Glucose variability; does it matter?

Poor Glycemic Control Is Associated With More Rapid Kidney Function Decline After the Onset of Diabetic Kidney Disease

BACKGROUND

The role of glycemic control and its variability on the rate of kidney function decline after the onset of diabetic kidney disease (DKD) remains unclear.

METHODS

The association between baseline glycated hemoglobin (HbA1c) and rates of estimated glomerular filtration rate (eGFR) loss during follow-up was examined by mixed-effects linear regression in 530 individuals with type 1 diabetes and early-to-moderate DKD from the Preventing Early Renal Loss (PERL) trial and 2378 individuals with type 2 diabetes and established DKD from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The benefit of intensive vs standard glycemic control in slowing eGFR decline was examined in ACCORD. The associations between continuous glucose monitoring-derived short-term glycemic variability indices and rate of eGFR decline were also evaluated in PERL.

RESULTS

A higher baseline HbA1c was associated with a more negative eGFR slope in both PERL and ACCORD (-0.87 and -0.27 mL/min/1.73 m2/year per Hba1c unit increment, P < .0001 and P = .0002, respectively). In both studies, the strength of this association progressively increased with increasing levels of albuminuria (P for interaction <.05). Consistent with this, the benefit of intensive glycemic control on eGFR decline was greater in ACCORD participants with severe rather than moderate albuminuria (+1.13 vs + 0.26 mL/min/1.73 m2/year, P = .01). No independent associations were found in PERL between short-term glycemic variability indices and rate of eGFR decline.

CONCLUSION

In both type 1 and type 2 diabetes, poor glycemic control is associated with a more rapid rate of glomerular filtration rate decline after DKD onset, especially in persons with severe albuminuria.

Comparison of efficacy and safety of insulin degludec/liraglutide and insulin glargine U-100/lixisenatide in individuals with type 2 diabetes mellitus using professional continuous glucose monitoring

AIM/INTRODUCTION

Insulin glargine U100/lixisenatide and insulin degludec/liraglutide are fixed-ratio combinations containing basal insulin and a glucagon-like peptide-1 receptor agonist capable of reducing both fasting and postprandial blood glucose levels with a single formulation. This study aimed to compare the time in range (TIR) and the time below range (TBR) level 1 using professional continuous glucose monitoring and to establish criteria for the differential use of the fixed-ratio combinations.

MATERIALS AND METHODS

Thirty-six outpatients with type 2 diabetes mellitus (24 men and 12 women; average age, 62.1 years) were randomly assigned to the groups. At 0 and 18 weeks, a device was worn to compare the TIR and TBR level 1. The correlation between the C-peptide index at baseline and TIR at 18 weeks was assessed.

RESULTS

The TIR and TBR level 1 showed no significant differences between the two groups. Both groups showed significant positive correlations between the C-peptide index and the TIR (P = 0.002, r = 0.679; P = 0.002, r = 0.681, respectively). The changes in glycemic variability, therapeutic indices, and body mass index were not significantly different among the groups (P > 0.05). The receiver operating curve analysis revealed that the cut-off values of the C-peptide index to achieve TIR of >70% at 18 weeks were 1.258 (sensitivity, 77.8%; specificity, 100%) and 1.099 (sensitivity, 57.1%; specificity, 90.9%) in the insulin glargine U100/lixisenatide and insulin degludec/liraglutide groups, respectively.

CONCLUSIONS

A TIR of >70% was achieved for both fixed-ratio combinations without significant differences.

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

OBJECTIVES

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.

DATA SOURCES

We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023.

STUDY SELECTION

We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU.

DATA EXTRACTION

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.

DATA SYNTHESIS

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).

CONCLUSIONS

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.

Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus

BACKGRUOUND

There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM).

METHODS

This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics.

RESULTS

Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without.

CONCLUSION

We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV.

Telemonitoring With a Connected Glucose Meter Improves Glycemia Among People With Insulin-Treated Type 2 Diabetes

BACKGROUND

Delayed initiation and inadequate titration remain critical challenges to optimizing insulin therapy in type 2 diabetes (T2D). We aimed to study whether hemoglobin A1c (HbA1c) can be lowered in people with insulin-treated T2D using telemonitoring.

METHODS

This single-center study recruited adults with greater than or equal to six months of diabetes, greater than or equal to three months of insulin therapy, HbA1c ≥8.5% and ≤12.5%, and body mass index (BMI) ≤40 kg/m2. All participants received a connected glucose meter and the accompanying smartphone application. Participants sent weekly blood glucose (BG) diary to their primary endocrinologist via email. Adjustments in insulin doses were communicated to the participants. HbA1c, proportion of BG readings in range (70-180 mg/dL, PIR), below range (<70 mg/dL, PBR) and above range (>180 mg/dL, PAR), and glycemic variability as the coefficient of variation (% CV) were measured at baseline, week 12, and week 24 and compared using repeated-measures analysis of variance (ANOVA) or Friedman's ANOVA.

RESULTS

We recruited 40 people (55% women). Mean age was 57.9 years, BMI 27.8 kg/m2, and baseline HbA1c 9.8% (83.7 mmol/mol). Mean HbA1c improved by 1.7%, % CV reduced from 32.9% to 30.7%, PIR increased from 58.8% to 67.1% (all P <.01) by week 24, without any change in PBR. This was achieved with a 0.04 U/kg/d median increase in total daily dose of insulin and 0.9 kg weight gain over 24 weeks.

CONCLUSION

Telemonitoring and titration of insulin using a connected glucose meter resulted in significant improvements in glycemia, characterized by a reduction in HbA1c, increase in PIR, and reduction in glycemic variability without any increase in hypoglycemia.

Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study

BACKGROUND

Continuous glucose monitoring (CGM) for diabetes combines noninvasive glucose biosensors, continuous monitoring, cloud computing, and analytics to connect and simulate a hospital setting in a person's home. CGM systems inspired analytics methods to measure glycemic variability (GV), but existing GV analytics methods disregard glucose trends and patterns; hence, they fail to capture entire temporal patterns and do not provide granular insights about glucose fluctuations.

OBJECTIVE

This study aimed to propose a machine learning-based framework for blood glucose fluctuation pattern recognition, which enables a more comprehensive representation of GV profiles that could present detailed fluctuation information, be easily understood by clinicians, and provide insights about patient groups based on time in blood fluctuation patterns.

METHODS

Overall, 1.5 million measurements from 126 patients in the United Kingdom with type 1 diabetes mellitus (T1DM) were collected, and prevalent blood fluctuation patterns were extracted using dynamic time warping. The patterns were further validated in 225 patients in the United States with T1DM. Hierarchical clustering was then applied on time in patterns to form 4 clusters of patients. Patient groups were compared using statistical analysis.

RESULTS

In total, 6 patterns depicting distinctive glucose levels and trends were identified and validated, based on which 4 GV profiles of patients with T1DM were found. They were significantly different in terms of glycemic statuses such as diabetes duration (P=.04), glycated hemoglobin level (P<.001), and time in range (P<.001) and thus had different management needs.

CONCLUSIONS

The proposed method can analytically extract existing blood fluctuation patterns from CGM data. Thus, time in patterns can capture a rich view of patients' GV profile. Its conceptual resemblance with time in range, along with rich blood fluctuation details, makes it more scalable, accessible, and informative to clinicians.

Cardiovascular autonomic neuropathy is associated with increased glycemic variability driven by hyperglycemia rather than hypoglycemia in patients with diabetes

AIM

Cardiac autonomic neuropathy (CAN) has been suggested to be associated with hypoglycemia and impaired hypoglycemia unawareness. We have assessed the relationship between CAN and extensive measures of glucose variability (GV) in patients with type 1 and type 2 diabetes.

METHODS

Participants with diabetes underwent continuous glucose monitoring (CGM) to obtain measures of GV and the extent of hyperglycemia and hypoglycemia and cardiovascular autonomic reflex testing.

RESULTS

Of the 40 participants (20 T1DM and 20 T2DM) (aged 40.70±13.73 years, diabetes duration 14.43±7.35 years, HbA1c 8.85±1.70%), 23 (57.5%) had CAN. Despite a lower coefficient of variation (CV) (31.26±11.87 vs. 40.33±11.03, P=0.018), they had a higher CONGA (8.42±2.58 vs. 6.68±1.88, P=0.024) with a lower median LBGI (1.60 (range: 0.20-3.50) vs. 4.90 (range: 3.20-7.40), P=0.010) and percentage median time spent in hypoglycemia (4 (range:4-13) vs. 1 (range:0-5), P=0.008), compared to those without CAN. The percentage GRADE_Euglycemia (3.30±2.78 vs. 5.69±3.09, P=0.017) and GRADE_Hypoglycemia (0.3 (range: 0 - 3.80) vs. 1.8 (range: 0.9-6.5), P=0.036) were significantly lower, while the percentage median GRADE_{Hyperglycemia} (95.45 (range:93-98) vs. 91.6 (82.8-95.1), P=0.013) was significantly higher in participants with CAN compared to those without CAN.

CONCLUSION

CAN was associated with increased glycemic variability with less time in euglycemia attributed to a greater time in hyperglycemia but not hypoglycemia.

A nomogram for accurately predicting the surgical site infection following transforaminal lumbar interbody fusion in type 2 diabetes patients, based on glycemic variability

Surgical site infection (SSI) is a common and serious complication of transforaminal lumbar interbody fusion (TLIF), and the occurrence of SSI usually leads to prolonged hospitalisation, increased medical costs, poor prognosis, and even death. The objectives of this study were to compare the incidence of SSI in patients with type 2 diabetes, investigate the correlation between perioperative glycemic variability and postoperative SSI, and develop a nomogram model to predict the risk of SSI. This study retrospectively analysed 339 patients with type 2 diabetes who underwent TLIF in the spinal surgery department of the Affiliated Zhongda Hospital of Southeast University from January 2018 to September 2021. The medical records of all patients were collected, and postoperative infection cases were determined according to the diagnostic criteria of surgical site infection. The risk factors for postoperative SSI were analysed by univariate and multivariate logistic regression. And Nomogram prediction model was established and validated. The nomogram incorporated seven independent predictors. Preoperative FPG-CV was the most important independent risk predictor of SSI, followed by preoperative MFBG, duration of drain placement, postoperative FPG-CV, preoperative blood glucose control scheme, duration of diabetes >5 years, and the number of fused vertebrae ≥2. The nomogram showed good diagnostic accuracy for the SS of both the training cohort and the validation cohort (AUC = 0.915 and AUC = 0.890). The calibration curves for the two cohorts both showed optimal agreement between nomogram prediction and actual observation. In conclusion, preoperative and postoperative glycemic variability is closely related to the occurrence of SSI. We developed and validated a nomogram to accurately predict the risk of SSI after TLIF surgery. It's helpful for spinal surgeons to formulate reasonable treatment plans and prevention strategies for type 2 diabetes patients.

Beyond hyperglycemia: glycaemic variability as a prognostic factor after acute ischemic stroke

INTRODUCTION

Glycaemic variability (GV) refers to variations in blood glucose levels, and may affect stroke outcomes. This study aims to assess the effect of GV on acute ischaemic stroke progression.

METHODS

We performed an exploratory analysis of the multicentre, prospective, observational GLIAS-II study. Capillary glucose levels were measured every 4 hours during the first 48 hours after stroke, and GV was defined as the standard deviation of the mean glucose values. The primary outcomes were mortality and death or dependency at 3 months. Secondary outcomes were in-hospital complications, stroke recurrence, and the impact of the route of insulin administration on GV.

