Glycemic Lability Research Articles

Preoperative Carbohydrate Load Does Not Alter Glycemic Variability in Diabetic and Non-Diabetic Patients Undergoing Major Gynecological Surgery: A Retrospective Study.

Background/Objectives: Elevated glycemic variability (GV) has been associated with postoperative morbidity. Traditional preoperative fasting guidelines may contribute to high GV by driving the body into catabolism. Enhanced recovery after surgery (ERAS) protocols that include a preoperative carbohydrate load (PCL) reduce hospital length of stay and healthcare costs; however, it remains unclear whether PCL improves GV in surgical patients. The aim of this retrospective study was to determine the effect of a PCL on postoperative GV in diabetic and non-diabetic patients having gynecological surgery. Methods: Retrospective data were collected on patients who had gynecological surgery before and after the rollout of an institutional ERAS protocol that included PCL ingestion. The intervention group included patients who underwent surgery in 2019 and were enrolled in the ERAS protocol and, therefore, received a PCL. The control group included patients who underwent surgery in 2016 and, thus, were not enrolled in the protocol. The primary endpoint was GV, calculated by the coefficient of variance (CV) and glycemic lability index (GLI). Results: A total of 63 patients in the intervention group and 45 in the control were analyzed. GV was not statistically significant between the groups for CV (19.3% vs. 18.6%, p = 0.65) or GLI (0.58 vs. 0.54, p = 0.86). Postoperative pain scores (4.5 vs. 5.2 p = 0.23) and incentive spirometry measurements (1262 vs. 1245 p = 0.87) were not significantly different. A subgroup analysis of patients with and without type 2 diabetes mellitus revealed no significant differences in GV for any of the subgroups. Conclusions: This retrospective review highlights the need for additional GV research, including consensus agreement on a gold standard GV measurement. Large-scale prospective studies are needed to test the effectiveness of the PCL in reducing GV.

Neonatal dysglycemia: a review of dysglycemia in relation to brain health and neurodevelopmental outcomes.

Neonatal dysglycemia has been a longstanding interest of research in neonatology. Adverse outcomes from hypoglycemia were recognized early but are still being characterized. Premature infants additionally introduced and led the reflection on the importance of neonatal hyperglycemia. Cohorts of infants following neonatal encephalopathy provided further information about the impacts of hypoglycemia and, more recently, highlighted hyperglycemia as a central concern for this population. Innovative studies exposed the challenges of management of neonatal glycemic levels with a "u-shape" relationship between dysglycemia and adverse neurological outcomes. Lately, glycemic lability has been recognized as a key factor in adverse neurodevelopmental outcomes. Research and new technologies, such as MRI and continuous glucose monitoring, offered novel insight into neonatal dysglycemia. Combining clinical, physiological, and epidemiological data allowed the foundation of safe operational definitions, including initiation of treatment, to delineate neonatal hypoglycemia as ≤47 mg/dL, and >150-180 mg/dL for neonatal hyperglycemia. However, questions remain about the appropriate management of neonatal dysglycemia to optimize neurodevelopmental outcomes. Research collaborations and clinical trials with long-term follow-up and advanced use of evolving technologies will be necessary to continue to progress the fascinating world of neonatal dysglycemia and neurodevelopment outcomes. IMPACT STATEMENT: Safe operational definitions guide the initiation of treatment of neonatal hypoglycemia and hyperglycemia. Innovative studies exposed the challenges of neonatal glycemia management with a "u-shaped" relationship between dysglycemia and adverse neurological outcomes. The importance of glycemic lability is also being recognized. However, questions remain about the optimal management of neonatal dysglycemia to optimize neurodevelopmental outcomes. Research collaborations and clinical trials with long-term follow-up and advanced use of evolving technologies will be necessary to progress the fascinating world of neonatal dysglycemia and neurodevelopment outcomes.

Alternative therapeutic strategies in diabetes management

Diabetes is a heterogeneous metabolic disease characterized by elevated blood glucose levels resulting from the destruction or malfunction of pancreatic β cells, insulin resistance in peripheral tissues, or both, and results in a non-sufficient production of insulin. To adjust blood glucose levels, diabetic patients need exogenous insulin administration together with medical nutrition therapy and physical activity. With the aim of improving insulin availability in diabetic patients as well as ameliorating diabetes comorbidities, different strategies have been investigated. The first approaches included enhancing endogenous β cell activity or transplanting new islets. The protocol for this kind of intervention has recently been optimized, leading to standardized procedures. It is indicated for diabetic patients with severe hypoglycemia, complicated by impaired hypoglycemia awareness or exacerbated glycemic lability. Transplantation has been associated with improvement in all comorbidities associated with diabetes, quality of life, and survival. However, different trials are ongoing to further improve the beneficial effects of transplantation. Furthermore, to overcome some limitations associated with the availability of islets/pancreas, alternative therapeutic strategies are under evaluation, such as the use of mesenchymal stem cells (MSCs) or induced pluripotent stem cells for transplantation. The cotransplantation of MSCs with islets has been successful, thus providing protection against proinflammatory cytokines and hypoxia through different mechanisms, including exosome release. The use of induced pluripotent stem cells is recent and requires further investigation. The advantages of MSC implantation have also included the improvement of diabetes-related comorbidities, such as wound healing. Despite the number of advantages of the direct injection of MSCs, new strategies involving biomaterials and scaffolds have been developed to improve the efficacy of mesenchymal cell delivery with promising results. In conclusion, this paper offered an overview of new alternative strategies for diabetes management while highlighting some limitations that will need to be overcome by future approaches.

