28 weeks' gestation (treated as if late GDM) were instructed to monitor capillary blood glucose (BG) four times a day (fasting and 2-h postprandial) until delivery. Optimal glycemia was defined as ≥95% of BG measurements between 70 and 140 mg/dL (3.9-7.8 mmol/L). Overall, 107,716 BG values were obtained from 329 of 549 (59.9%) women (mean age 32.3 ± 4.9 years, BMI 32.0 ± 8.0 kg/m2, 35% European, gestation at GDM diagnosis 15.2 ± 2.4 weeks). Women treated early (n = 213) showed lower mean glucose (MG) and mean fasting glucose (MFG) compared with those treated late (n = 116) (MG: 5.7 ± 0.4 vs. 5.9 ± 0.5, P < 0.001; MFG: 5.2 ± 0.3 vs. 5.3 ± 0.4, P = 0.004), with greater optimal glycemia (74.6% vs. 59.5%, P = 0.006) and similar glycemic variability. MG was similar from 30 weeks' gestation. Overall, optimal glycemia was achieved in 69% of women and associated with lower birth weight, fewer large-for-gestational-age infants (14.4% vs. 26.7%, P = 0.01), more small-for-gestational-age infants (15.3% vs. 5.9%, P = 0.02), and lower gestational weight gain (4.9 ± 6.4 vs. 7.6 ± 6.2 kg, P = 0.001). Suboptimal glycemia was associated with non-European ethnicity, prior GDM, 1-h glucose at booking oral glucose tolerance test, and insulin use. Both early and delayed treatment of early GDM resulted in similar glycemia toward the end of pregnancy. Early treatment was associated with improved glycemia overall.

The association between glycaemic variability and sleep quality and quantity in adults with type 1 and type 2 diabetes: A systematic review.

Individuals with diabetes frequently encounter sleep disturbances, which can detrimentally impact glycaemic management. We reviewed the relationship between sleep outcomes and glycaemic variability in adults with diabetes. We systematically searched Medline, EMBASE and Cochrane Library (2002-March 2023) for studies evaluating sleep and glycaemic variability in adults with type 1 and type 2 diabetes. Among the 3049 records, 27 met the inclusion criteria (type 1 diabetes studies = 22). Due to methodological heterogeneity, a qualitative analysis was conducted. Most studies measuring sleep quality (5 out 7; 71%) reported a significant association with glycaemic variability in type 1 and type 2 diabetes. Sleep duration was not significantly associated with glycaemic variability in type 1 diabetes, whereas other sleep metrics yielded inconclusive results. Hybrid closed-loop pump interventions (n = 12) demonstrated varying sleep outcomes with improved glycaemic variability. Similarly, sleep interventions (n = 3) consistently enhanced sleep but not glycaemic variability. Limitations included moderate to high risk of study bias, confounders, methodological heterogeneity and limited type 2 diabetes data. A potential association between sleep quality and glycaemic variability exists. However, associations with other sleep metrics remain elusive, with no discernible association between sleep duration and glycaemic variability in type 1 diabetes. Despite advancements in continuous glucose monitoring and ambulatory sleep monitoring, standardised sleep assessment methodologies are lacking in real-world studies. Establishing standard protocols for sleep assessment and defining optimal sleep targets are crucial for meaningful comparisons between studies. Understanding the complex interplay between sleep and glycaemic variability holds promise in improving diabetes management and sleep health.

Placental expression of GLUT-1, GLUT-3, and GLUT-4 mRNA and transcriptome profiling in pregnant women with diabetes.

Placental glucose transport is regulated by glucose transporter proteins (GLUTs). The study aimed to examine placental expression of GLUT-1, GLUT-3, and GLUT-4 mRNA in patients with type 1 diabetes, early gestational diabetes (eGDM), and healthy controls, and to investigate correlations between GLUTs expression and clinical parameters. Additionally, we compared placental transcriptome profiles in recruited subgroups. We recruited 59 pregnant women: 23 with type 1 diabetes, 17 with eGDM, and 19 controls. Patients with diabetes attended follow-up visits at each trimester. Transcriptome studies were performed in 4 patients per subgroup. The mean age was similar across all subgroups. eGDM patients had significantly higher BMI and were predominantly obese. We observed a significant 2-fold (P = 0.009) decrease in placental GLUT-3 mRNA expression in the type 1 diabetes and eGDM groups. GLUT-4 mRNA expression was significantly lower in the eGDM group compared to type 1 diabetes (3-fold) and controls (6-fold) (P = 0.007). There was a significant negative correlation between GLUT-3 (R = -0.29) and GLUT-4 (R = -0.27) mRNA expression and neonatal birth weight. GLUT-4 expression was negatively correlated with 1st trimester HbA1c (R = -0.72) and OGTT 120' (R = -0.82) results in eGDM patients, and 3rd trimester glycemic variability (R = -0.49) in type 1 diabetes. Microarray analysis revealed significant transcriptomic changes, with 45 down-regulated and 365 up-regulated genes in type 1 diabetes, and 21 significant changes in eGDM. Placental samples from patients with diabetes exhibit changes in GLUTs expression, which correlates with neonatal growth and several glycemic parameters. Additionally, multiple changes in transcriptomic profiles are observed in hyperglycemic patients.