RESULTS

A total of 213 patients were included. Higher GV values were observed in patients who died (n = 16; 7.8%; 30.9 mg/dL vs 23.3 mg/dL; p = 0.05). In a logistic regression analysis adjusted for age and comorbidity, both GV (OR = 1.03; 95% CI, 1.003-1.06; p = 0.03) and stroke severity (OR = 1.12; 95% CI, 1.04-1.2; p = 0.004) were independently associated with mortality at 3 months. No association was found between GV and the other outcomes. Patients receiving subcutaneous insulin showed higher GV than those treated with intravenous insulin (38.95 mg/dL vs 21.34 mg/dL; p < 0.001).

CONCLUSIONS

High GV values during the first 48 hours after ischaemic stroke were independently associated with mortality. Subcutaneous insulin may be associated with higher VG levels than intravenous administration.

Real-time Assessment of the Bidirectional Relationship Between Affective States and Glucose: Protocol for a 14-Day Observational Study

BACKGROUND

Glucose variability increases cardiometabolic disease risk. While many factors can influence glucose levels, postprandial glucose response is the primary driver of glucose variability. Furthermore, affect may directly and indirectly impact glucose variability through its effect on eating behavior. Continuous glucose monitors (CGMs) facilitate the real-time evaluation of blood glucose, and ecological momentary assessment (EMA) can be used to assess affect in real time. Together, data collected from these sources provide the opportunity to further understand the role of affect in glucose levels.

OBJECTIVE

This paper presents the protocol for a study that aims to (1) evaluate the feasibility and acceptability of using CGMs along with EMA in nondiabetic populations and (2) examine the bidirectional relationship between affect and glucose in nondiabetic adults with overweight or obesity using a CGM and EMA.

METHODS

Eligibility criteria for the study include participants (1) aged 18 to 65 years old, (2) with a BMI of ≥25 kg/m², (3) who are able to read and write in English, and (4) who own a smartphone. Individuals will be excluded if they (1) have type 1 or 2 diabetes or have any other condition that requires glucose monitoring, (2) are pregnant, (3) use any medications that have the potential to alter blood glucose levels or interfere with the glucose sensing process, or (4) have a diagnosed gastrointestinal condition or eating disorder. In a 14-day observational study, participants will wear a FreeStyle Libre Pro CGM sensor (Abbott) and will receive mobile phone-based EMA prompts 6 times per day (randomly within six 2-hour windows between 8 AM and 8 PM) to assess positive and negative affect. Participants will also wear a Fitbit Inspire 2 (Fitbit) to continuously monitor physical activity and sleep, which will be included as covariates in the analysis. Multilevel linear regression models will be used to evaluate the acute relationship between glucose level and affect.

RESULTS

Recruitment started in October 2022 and is expected to be completed in March 2023. We will aim to recruit 100 participants. As of December 12, 2022, a total of 39 participants have been enrolled.

CONCLUSIONS

The results of this study will further elucidate the role of affect in glucose variability. By identifying affective states that may lead to glucose excursions, our findings could inform just-in-time behavioral interventions by indicating opportunities for intervention delivery.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45104.

The efficacy and safety of combined GLP-1RA and basal insulin therapy among inadequately controlled T2D with premixed insulin therapy

This study investigated the effect of a combination of glucagon-like peptide-1 receptor agonist (GLP-1 RA) and basal insulin (BI) in poorly controlled type 2 diabetes mellitus previously treated with premixed insulin. The possible therapeutic benefit of the subject is mainly hoped to provide a direction for optimizing treatment options to reduce the risk of hypoglycemia and weight gain. A single-arm, open-label study was conducted. The antidiabetic regimen was switched to GLP-1 RA plus BI to replace previous treatment with premixed insulin in type 2 diabetes mellitus subjects. After 3 months of treatment modification, GLP-1 RA plus BI was compared for superior outcomes by continuous glucose monitoring system. There were 34 subjects at the beginning, 4 withdrew due to gastrointestinal discomfort, and finally 30 subjects completed the trial, of which 43% were male; the average age was 58 ± 9 years old, and the average duration of diabetes was 12 ± 6 years, the baseline glycated hemoglobin level was 8.6 ± 0.9 %. The initial insulin dose of premixed insulin was 61 ± 18 units, and the final insulin dose of GLP-1 RA + BI was 32 ± 12 units (P < .001). Time out of range (from 59%-42%), time-in-range (from 39%-56%) as well as glucose variability index including standard deviation also improved, mean magnitude of glycemic excursions, mean daily difference and continuous population in continuous glucose monitoring system, continuous overall net glycemic action (CONGA). Also noted was a decrease in body weight (from 70.9 kg-68.6 kg) and body mass index (all P values < .05). It provided important information for physicians to decide to modify therapeutic strategy as individualized needs.

Objective sleep characteristics and continuous glucose monitoring profiles of type 2 diabetes patients in real-life settings

AIM

To investigate the association between objective sleep parameters and glycaemic variability determined by continous glucose monitoring (CGM) among patients with type 2 diabetes, given the significant role of sleep in glycaemic control.

METHODS

In this study, CGM was carried out in 28 patients with T2D (aged 62.3 ± 4.8 years, 57% women). Sleep characteristics were assessed by actigraphy within the CGM period. CGM-derived outcomes included glucose level, and percentages of time in range (TIR) and time above range (TAR) during the monitoring period. Associations between intraindividual night-to-night variations in sleep characteristics and overall CGM outcomes were analysed using linear regression. Associations between sleep characteristics during each night and time-matched CGM outcomes were analysed using linear mixed models.