GLP-1 Analogue-Loaded Glucose-Responsive Nanoparticles as Allies of Stem Cell Therapies for the Treatment of Type I Diabetes.

Type 1 diabetes (T1D) is characterized by insufficient insulin secretion due to β-cell loss. Despite exogenous insulin administration being a lifesaving treatment, many patients still experience severe glycemic lability. For these patients, a β-cell replacement strategy through pancreas or pancreatic islet transplantation is the most physiological approach. However, donors' scarcity and the need for lifelong immunosuppressive therapy pose some challenges. This study proposes an innovative biomimetic pancreas, comprising β- and α-cells differentiated from human induced pluripotent stem cells (hiPSCs) embedded in a biofunctional matrix with glucose-responsive nanoparticles (NPs) encapsulating a glucagon-like peptide 1 (GLP-1) analogue, which aims to enhance the glucose responsiveness of differentiated β-cells. Herein, glucose-sensitive pH-responsive NPs encapsulating exenatide or semaglutide showed an average size of 145 nm, with 40% association efficiency for exenatide-loaded NPs and 55% for semaglutide-loaded NPs. Both peptides maintained their secondary structure after in vitro release and showed a similar effect on INS-1E cells' insulin secretion. hiPSCs were differentiated into β- and α-cells, and insulin-positive cells were obtained (82%), despite low glucose responsiveness, as well as glucagon-positive cells (17.5%). The transplantation of the developed system in diabetic mice showed promising outcomes since there was an increase in the survival rate of those animals. Moreover, diabetic mice transplanted with cells and exenatide showed a decrease in their glucose levels. Overall, the biomimetic pancreas developed in this work showed improvements in diabetic mice survival rate, paving the way for new cellular therapies for T1D that explore the synergy of nanomedicines and stem cell-based approaches.

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis.

To perform a systematic review and meta-analysis to evaluate the association of various measures of glycemic variability, including time-domain and complexity-domain, with short-term mortality in patients with critical illness. We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023. We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU. Two authors performed independent data abstraction and risk-of-bias assessments. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios and mean difference. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty of pooled estimates. We included 41 studies (n = 162,259). We demonstrate that increased sd, coefficient of variance, glycemic lability index, and decreased time in range are probably associated with increased mortality in critically ill patients (moderate certainty) and that increased mean absolute glucose, mean amplitude of glycemic excursion, and detrended fluctuation analysis may be associated with increased mortality (low certainty). We found a consistent association between increased measures of glycemic variability and higher short-term mortality in patient with critical illness. Further research should focus on standardized measurements of glycemic variation and complexity, along with their utility as therapeutic targets and prognostic markers.

Association of blood glucose change with postoperative delirium after coronary artery bypass grafting in patients with diabetes mellitus: a study of the MIMIC-IV database.

Study results on blood glucose and the risk of delirium in patients receiving cardiac surgery are inconsistent, and there is also a gap in how to manage blood glucose after coronary artery bypass grafting (CABG). This study focused on patients with diabetes mellitus (DM) undergoing CABG and explored the associations of different blood glucose-related indexes and blood glucose change trajectory with postoperative delirium (POD), with the aim of providing some information for the management of blood glucose in this population. Data of patients with DM undergoing CABG were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database in this retrospective cohort study. The blood glucose-related indexes included baseline blood glucose, mean blood glucose (MBG), mean absolute glucose (MAG), mean amplitude of glycemic excursions (MAGE), glycemic lability index (GLI), and largest amplitude of glycemic excursions (LAGE). The MBG trajectory was classified using the latent growth mixture modeling (LGMM) method. Univariate and multivariate logistic regression analyses were utilized to screen covariates and explore the associations of blood glucose-related indexes and MBG trajectory with POD. These relationships were also assessed in subgroups of age, gender, race, estimated glomerular filtration rate (eGFR), international normalized ratio (INR), sepsis, mechanical ventilation use, and vasopressor use. In addition, the potential interaction effect between blood glucose and hepatorenal function on POD was investigated. The evaluation indexes were odds ratios (ORs), relative excess risk due to interaction (RERI), attributable proportion of interaction (AP), and 95% confidence intervals (CIs). Among the eligible 1,951 patients, 180 had POD. After adjusting for covariates, higher levels of MBG (OR = 3.703, 95% CI: 1.743-7.870), MAG >0.77 mmol/L/h (OR = 1.754, 95% CI: 1.235-2.490), and GLI >2.6 (mmol/L)2/h/per se (OR = 1.458, 95% CI: 1.033-2.058) were associated with higher odds of POD. The positive associations of MBG, MAG, and GLI with POD were observed in patients aged <65 years old, male patients, White patients, those with eGFR <60 and INR<1.5, patients with sepsis, and those who received mechanical ventilation and vasopressors (all p < 0.05). Patients with class 3 (OR = 3.465, 95% CI: 1.122-10.696) and class 4 (OR = 3.864, 95% CI: 2.083-7.170) MBG trajectory seemed to have higher odds of POD, compared to those with a class 1 MBG trajectory. Moreover, MAG (RERI = 0.71, 95% CI: 0.14-1.27, AP = 0.71, 95% CI: 0.12-1.19) and GLI (RERI = 0.78, 95% CI: 0.19-1.39, AP = 0.69, 95% CI: 0.16-1.12) both had a potential synergistic effect with INR on POD. Focusing on levels of MBG, MAG, GLI, and MBG trajectory may be more beneficial to assess the potential risk of POD than the blood glucose level upon ICU admission in patients with DM undergoing CABG.