Glucose Metabolism Disorders and Parkinson's Disease: Coincidence or Indicator of Dysautonomia?

Background: Parkinson's disease (PD) and type 2 diabetes mellitus (T2DM) are both age-related diseases. Evidence from recent studies suggests a link between them. The existence of an interaction between autonomic nervous system dysfunction and the dysregulation of glucose metabolism is one of the proposed mechanisms to explain the complicated relationship between these diseases. The aims of this study are to assess the incidence of glycemic dysregulation in people with PD and to identify clinical factors that may predispose patients with PD to the occurrence of metabolic disturbances. Methods: In total, 35 individuals diagnosed with PD and 20 healthy control subjects matched in terms of age and gender participated in a study consisting of clinical and biometric assessments along with 14 days of continuous glucose monitoring (CGM) using the Freestyle Libre system. In the group of patients with PD, a comparative analysis was performed between patients with and without autonomic dysfunction. The severity of autonomic dysfunction was assessed using the SCOPA-AUT. Results: Participants diagnosed with PD demonstrated a trend toward lower morning glucose levels compared to the control group. PD patients with autonomic symptoms had greater glucose variability and a deeper trend toward lower glucose levels in the mornings. The presence of autonomic dysfunction, especially orthostatic hypotension and micturition disturbance, and the severity of autonomic symptoms were associated with greater glycemic variability. Conclusions: The occurrence of autonomic disorders in the course of Parkinson's disease predisposes patients to more profound glycemic dysregulation.

Safety and efficacy of different basal insulin in type 2 diabetes mellitus with chronic kidney disease in Ramadan: prospective observational study

BackgroundDiabetic kidney disease populations are categorized as high risk for fasting in Ramadan due to various potential fasting-related complications. Insulin analogues are recommended to be used in place of human insulin during fasting, as they carry a lower risk of hypoglycaemia and stable glycaemic variability. A paucity of data exits on the safety and efficacy of different basal insulin types during fasting for this population. This study aims to evaluate the safety and efficacy of three basal insulin among patients with Type 2 Diabetes Mellitus and concomitant mild to moderate chronic kidney disease who are keen to fast during Ramadan.Materials and methodsA single-centered, prospective observational study was conducted among 46 patients with type 2 diabetes mellitus and concomitant chronic kidney disease stage 2 and 3 who were on three different types of basal insulin (Glargine U-100, Levemir, and Insulatard), fasted in Ramadan 2022. All variables were listed as median (IQR). Hypoglycaemia events and glycemic variability obtained from Freestyle Libre continuous glucose monitoring were compared between insulin groups. Changes in glycated haemoglobin, fasting plasma glucose, renal profile, body weight, body mass index, and waist circumference pre and post-Ramadan were evaluated. ResultsThe glycaemic variability was found highest in Insulatard with a median (IQR) of 37.2(33)% versus Levemir 34.4(32.4)% versus Glargine U-100 36.8(30.6)%, p = NS. Levemir had reported the lowest median time of below range of 2.5(13)% followed by Glargine 4(25)% and Insulatard 5(8)%; p = NS. The findings of this study indicated that glycated haemoglobin, fasting plasma glucose, renal profile, body weight, body mass index, and waist circumference did not alter statistically between the three groups post-Ramadan. Individually, Insulatard showed a significant reduction in weight and waist circumference (0.9kg, p = 0.026; 0.44 cm, p = 0.008) while Levemir showed a reduction in waist circumference (0.75cm, p = 0.019).ConclusionThis study revealed that Insulatard, Levemir, and Glargine demonstrated similar levels of safety and efficacy among those with diabetic kidney disease who observed fasting during Ramadan.