RESULTS

A total of 249 person-days of CGM, coupled with 221 nights of sleep characteristics, were documented. Greater standard deviation (SD) of objective sleep duration (minutes) between measurement nights was associated with higher glucose level (coefficient 0.018 mmol/L [95% confidence interval {CI} 0.004, 0.033], P = 0.017), smaller proportion of TIR (% in observation period; coefficient -0.20% [95% CI -0.36, -0.03], P = 0.023), and greater proportion of TAR (coefficient 0.22% [95% CI 0.06, 0.39], P = 0.011). Later sleep midpoint (minutes from midnight) was associated with greater SD of glucose during the same sleep period (coefficient 0.002 minutes [95% CI 0.0001, 0.003], P = 0.037), longer nocturnal sleep duration was associated with smaller coefficient of variation of glucose level in the upcoming day (-0.015% [95% CI -0.03, -0.001], P = 0.041).

CONCLUSION

Objectively determined sleep duration and sleep midpoint, as well as their daily variability, are associated with CGM-derived glucose profiles in T2D patients.

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.

Associations between oral processing, saliva, and bolus properties on daily glucose excursions amongst people at risk of type-2 diabetes

Background: A greater time spent with glucose above the normal range (TAR) has been associated with poorer glycaemic control amongst pre-diabetic individuals. Individual differences in oral processing behaviours and saliva amylase activity have been shown to influence glucose responses. Objective: The current study is a preliminary exploration of the associations of oral processing behaviours, bolus characteristics, and salivary amylase activity with the variability in daily glucose excursions within a free-living setting in populations with an elevated risk of type-2 diabetes. Method: Participant oral processing behaviour was derived from video recordings while they consumed a test meal. Post-meal bolus characteristics and saliva properties were measured. Participants were fitted with a continuous glucose monitor (CGM) which monitored blood glucose fluctuation over 7 consecutive free-living days. Dietary intake was recorded through a smartphone application and physical activity was monitored using a wrist worn accelerometer. Results: Participants varied in daily time spent with glucose above the normal range (>7.8 mmol l^-1) from 0% to 15%. Greater saliva uptake in the bolus was associated with a higher time spent above the normal range for glucose (β = 0.067 [95% CI = 0.015, 0.120]; p < 0.05), which remained significant after adjustment for dietary carbohydrate intake and BMI. Salivary amylase and saliva flow rate were not significantly associated with the time spent above the normal range. Conclusion: In addition to conventional dietary factors, more research is needed to understand how eating behaviours such as oro-sensory exposure, bolus surface area, and saliva uptake contribute to daily variations in postprandial glucose excursions among populations with a higher risk of developing type-2 diabetes.

Glycemic profile variability: An independent risk factor for diabetic neuropathy in patients with type 2 diabetes

BACKGROUND

Impaired glycemic control is a potential predictor for macro- and microvascular complications of diabetes, which could be recognized by glycemic variability. The aim of this 10-year prospective cohort study presented here is to gain a better understanding of the correlation between GV and diabetic peripheral neuropathy (DPN) as one of the most common complications of T2DM.

METHODS

Since February 2010, 1152 adult patients with T2DM have been followed-up. Baseline features, anthropometric measurements, and laboratory findings were collected and documented during ten years. The association between DPN incidence and glycemic profile variability was evaluated using cox regression analysis. The coefficient of variation of glycemic indices within subjects was calculated and compared using an independent sample t-test.

RESULTS

Individuals who developed neuropathy had significantly higher mean levels of glycemic indices (HbA1c, FBS, and 2hpp), urinary albumin excretion, mean creatinine levels, and a longer duration of diabetes. A significant positive correlation between incidence of DPN and glycemic profile variability (cv-FBS10 %, cv-FBS20 %, cv-2hpp20 %, cv-HbA1c5 % and cv-HbA1c10 %) was revealed. Results also showed that higher variability of FBS was associated with the higher risk of neuropathy incidence (HR: 12.29, p-value: 0.045), which indicates that glycemic profile variability is an independent risk factor for DPN in patients with T2DM.

CONCLUSION

Variability of glycemic profiles from a visit to visit, regardless of sustained hyperglycemia, was indeed a significant risk factor for DPN in diabetic type 2 patients. CV-FBS was the most critical glycemic variability indices for DPN development.

Significant increase of serum extracellular vesicle-packaged growth differentiation factor 15 in type 2 diabetes mellitus: a cross-sectional study

BACKGROUND

Growth differentiation factor 15 (GDF15) is a stress-inducible factor involved in the inflammatory progression of many complications, including type 2 diabetes mellitus (T2DM). Growing evidence suggests that molecules in extracellular vesicles (EVs) are associated with diabetes or diabetes-related complications. However, the correlation between serum extracellular vesicle-derived growth differentiation factor15 (EV-GDF15) and T2DM is unknown. The aim of this cross-sectional study is to investigate whether serum EV-GDF15 is associated with T2DM incidence.

METHODS

116 individuals, including 78 T2DM and 38 non-T2DM, were recruited as participants. The concentrations of serum EV-GDF15 and serum GDF15 were determined by Luminex assay. Serum EVs were obtained by ultracentrifugation. Multivariate stepwise regression analysis was used to determine the association between serum GDF15 levels and fasting plasma glucose (FPG) as well as glycated hemoglobin (HbA1c). The association of serum EV-GDF15 levels with T2DM was determined by multivariate logistic regression analysis.

RESULTS

Our data showed that the levels of serum EV-GDF15 and serum GDF15 were significantly increased in T2DM patients compared with non-T2DM subjects (EV-GDF15 levels, 13.68 (6.61-23.44) pg/mL vs. 5.56 (3.44-12.09) pg/mL, P < 0.001; and serum GDF15 levels, 1025.49 (677.87-1626.36) pg/mL vs. 675.46 (469.53-919.98) pg/mL, P < 0.001). There was a linear correlation between EV-GDF15 levels and fasting plasma glucose (FPG) and Hemoglobin A1C (HbA1c) levels (normalized β = 0.357, P < 0.001; normalized β = 0.409, P < 0.001, respectively). Elevated levels of EV-GDF15 were accompanied by an increase in the proportion of patients with T2DM (from 47.5 to 78.9%) and a progressive independent association with the incidence of T2DM (from OR = 3.06, 95% CI 1.02-9.19, P = 0.047 to OR = 3.75, 95% CI 1.14-12.26, P = 0.029). Notably, high levels of serum GDF15 plus high levels of serum EV-GDF15 were significantly associated with T2DM more than either alone.