Diagnosis and treatment of anti-insulin antibody-mediated labile glycaemia in insulin-treated diabetes.

Anti-insulin antibodies in insulin-treated diabetes can derange glycaemia, but are under-recognised. Detection of significant antibodies is complicated by antigenically distinct insulin analogues. We evaluated a pragmatic biochemical approach to identifying actionable antibodies, and assessed its utility in therapeutic decision making. Forty people with insulin-treated diabetes and combinations of insulin resistance, nocturnal/matutinal hypoglycaemia, and unexplained ketoacidosis were studied using broad-specificity insulin immunoassays, polyethylene glycol (PEG) precipitation and gel filtration chromatography (GFC) with or without ex vivo insulin preincubation. Twenty-seven people had insulin immunoreactivity (IIR) below 3000 pmol/L that fell less than 50% after PEG precipitation. Insulin binding by antibodies in this group was low and judged insignificant. In 8 people IIR was above 3000 pmol/L and fell by more than 50% after PEG precipitation. GFC demonstrated substantial high molecular weight (HMW) IIR in 7 of these 8. In this group antibodies were judged likely significant. In 2 people immunosuppression was introduced, with a good clinical result in one but only a biochemical response in another. In 6 people adjustment of insulin delivery was subsequently informed by knowledge of underlying antibody. In a final group of 5 participants IIR was below 3000 pmol/L but fell by more than 50% after PEG precipitation. In 4 of these GFC demonstrated low levels of HMW IIR and antibody significance was judged indeterminate. Anti-insulin antibodies should be considered in insulin-treated diabetes with unexplained glycaemic lability. Combining immunoassays with PEG precipitation can stratify their significance. Antibody depletion may be beneficial, but conservative measures often suffice.

Validating and Establishing a Diagnostic Threshold for the Hypoglycemia Awareness Questionnaire Impaired Awareness Subscale

ObjectiveTo evaluate the discriminant and convergent validities of the Hypoglycemia Awareness Questionnaire Impaired Awareness (HypoA-Q IA) subscale and establish a diagnostic threshold for the classification of impaired awareness of hypoglycemia (IAH) in adults with type 1 diabetes (T1D). MethodsTwenty-one adults with T1D (male, 48%; median age, 36 years; and T1D duration, 21 years) completed the HypoA-Q IA subscale, Clarke, and hypoglycemia severity (HYPO) scores, continuous glucose monitoring, and hyperinsulinemic hypoglycemic clamp testing. Those with IAH defined by a Clarke score of ≥4 (n = 10) and who experienced severely problematic hypoglycemia and/or marked glycemic lability started automated insulin delivery as part of an 18-month intervention study with the 6-monthly paired assessment of the HypoA-Q IA subscale, Clarke score, HYPO score and continuous glucose monitoring, and hypoglycemic clamp testing at baseline and 6 and 18 months. ResultsThe HypoA-Q IA subscale discriminated between those with and without IAH defined by the Clarke score (W = 110.5; P <.001). During intervention, the HypoA-Q IA subscale demonstrated convergent validity via significant relationships with the Clarke (r = 0.72; P <.001) and HYPO (r = 0.60; P <.001) scores; hypoglycemia exposure below 70 (r = 0.53; P <.01), 60 (r = 0.50; P <.01), and 54 (r = 0.48; P <.01) mg/dL; and autonomic symptom (r = −0.53; P <.05), epinephrine (r = −0.68; P <.001), and pancreatic polypeptide (r = −0.52; P <.05) responses to insulin-induced hypoglycemia. The receiver operating characteristic curve analysis revealed that the HypoA-Q IA subscale was an excellent predictor of an abnormal symptom response to insulin-induced hypoglycemia (area under the curve, 0.86) with a score of 12, which was the optimal threshold for IAH classification (sensitivity, 83%; specificity, 80%). ConclusionThese findings support the validity of the HypoA-Q IA subscale and propose a HypoA-Q IA diagnostic threshold to identify IAH in both clinical and research settings.