CONCLUSION

This study elucidated that increased levels of GDF15 in serum EVs were independently associated with T2DM.

Delayed Eating Schedule Raises Mean Glucose Levels in Young Adult Males: a Randomized Controlled Cross-Over Trial

BACKGROUND

Misalignment of meals to the biological clock may cause adverse effects on glucose metabolism. However, the effects of repeated different eating schedules (early compared with late) on glucose concentration throughout the day are poorly understood.

OBJECTIVES

We examined the effects of different eating schedules on the 24-h glucose response using a continuous glucose monitor (CGM).

METHODS

Eight young adult males (age, 20.9 ± 3.4 y; body mass index: 21.3 ± 1.8 kg/m²) each followed 2 different eating schedules (early [08:30, 13:30, and 19:30] and late [12:00, 17:00, and 23:00]) in random order. These diet interventions were conducted for 8 d, with an experimental period of 3 d and 2 nights (from dinner on day 7) after 7 d of free living. The 3 meals in each intervention were nutritionally equivalent (55% carbohydrate, 15% protein, and 30% fat). The 24-h mean interstitial glucose concentration on day 8 was obtained under controlled conditions using the CGM (primary outcome). These concentrations were compared among the following 3 schedules using Dunnett's test, with the early eating schedule as reference (1 compared with 2 and 1 compared with 3): 1) early eating schedule (control), 2) late eating schedule according to the clock time (08:00 on day 8 to 08:00 on day 9), and 3) late eating schedule according to the time elapsed since the first meal for 24 h.

RESULTS

The 24-h mean ± SD interstitial glucose concentrations when participants followed the late eating schedule were higher than those when they followed the early eating schedule in terms of clock time (91.2 ± 2.9 compared with 99.2 ± 4.6 mg/dL, P = 0.003) and time elapsed (91.2 ± 2.9 compared with 98.3 ± 3.8 mg/dL, P < 0.001).

CONCLUSIONS

A late eating schedule increases the mean 24-h interstitial glucose concentration in young adult males. This insight will have useful implications in determining meal timings, especially for those with conditions such as diabetes.

The Effect of high temperature on the stability of basal insulin in a pen: a randomized controlled, crossover, equivalence trial

INTRODUCTION

Insulin is an essential medicine in the management of diabetes. When stored at high temperatures(HTs), its efficacy could rapidly decline. Therefore, appropriate storage of in-use insulin is necessary to achieve its maximum therapeutic effects. However, the ambient temperature in tropical countries is normally relatively high. This study aimed to compare the efficacies of basal insulin in a pen previously kept at 37°C for 21 days and basal insulin in a refrigerated pen (2°C-8°C). Continuous glucose monitoring (CGM) was used to evaluate daily mean glucose levels (MGLs).

RESEARCH DESIGN AND METHODS

This randomized controlled, crossover, equivalence trial recruited adults with type 2 diabetes mellitus and glycated hemoglobin levels <8% who had used insulin glargine for >3 months. Subjects were randomized for sequential use of refrigerated basal insulin followed by basal insulin kept at HT, with a 2-week washout between phases. The HT insulin pens were stored in a 37°C incubator for 21 days before use, while the refrigerated insulin pens were stored at 2°C-8°C. Study patients received 7-day CGM. The primary outcome was the difference in the groups' MGLs. The secondary outcome parameters were glucose variability represented by the standard deviation (SD), mean amplitude of glycemic excursion (MAGE), and percentage of time in range (TIR). The remaining quantity of insulin was evaluated by ultrahigh-performance liquid chromatography (UHPLC) assay.

RESULTS

Forty patients completed the study. The MGLwas 158.7±30.5 mg/dL and 157.0±40.9 mg/dL in the HT and refrigerated insulin pen groups, respectively (p=0.72). The groups had no significant differences in MAGE_7day, SD, percentage of TIR, carryover period, or treatment effects (all p>0.05). There was also no significant difference in the remaining quantity of insulin evaluated by UHPLC (p=0.97).

CONCLUSIONS

HT basal insulin pens retain their potency and have biological activity comparable to that of refrigerated pens.Trial registration number TCTR20210611002.

Glucose variability is a marker for COVID-19 severity and mortality

Objective

We aimed to investigate the association between glucose coefficient of variation (CV) and mortality and disease severity in hospitalized patients with coronavirus disease-19 (COVID-19).

Subjects and Methods

Retrospective cohort study in a tertiary center of patients with COVID-19 admitted to designated departments between March 11^th, 2020, and November 2^nd, 2020. We divided patients based on quartiles of glucose CV after stratification to those with and without diabetes mellitus (DM). Main outcomes were length of stay and in-hospital mortality.

Results

The cohort included 565 patients with a mean age of 67.71 ± 15.45 years, and 62.3% were male. Of the entire cohort, 44.4% had DM. The median glucose CV was 32.8% and 20.5% in patients with and without DM, respectively. In patients with DM, higher glucose CV was associated with a longer hospitalization in the unadjusted model (OR = 2.7, 95% CI [1.3,5.6] for Q4), and when adjusted for age, sex, comorbidities, and laboratory markers, this association was no longer statistically significant (OR = 1.3, 95% CI [0.4,4.5] for Q4). In patients with and without DM, higher glucose CV was associated with higher rates of in-hospital mortality in the unadjusted model, but adjustment for comorbidities and laboratory markers eliminated the association (OR = 0.5, 95% CI [0.1,3.4] for Q4 in patients with DM).