Challenges of Glycemic Control in People With Diabetes and Advanced Kidney Disease and the Potential of Automated Insulin Delivery.

Diabetes is the leading cause of chronic kidney disease (CKD) and end-stage kidney disease in the world. It is known that maintaining optimal glycemic control can slow the progression of CKD. However, the failing kidney impacts glucose and insulin metabolism and contributes to increased glucose variability. Conventional methods of insulin delivery are not well equipped to adapt to this increased glycemic lability. Automated insulin delivery (AID) has been established as an effective treatment in patients with type 1 diabetes mellitus, and there is emerging evidence for their use in type 2 diabetes mellitus. However, few studies have examined their role in diabetes with concurrent advanced CKD. We discuss the potential benefits and challenges of AID use in patients with diabetes and advanced CKD, including those on dialysis.

Hyperglycemia and Glycemic Variability Associated with Glucocorticoids in Women without Pre-Existing Diabetes Undergoing Neoadjuvant or Adjuvant Taxane Chemotherapy for Early-Stage Breast Cancer

Glucocorticoids, which are administered with chemotherapy, cause hyperglycemia. Glycemic variability among breast cancer patients without diabetes is not well known. A retrospective cohort study was conducted involving early-stage breast cancer patients without diabetes who received dexamethasone prior to neoadjuvant or adjuvant taxane chemotherapy between August 2017-December 2019. Random blood glucose levels were analyzed, and steroid-induced hyperglycemia (SIH) was defined as a random glucose level of >140 mg/dL. A multivariate proportional hazards model was used to identify the risk factors of SIH. Out of 100 patients, the median age was 53 years (IQR: 45-63.5). A total of 45% of patients were non-Hispanic White, 28% Hispanic, 19% Asian, and 5% African American. The incidence of SIH was 67%, and glycemic fluctuations were highest in those with glucose levels of >200 mg/dL. Non-Hispanic White patients represented a significant predictor for time to SIH, with a hazard ratio of 2.5 (95% CI: 1.04, 5.95, p = 0.039). SIH was transient in over 90% of the patients, and only seven patients remained hyperglycemic after glucocorticoid and chemotherapy completion. Pretaxane dexamethasone-induced hyperglycemia was observed in 67% of the patients, with the greatest glycemic lability in those patients with blood glucose levels of >200 mg/dL. The non-Hispanic White patients had a higher risk of developing SIH.

Glycemia and Neonatal Encephalopathy: Outcomes in the LyTONEPAL (Long-Term Outcome of Neonatal Hypoxic EncePhALopathy in the Era of Neuroprotective Treatment With Hypothermia) Cohort

To assess in newborns with neonatal encephalopathy (NE), presumptively related to a peripartum hypoxic-ischemic event, the frequency of dysglycemia and its association with neonatal adverse outcomes. We conducted a secondary analysis of LyTONEPAL, a population-based cohort study including 545 patients with moderate to severe NE. Newborns were categorized by the glycemia values assessed by routine clinical care during the first 3 days of life: normoglycemic (all glycemia measurements ranged from 2.2 to 8.3 mmol/L), hyperglycemic (at least one measurement > 8.3 mmol/L), hypoglycemic (at least one measurement < 2.2 mmol/L), or with glycemic lability (measurements included at least one episode of hypoglycemia and one of hyperglycemia). The primary adverse outcome was a composite outcome defined by death and/or brain lesions on MRI, regardless of severity or location. 199 newborns were categorized as normoglycemic (36.5%), 74 hypoglycemic (13.6%), 213 hyperglycemic (39.1%), and 59 (10.8%) with glycemic lability, based on the 2,593 glycemia measurements collected. The primary adverse outcome was observed in 77 (45.8%) normoglycemic newborns, 37 (59.7%) with hypoglycemia, 137 (67.5%) with hyperglycemia, and 40 (70.2%) with glycemic lability (P<.01). With the normoglycemic group as the reference, the adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) for the adverse outcome were significantly higher for the group with hyperglycemia (aOR, 1.81 95%CI, 1.06-3.11). Dysglycemia affects nearly two-thirds of newborns with NE and is independently associated with a higher risk of mortality and/or brain lesions on MRI.