Conclusion

Higher glucose CV was associated with increased in-hospital mortality and length of stay, but this association disappeared when the adjustment included laboratory result data. Glucose CV can serve as a simple and cheap marker for mortality and severity of disease in patients with COVID-19.

Serum Glucose Variability Increases the Risk of Complications Following Aseptic Revision Hip and Knee Arthroplasty

BACKGROUND

Increased serum glucose variability has been proposed as a risk factor for perioperative morbidity and mortality. Given the greater surgical complexity and complication risk of revision total joint arthroplasty (TJA), previous findings may not be generalizable to the revision population. The purpose of this study was to investigate the association between glucose variability and postoperative complications following aseptic revision TJA.

METHODS

We identified 1,983 patients who underwent an aseptic revision TJA (636 total knee arthroplasties [TKAs] and 1,347 total hip arthroplasties [THAs]) from 2001 to 2019. Patients with ≥2 postoperative glucose values per day or ≥3 values during hospitalization were included in this study. Glucose variability was assessed using the coefficient of variation (COV). Outcomes included length of hospital stay, 90-day complications, mortality, and periprosthetic joint infection (PJI) as defined by the 2018 International Consensus Meeting criteria. Multivariate regression was used to determine the association between glucose variability and each end point, using COV as continuous and categorical variables (that is, COV tertiles).

RESULTS

Patients with high glycemic variability were at 1.7 times greater risk for 90-day complications (odds ratio [OR], 1.664 [95% confidence interval (CI), 1.266 to 2.188]; p < 0.001) and 2 times greater risk for PJI at a minimum 1-year follow-up (OR, 1.984 [95% CI, 1.270 to 3.100]; p = 0.003). The risk of 90-day complications increased by 2.2% (OR, 1.022 [95% CI, 1.012 to 1.032]; p < 0.001) and the risk of PJI increased by 1.8% (OR, 1.018 [95% CI, 1.003 to 1.034]; p = 0.013) for every percentage-point increase in COV. Patients with higher glucose variability also had a longer length of stay (beta, 1.028 days [95% CI, 0.590 to 1.466 days]; p < 0.001). These associations were independent of age, sex, body mass index, Charlson Comorbidity Index, involved joint, operative time, history of diabetes, and mean glucose levels.

CONCLUSIONS

Higher glucose variability was associated with an increased risk of medical complications and PJI following aseptic revision TJA. Patients undergoing these complex procedures should have glucose levels monitored closely in the perioperative period. Future studies should evaluate the utility of continuous glucose monitoring in this high-risk population.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Continuous glucose monitoring metrics for earlier identification of pre-diabetes: protocol for a systematic review and meta-analysis

INTRODUCTION

Glycaemic variability and other metrics are not well characterised in subjects without diabetes. More comprehensive sampling as obtained with continuous glucose monitoring (CGM) may improve diagnostic accuracy of the transition from health to pre-diabetes. Our goal is to investigate the glycaemic system as it shifts from health to pre-disease in adult patients without diabetes using CGM metrics. New insights may offer therapeutic promise for reversing dysglycaemia more successfully with dietary, nutritional and lifestyle change before progression occurs to pre-diabetes and diabetes.

METHODS AND ANALYSIS

This systematic review will include comprehensive searches of the PubMed, Scopus, Cochrane Library and ClinicalTrials.gov databases, with restrictions set to studies published in the last 10 years in English and planned search date 10 March 2022. Reference lists of studies that meet eligibility criteria in the screening process will subsequently be screened for the potential inclusion of additional studies. We will include studies that examine CGM use and report diagnostic criteria such as fasting glucose and/or haemoglobin A1c such that we can assess correlation between CGM metrics and established diagnostic criteria and describe how CGM metrics are altered in the transition from health to pre-diabetes. The screening and data extraction will be conducted by two independent reviewers using Covidence. All included papers will also be evaluated for quality and publication bias using Cochrane Collaboration risk of bias tools. If there are two or more studies with quantitative estimates that can be combined, we will conduct a meta-analysis after assessing heterogeneity.

ETHICS AND DISSEMINATION

The systematic review methodology does not require formal ethical review due to the nature of the study design. Study findings will be publicly available and published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42022308222.

Continuous glucose monitoring to assess glucose variability in type 3c diabetes

AIM

The effectiveness of continuous glucose monitoring (CGM) in maintaining glycaemic control in type 1 diabetes mellitus and type 2 diabetes mellitus has been well demonstrated. However, the degree of glycaemic variability (GV) in people with type 3c diabetes mellitus has not been fully explored using CGM. This study aims to evaluate GV in type 3c diabetes mellitus participants and compare it to type 1 diabetes mellitus and type 2 diabetes mellitus.

METHODS

Participants were grouped according to type of diabetes. GV, defined as percentage coefficient of variation (%CV), and other glycaemic indices were obtained using CGM (FreeStyle Libre, Abbott, Australia) from 82 participants across all three cohorts over a 14-day period. Comparison of baseline characteristics and GV were performed across all groups. Correlation of GV with C-peptide values, and whether pancreatic supplementation had an effect on GV were also assessed in the type 3c diabetes mellitus cohort.

RESULTS

GV of type 3c diabetes mellitus participants was within the recommended target of less than %CV 36% (p = 0.004). Type 3c diabetes mellitus participants had the lowest GV among the three groups (p = 0.001). There was a trend for lower C-peptide levels to be associated with higher GV in type 3c diabetes mellitus participants (p = 0.22). Pancreatic enzyme supplementation in type 3c diabetes mellitus participants did not have an effect on GV (p = 0.664).

CONCLUSIONS

Although type 3c diabetes mellitus participants were the least variable, they had the highest mean glucose levels and estimated HbA_1c , which suggests that the concept of 'brittle' diabetes in type 3c diabetes mellitus is not supported by the results of CGM in this study and may be leading to poorer glycaemic control.

Increased postoperative glycemic variability is associated with increased mortality in diabetic patients undergoing hip arthroplasty for hip fracture

BACKGROUND

Increased glycemic variability (GV) during hospitalization has been associated with increased rates of surgical site and periprosthetic joint infections (PJI) following elective total joint arthroplasty. Uncertainty exists surrounding GV as a predictor for complications in urgent arthroplasty cases following hip fractures. In this study, we evaluated the association between GV and postoperative complications in diabetic patients undergoing total hip arthroplasty (THA) and hemiarthroplasty (HA) for hip fractures.

METHODS

We analyzed data on 2421 consecutive patients who underwent THA or HA at our institution from 2011 to 2020. Patients with a known diagnosis of diabetes mellitus who had a minimum of three postoperative glucose values taken within the first week after surgery were included. GV was assessed using a coefficient of variation. Outcomes included short- and long-term mortality, reoperations, prosthetic joint infection (PJI) requiring revision and readmissions for any cause.

RESULTS

The final cohort consisted of 482 patients (294 females, 188 males). Higher GV was associated with an increased 90-day mortality (p = 0.017). GV was not associated with 30-day mortality (p = 0.45), readmissions of any cause at 30 or 90 days (p = 0.99, p = 0.91, respectively), reoperation of any cause (p = 0.91) or PJI requiring revision surgery (p = 0.42).

CONCLUSIONS

Higher GV in the postoperative period is associated with increased rates of mortality in diabetic patients following THA and HA for hip fractures. Efforts should be made to monitor and control glucose variability in the postoperative period.

Association between hypoglycaemic glucose variability and autonomic function in type1 diabetes with impaired hypoglycaemia awareness

Cardiovascular autonomic neuropathy (CAN) is suggested to underlie hypoglycaemic risk in impaired awareness of hypoglycaemia (IAH). We assessed the prevalence of CAN and the association between glucose variability (GV) and cardiovascular autonomic function in patients with type 1 diabetes (T1DM) and IAH. This study is a post-hoc-analysis of results obtained with the IN-CONTROL-trial, designed to assess the effects of continuous glucose monitoring (CGM) on glycaemia. Forty participants (aged 46.4 ± 11.4 years, diabetes duration 29.1 ± 13.5 years, HbA1c 7.5 ± 0.8%(58.2 ± 8.8 mmol/mol)) underwent 2-week blinded CGM measurements to obtain GV indices. Standardized cardiovascular reflex tests were used to determine the presence of CAN. Cardiovascular autonomic function was assessed with heart rate variability (HRV) measures. 14(35%) participants were classified as having CAN. Participants with CAN had lower percentage time spent in hypoglycaemic range and low blood glucose index(LBGI). After correction for confounders, a significant positive association was found between the coefficient of variation (CV) or time spent in hypoglycaemic range and HRV measures SDRR or RMSSD, and between LBGI and RMSSD. In patients with T1DM and IAH, hypoglycaemic parameters were associated with better cardiovascular autonomic function and lower prevalence of CAN. This suggests that autonomic neuropathy does not seem to further deteriorate hypoglycaemic risk in patients with IAH.

The Effect of High and Variable Glucose on the Viability of Endothelial Cells Co-Cultured with Smooth Muscle Cells

Diabetes mellitus causes endothelial dysfunction. The aim of this study was to investigate the effect of normal (5 mmol/L), high (20 mmol/L), and fluctuating (5 and 20 mmol/L changed every day) glucose concentration in the culture medium on the viability of human umbilical vein endothelial cells (HUVECs) co-cultured with human umbilical artery smooth muscle cells (HUASMCs). The cultures were conducted on semi-permeable flat polysulfone (PSU) fibronectin-coated membranes immobilized in self-made inserts. The insert contained either HUVECs on a single membrane or HUASMCs and HUVECs on two membranes close to each other. Cultures were conducted for 7 or 14 days. Apoptosis, mitochondrial potential, and the production of reactive oxygen species and lactate by HUVECs were investigated. The results indicate that fluctuations in glucose concentration have a stronger negative effect on HUVECs viability than constant high glucose concentration. High and fluctuating glucose concentrations slow down cell proliferation compared to the culture carried out in the medium with normal glucose concentration. In conclusion, HUASMCs affect the viability of HUVECs when both types of cells are co-cultured in medium with normal or variable glucose concentration.

Efficacy of IDegLira Versus IDegAsp Therapy in Patients with Type 2 Diabetes: A Randomized Crossover Study by isCGM

Introduction

We aimed to compare the efficacy of insulin degludec/insulin aspart (IDegAsp) and insulin degludec/liraglutide (IDegLira) in controlling glucose fluctuation and suppressing postprandial glucose levels using intermittently scanned continuous glucose monitoring.

Methods

Twenty-four patients with type 2 diabetes mellitus were randomly allocated to receive either IDegLira or IDegAsp followed by IDegAsp or IDegLira, respectively. A crossover study was conducted with intermittently scanned continuous glucose monitoring. We compared the postprandial blood glucose level, time in range, and time below range from a 3-day intermittently scanned continuous glucose monitoring period for each treatment group.

Results

The time in range was significantly higher in IDegLira than in IDegAsp. Postprandial glucose levels 90 and 120 min after breakfast and 60, 90, and 120 min after lunch were significantly lower for IDegLira than for IDegAsp. However, postprandial glucose levels 90 and 120 min after supper were significantly lower for IDegAsp than for IDegLira. There was no significant difference in the time below range between IDegLira and IDegAsp.

Conclusion

IDegLira was more effective in treating type 2 diabetes mellitus than IDegAsp, as indicated by a higher time in range and lower postprandial glucose level at breakfast and lunch. This study was registered with the University Hospital Medical Information Network Clinical Trial Registry (UMIN 000039221).