Glucometrics in the first week of critical illness and its association with mortality

ObjectiveEvaluation of glucometrics in the first week of ICU stay and its association with outcomes. DesignProspective observational study. SettingMixed ICU of teaching hospital. PatientsAdults initiated on insulin infusion for 2 consecutive blood glucose (BG) readings ≥180mg/dL. Main variables of interestGlucometrics calculated from the BG of first week of admission: hyperglycemia (BG>180mg/dL) and hypoglycemia (BG<70mg/dL) episodes; median, standard deviation (SD) and coefficient of variation (CV) of BG, glycemic lability index (GLI), time in target BG range (TIR). Factors influencing glucometrics and the association of glucometrics to patient outcomes analyzed. ResultsA total of 5762 BG measurements in 100 patients of median age 55 years included. Glucometrics: hyperglycemia: 2253 (39%), hypoglycemia: 28 (0.48%), median BG: 169mg/dL (162–178.75), SD 31mg/dL (26–38.75), CV 18.6% (17.1–22.5), GLI: 718.5 [(mg/dL)2/h]/week (540.5–1131.5) and TIR 57% (50–67).Diabetes and higher APACHE II score were associated with higher SD and CV, and lower TIR. On multivariate regression, diabetes (p=0.009) and APACHE II score (p=0.016) were independently associated with higher SD.Higher SD and CV were associated with less vasopressor-free days; lower TIR with more blood-stream infections (BSI). Patients with higher SD, CV and GLI had a higher 28-day mortality. On multivariate analysis, GLI alone was associated with a higher mortality (OR 2.99, p=0.04). ConclusionsGlycemic lability in the first week in ICU patients receiving insulin infusion is associated with higher mortality. Lower TIR is associated with more blood stream infections.

Glycemic control and blood gas sampling frequency during continuous glucose monitoring in the intensive care unit: A before-and-after study.

Whether subcutaneous continuous glucose monitoring (CGM) can safely replace intermittent arterial blood gas glucose analyses in intensive care unit (ICU) patients remains uncertain. We aimed to compare CGM to blood gas glucose values and assess whether CGM use reduces blood gas sampling frequency and glucose variability in ICU patients with type 2 diabetes managed with liberal glucose control. We used the FreeStyle Libre CGM in 15 ICU patients and compared their blood glucose metrics with a pre-CGM control population of 105 ICU patients with type 2 diabetes. Both groups received insulin to target glucose range of 10-14 mmol/L. We used linear regression analysis adjusted for illness severity to assess the association of CGM use with blood gas sampling frequency and glucose variability. We used mean absolute relative difference (MARD) and Clarke error grid analysis to assess accuracy of matched CGM-blood glucose values overall, across glucose stata (<10, 10-14, >14 mmol/L), and over time (≤48, 48-96, >96 h). We analyzed 483 matched glucose values. Overall MARD was 11.5 (95% CI, 10.7-12.3)% with 99% of readings in Clarke zones A and B. MARD was 15.5% for glucose values <10 mmol/L, 11.1% at 10-14 mmol/L, and 11.4% >14 mmol/L. MARD was 13.8% in the first 48 h, 10.9% at 48-96 h, and 8.9% beyond 96 h. CGM use was associated with 30% reduction in blood gas sampling frequency. CGM use was not associated with glucose variability as determined by glycemic lability index or standard deviation of blood glucose. In our cohort of ICU patients with type 2 diabetes receiving liberal glycemic control, CGM showed acceptable accuracy and was associated with a reduction in blood gas sampling frequency without compromising glucose control. Lowest accuracy was observed at glucose values below 10 mmol/L and during the first 48 h of CGM use.

Evaluation of Clinical Metrics for Identifying Defective Physiologic Responses to Hypoglycemia in Long-Standing Type 1 Diabetes.

Repeated hypoglycemia exposure leads to impaired awareness of hypoglycemia (IAH) and the development of defective counterregulatory responses. To date, only pancreas or islet transplantation has demonstrated normalization of hypoglycemia awareness and the endogenous glucose production (EGP) response to defend against insulin-induced hypoglycemia in long-standing type 1 diabetes (T1D). This study aims to validate clinical metrics of IAH (Clarke score), hypoglycemia severity (HYPO score), glycemic lability (lability index), and continuous glucose monitoring (CGM) as predictors of absent autonomic symptom (AS) recognition and defective glucose counterregulation during insulin-induced hypoglycemia, thus enabling early identification of individuals with compromised physiologic defense against clinically significant hypoglycemia. Forty-three subjects with mean ± standard deviation age 43 ± 13 years and T1D duration 28 ± 13 years, including 32 with IAH and 11 with hypoglycemia awareness (Aware), and 12 nondiabetic control subjects, underwent single-blinded randomized-paired hyperinsulinemic-euglycemic and hypoglycemic clamp experiments. Receiver operating characteristic (ROC) curves and sensitivity analyses were performed to assess metric prediction of absent AS recognition and defective EGP responses to hypoglycemia. Clarke score and CGM measures of hypoglycemia exposure demonstrated good ability to predict absent AS recognition (area under the curve ≥0.80). A composite threshold of IAH-Clarke ≥4 with ROC curve-derived thresholds for CGM measures of hypoglycemia exposure showed high specificity and predictive value in identifying an absent AS response during the hypoglycemic clamp. Metrics demonstrated poor ability to predict defective glucose counterregulation by the EGP response, which was impaired even in the Aware group. Screening for IAH alongside assessment of CGM data can increase the specificity for identifying individuals with absent hypoglycemia symptom recognition who may benefit from further intervention.

0585 Use of a Hybrid Closed Loop Insulin Delivery System Improves Sleep and Glycemic Control in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness

Abstract Introduction Insulin delivery and continuous glucose monitoring systems (CGMs) have been reported to disrupt sleep in individuals with type 1 diabetes (T1D), potentially thwarting the adoption and continued use of diabetes therapeutic technologies. This study assessed changes in actigraphic sleep and glycemic outcomes in individuals at high risk for life threatening nocturnal hypoglycemia after initiating a hybrid closed loop (HCL) insulin delivery system with integrated CGM. Methods 10 adults (median age=51y) with long-standing T1D (median duration=34y) and hypoglycemia unawareness participated in an 18-month ongoing clinical trial assessing the effectiveness of a HCL system. Wrist actigraphs and CGMs measured sleep and glycemic control, respectively, at baseline (1 week) and at months 3, 6, 9, 12, 15, and 18 (3 weeks) following HCL initiation. Body mass index and hemoglobin A1c (HbA1c) were also collected at these timepoints. Hypoglycemia awareness was assessed using the Clarke hypoglycemia questionnaire, HYPO score, and glycemic lability index. Paired sample t-tests and Cohen’s d effect sizes modeled changes in sleep, glycemic control, and hypoglycemic awareness and the magnitude of these changes from baseline to 18 months. Results Sleep improved from baseline to 18 months [shorter sleep latency (p&amp;lt;0.01), later sleep offset (p&amp;lt;0.05), and less wake after sleep onset (WASO) (&amp;lt;0.01)]. Medium effect sizes were found for later sleep onset (d=0.74) and later sleep midpoints (d=0.77). HCL also improved hypoglycemia awareness from baseline to 18 months [Clarke score (p&amp;lt;0.01), HYPO score (p&amp;lt;0.01), lability index (p&amp;lt;0.05)]. Medium to large effect sizes were found for reduced nocturnal hypoglycemia (percent time glucose was &amp;lt;54mg/dL,&amp;lt;60mg/dL,&amp;lt;70mg/dL; d=0.66 – 0.81), daytime and nocturnal hypoglycemia (percent time glucose was&amp;lt;54mg/dL,&amp;lt;60mg/dL,&amp;lt;70mg/dL; d=0.61 – 0.69), and glucose variability (coefficient of variability; d=0.62). Conclusion HCL insulin delivery with CGM improved sleep over time as indicated by shorter sleep onset latency, later sleep offset, and less WASO. HCL insulin delivery also improved hypoglycemia awareness and led to clinically significant reductions in hypoglycemia and glucose variability. Support (If Any) NIH (R01DK117488 (NG), R01DK091331 (MRR), K99NR017416 (SKM), and UL1TR001878 (University of Pennsylvania Center for Human Phenomic Science)). National Aeronautics and Space Administration (NASA) (NNX14AN49G and 80NSSC20K0243 (NG)) and from the Pennsylvania Department of Health (SAP 4100079750 (IL)).

Acute glycemic variability and risk of mortality in patients with sepsis: a meta-analysis

BackgroundAcute glycemic variability (GV) has been correlated with the severity of sepsis. The aim of the study was to evaluate the potential association between acute GV and mortality risk in patients with sepsis.MethodsCohort studies comparing the risk of death within 3 months between septic patients with higher versus lower acute GV were retrieved by systematic search of Medline, Embase, Web of Science, Wanfang and CNKI databases. We used a random-effect model to pool the data by incorporating the between-study heterogeneity. Sensitivity analyses were performed to evaluate the stability of the findings.ResultsTen studies including 4296 patients were available for the meta-analysis. Pooled results showed that septic patients with higher acute GV had significantly increased mortality risk compared to those with lower acute GV, as evidenced by results using different parameters including standard deviation of blood glucose (SDBG, risk ratio [RR]: 1.74, 95% confidence interval [CI] 1.36–2.24, p < 0.001; I2 = 0%), coefficient of variation of blood glucose (RR: 1.91, 95% CI 1.57–2.31, p < 0.001; I2 = 0%), mean amplitude of glycemic excursion (RR: 1.81. 95% CI 1.36–2.40, p < 0.001; I2 = 0%), and glycemic lability index (RR: 2.52, 95% CI 1.72–3.68, p < 0.001; I2 = 0%). Sensitivity analyses by excluding one study at a time did not significantly affect the results (p all < 0.05).ConclusionsHigher acute GV may be a predictor of mortality risk in patients with sepsis.

Glycemic Variability Is Independently Associated With Poor Prognosis in Five Pediatric ICU Centers in Southwest China.

BackgroundGlucose variability (GV) is a common complication of dysglycemia in critically ill patients. However, there are few studies on the role of GV in the prognosis of pediatric patients, and there is no consensus on the appropriate method for GV measurement. The objective of this study was to determine the “optimal” index of GV in non-diabetic critically ill children in a prospective multicenter cohort observational study. Also, we aimed to confirm the potential association between GV and unfavorable outcomes and whether this association persists after controlling for hypoglycemia or hyperglycemia.Materials and MethodsBlood glucose values were recorded for the first 72 h and were used to calculate the GV for each participant. Four different metrics [SD, glycemic lability index (GLI), mean absolute glucose (MAG), and absolute change of percentage (ACACP)] were considered and compared to identify the “best” GV index associated with poor prognosis in non-diabetic critically ill children. Among the four metrics, the SD was most commonly used in previous studies, while GLI- and MAG-integrated temporal information, that is the rate and magnitude of change and the time interval between glucose measurements. The fourth metric, the average consecutive ACACP, was introduced in our study, which can be used in real-time clinical decisions. The primary outcome of this study was the 28-day mortality. The receiver operating characteristic (ROC) curve analysis was conducted to compare the predictive power of different metrics of GV for the primary outcome. The GV index with the largest area under ROC curve (AUC) was chosen for subsequent multivariate analyses. Multivariate Cox regression analysis was performed to identify the potential predictors of the outcome. To compare the contribution in 28-day mortality prognosis between glycemic variability and hyper- or hypoglycemia, performance metrics were calculated, which included AUC, net reclassification improvement (NRI), and integrated discrimination improvement (IDI).ResultsAmong 780 participants, 12.4% (n = 97) died within 28 days after admission to the pediatric intensive care unit (PICU). Statistically significant differences were found between survivors and non-survivors in terms of four GV metrics (SD, GLI, MAG, and ACACP), in which MAG (AUC: 0.762, 95% CI: 0.705–0.819, p < 0.001) achieved the largest AUC and showed a strong independent association with ICU mortality. Subsequent addition of MAG to the multivariate Cox model for hyperglycemia resulted in further quantitative evolution of the model statistics (AUC = 0.651–0.681, p = 0.001; IDI: 0.017, p = 0.044; NRI: 0.224, p = 0.186). The impact of hyperglycemia (adjusted hazard ratio [aHR]: 1.419, 95% CI: 0.815–2.471, p = 0.216) on outcome was attenuated and no longer statistically relevant after adjustment for MAG (aHR: 2.455, 95% CI: 1.411–4.270, p = 0.001).ConclusionsGV is strongly associated with poor prognosis independent of mean glucose level, demonstrating more predictive power compared with hypoglycemia and hyperglycemia after adjusting for confounding factors. GV metrics that contain information, such as time and rate of change, are the focus of future research; thus, the MAG may be a good choice. The findings of this study emphasize the crucial role of GVs in children in the PICU. Clinicians should pay more attention to GV for clinical glucose management.

Glucose variability during the early course of acute pancreatitis predicts two‐year probability of new‐onset diabetes: A prospective longitudinal cohort study

BackgroundAcute pancreatitis (AP) is the largest contributor to diabetes of the exocrine pancreas. However, there is no accurate predictor at the time of hospitalisation for AP to identify individuals at high risk for new‐onset diabetes.ObjectiveTo investigate the accuracy of indices of glucose variability (GV) during the early course of AP in predicting the glycated haemoglobin (HbA1c) trajectories during follow‐up.MethodsThis was a prospective longitudinal cohort study of patients without diabetes at the time of hospitalisation for AP. Fasting blood glucose was regularly measured over the first 72 h of hospital admission. The study endpoint was the HbA1c trajectories ‐ high‐increasing, moderate‐stable, normal‐stable ‐ over two years of follow‐up. Multinomial logistic regression analyses were conducted to investigate the associations between several common GV indices and the HbA1c trajectories, adjusting for covariates (age, sex, and body mass index). A sensitivity analysis constrained to patients with non‐necrotising AP was conducted.ResultsA total of 120 consecutive patients were studied. All patients in the high‐increasing HbA1c trajectory group had new‐onset diabetes at 18 and 24 months of follow‐up. Glycaemic lability index had the strongest significant direct association (adjusted odds ratio = 13.69; p = 0.040) with the high‐increasing HbA1c trajectory. High admission blood glucose, standard deviation of blood glucose, and average real variability significantly increased the patients' odds of taking the high‐increasing HbA1c trajectory by at least two‐times. Admission blood glucose, but not the other GV indices, had a significant direct association (adjusted odds ratio = 1.46; p = 0.034) with the moderate‐stable HbA1c trajectory. The above findings did not change materially in patients with non‐necrotising AP alone.ConclusionsHigh GV during the early course of AP gives a prescient warning of worsening HbA1c pattern and new‐onset diabetes after hospital discharge. Determining GV during hospitalisation could be a relatively straightforward approach to early identification of individuals at high risk for new‐onset diabetes after AP.

306.1: Clinical Metrics Predict Defective Physiologic Responses to Hypoglycemia in Long-standing Type 1 Diabetes and May Facilitate Early Consideration of Referral for Beta-Cell Replacement Therapy

Repeated hypoglycemia exposure leads to impaired awareness of hypoglycemia (IAH) and the development of defective counterregulatory responses. To date, only islet transplantation has demonstrated normalization of endogenous glucose production (EGP) during insulin-induced hypoglycemia, in addition to improving hypoglycemia awareness. This study aims to validate clinical metrics of IAH (Clarke score), hypoglycemia severity (HYPO score), glycemic lability (lability index, LI), and CGM measures of hypoglycemia exposure and glucose variability as predictors of defective glucose counterregulation, defined by absent EGP, and hypoglycemia unawareness, defined by absent autonomic symptom (AS) recognition, measured in response to insulin-induced hypoglycemia. 42 subjects with mean±SD age 43±13 years and T1D duration 29±12 years including 32 with IAH (Clarke unaware;19 pre-islet [Cohort 0], 13 pre-CGM [Cohort 1]) and 10 with intact hypoglycemia awareness (aware), and 12 non-diabetic control subjects, matched for age, sex and BMI (Cohort 3) underwent single-blinded randomized-paired hyperinsulinemic euglycemic and hypoglycemic clamp experiments using a stable glucose isotope tracer at the University of Pennsylvania between 2008–2021. Glycemic thresholds for EGP and AS responses were determined by the plasma glucose at which the response >95%CI of the euglycemic clamp control experiment. ROC and sensitivity analyses were performed to assess metric prediction of defective counterregulation. HYPO and LI were greater in Clarke unaware (Cohorts 0 and 1) vs aware cohort (Cohort 3; p<0.0001 and p=0.03, respectively). During hypoglycemic clamp experiments, final step EGP response was greatest in controls (1.4±0.4 mg/kg/min) and greater in aware (0.9±0.4 mg/kg/min) than unaware cohorts (0.5±0.4 mg/kg/min, p<0.01) which remained greater than in euglycemia (0.2±0.6 mg/kg/min, p=0.004). AS responses were comparable in aware and control groups (7.9±2.9 vs 8.0±6.7) however significantly less in the unaware group (2.4±3.0, p<0.001) which were no different than during euglycemia (1.0±2.2). Dichotomized Clarke score (</≥4) and Composite HYPO score/LI (</≥75th%) demonstrated good predictive value for determining glycemic threshold for EGP (Clarke: AUC=0.73, p=0.03; HYPO/LI: AUC=0.71, p=0.03) and AS (Clarke: AUC=0.71, p=0.04; HYPO/LI: AUC=0.71, p=0.03) responses. CGM time spent in hypoglycemia showed good ability to predict AS by 240 minutes but not EGP response. Parallel assessment of Clarke and hypoglycemia metrics increased the sensitivity and specificity to predict absent AS response at 240 minutes. Defective EGP response at 240 minutes was best predicted by a composite of Clarke and variability / lability metrics however at a lower specificity. These data suggest presence of IAH together with hypoglycemia exposure or increased glucose variability may identify individuals with defective counterregulation appropriate for early consideration of beta-cell replacement therapy. The project is supported by Public Health Services research grants R01 DK091331 (to M.R.R.), U01 DK070430 (University of Pennsylvania Center for Clinical Islet Transplantation), UL1 TR001878 (University of Pennsylvania Center for Human Phenomic Science), P30 DK19525 (University of Pennsylvania Diabetes Research Center), T32 DK00734 (University of Pennsylvania Training Grant in Diabetes, Endocrinology and Metabolic Diseases), and the Charles B. Humpton, Jr. Endowed Fellowship in Diabetes Research (to A.F.). The authors thank Dr. John Millar of the University of Pennsylvania Institute for Diabetes, Obesity and Metabolism Metabolic Tracer Resource for performance of the gas chromatography-mass spectrometry analysis of the 6,6-2H2-glucose tracer.

Update on islet cell transplantation.

Chronic diabetes-related complications continue to exert a rapidly growing and unsustainable pressure on healthcare systems worldwide. In type 1 diabetes, glycemic control is particularly challenging, as intensive management substantially increase the risk of severe hypoglycemic episodes. Alternative approaches to address this issue are required. Islet cell transplantation offers the best approach to reduce hypoglycemic risks and glycemic lability, while providing optimal glycemic control. Although ongoing efforts have improved clinical outcomes, the constraints in tissue sources and the need for chronic immunosuppression limit the application of islet cell transplantation as a curative therapy for diabetes. This review provides an update on islet cell transplantation, focusing on recent clinical experience, ongoing research, and future challenges. Current evidence demonstrates advances in terms of long-term glycemic control, improved insulin independence rates, and novel approaches to eliminate chronic immunosuppression requirements after islet cell transplantation. Advances in stem cell-based therapies provide a promising path towards truly personalized regenerative therapies, solving both tissue supply shortage and the need for lifelong immunosuppression, enabling widespread use of this potentially curative treatment. However, as these therapies enter the clinical realm, regional access variability and ethical questions regarding commercialization are becoming increasingly important and require a collaborative solution. In this state-of-the-art review, we discuss current clinical evidence and discuss key aspects on the present and future of islet cell transplantation.