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-022-02138-w.

Comparison of Glycemic Variability and Hypoglycemic Events in Hospitalized Older Adults Treated with Basal Insulin plus Vildagliptin and Basal-Bolus Insulin Regimen: A Prospective Randomized Study

Background: The basal−bolus insulin regimen is recommended in hospitalized patients with diabetes mellitus (DM), but has an increased risk of hypoglycemia. We aimed to compare dipeptidyl peptidase 4 inhibitors (DPP4-i) and basal−bolus insulin glycemic outcomes in hospitalized type 2 DM patients. Methods and patients: Our prospective randomized study included 102 elderly T2DM patients (82 ± 9 years, HbA1c 6.6% ± 1.9). Glycemic control: A variability coefficient assessed by continuous glucose monitoring (Free Style® sensor), mean insulin dose and hypoglycemia rates obtained with the two treatments were analyzed. Results: No differences were found between groups in glycemic control (mean daily glycemia during the first 10 days: 152.6 ± 38.5 vs. 154.2 ± 26.3 mg/dL; p = 0.8). The total doses Kg/day were 0.40 vs. 0.20, respectively (p < 0.001). A lower number of hypoglycemic events (9% vs. 15%; p < 0.04) and lower glycemic coefficient of variation (22% vs. 28%; p < 0.0002) were observed in the basal−DPP4-i compared to the basal−bolus regimen group. Conclusions: Treatment of inpatient hyperglycemia with basal insulin plus DPP4-i is an effective and safe regimen in old subjects with T2DM, with a similar mean daily glucose concentration, but lower glycemic variability and fewer hypoglycemic episodes compared to the basal bolus insulin regimen.

Development and validation of a prediction model of perioperative hypoglycemia risk in patients with type 2 diabetes undergoing elective surgery

AIM

To develop and validate a prediction model to evaluate the perioperative hypoglycemia risk in hospitalized type 2 diabetes mellitus (T2DM) patients undergoing elective surgery.

METHODS

We retrospectively analyzed the electronic medical records of 1410 T2DM patients who had been hospitalized and undergone elective surgery. Regression analysis was used to develop a predictive model for perioperative hypoglycemia risk. The receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow test were used to verify the model.

RESULTS

Our study showed an incidence of 10.7% for level 1 hypoglycemia and 1.8% for level 2 severe hypoglycemia during the perioperative period. A perioperative hypoglycemic risk prediction model was developed that was mainly composed of four predictors: duration of diabetes ≥ 10 year, body mass index (BMI) < 18.5 kg/m², standard deviation of blood glucose (SDBG) ≥ 3.0 mmol/L, and preoperative hypoglycemic regimen of insulin subcutaneous. Based on this model, patients were categorized into three groups: low, medium, and high risk. Internal validation of the prediction model showed high discrimination (ROC statistic = 0.715) and good calibration (no significant differences between predicted and observed risk: Pearson χ² goodness-of-fit P = 0.765).

CONCLUSIONS

The perioperative hypoglycemic risk prediction model categorizes the risk of hypoglycemia using only four predictors and shows good reliability and validity. The model serves as a favorable tool for clinicians to predict hypoglycemic risk and guide future interventions to reduce hypoglycemia risk.

Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems

Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucose-related outcomes of such user-driven innovation. Initial OpenAPS studies include retrospective studies assessing high-level outcomes of average glucose levels and HbA1c, without in-depth analysis of glucose variability (GV). The OpenAPS Data Commons dataset, donated to by open-source AID users with insulin-requiring diabetes, is the largest freely available diabetes-related dataset with over 46,070 days’ worth of data and over 10 million CGM data points, alongside insulin dosing and algorithmic decision data. This paper first reviews the development toward the latest open-source AID and the performance of clinically approved GV metrics. We evaluate the GV outcomes using large-scale data analytics for the n = 122 version of the OpenAPS Data Commons. We describe the data cleaning processes, methods for measuring GV, and the results of data analysis based on individual self-reported demographics. Furthermore, we highlight the lessons learned from the GV outcomes and the analysis of a rich and complex diabetes dataset and additional research questions that emerged from this work to guide future research. This paper affirms previous studies’ findings of the efficacy of open-source AID.

Glucose variability is associated with an adverse vascular profile but only in the presence of insulin resistance in individuals with type 1 diabetes: An observational study

AIMS/HYPOTHESIS

We hypothesised that the detrimental effect of high glucose variability (GV) in people with type 1 diabetes is mainly evident in those with concomitant insulin resistance.

METHODS

We conducted secondary analyses on continuous glucose monitoring (CGM) using baseline observational data from three randomised controlled trials and assessed the relationship with established vascular markers. We used standard CGM summary statistics and principal component analysis to generate individual glucose variability signatures for each participant. Cluster analysis was then employed to establish three GV clusters (low, intermediate, or high GV, respectively). The relationship with thrombotic biomarkers was then investigated according to insulin resistance, assessed as estimated glucose disposal rate (eGDR).

RESULTS

Of 107 patients, 45%, 37%, and 18% of patients were assigned into low, intermediate, and high GV clusters, respectively. Thrombosis biomarkers (including fibrinogen, plasminogen activator inhibitor-1, tissue factor activity, and tumour necrosis factor-alpha) increased in a stepwise fashion across all three GV clusters; this increase in thrombosis markers was evident in the presence of low but not high eGDR and at a threshold of eGDR <5.1 mg/kg/min.

CONCLUSION

Higher GV is associated with increased thrombotic biomarkers in type 1 diabetes but only in those with concomitant insulin resistance.

Hypoglycemic agents and glycemic variability in individuals with type 2 diabetes: A systematic review and network meta-analysis

While hemoglobin A1c (HbA1c) is commonly used to monitor therapy response in type 2 diabetes (T2D), GV is emerging as an essential additional metric for optimizing glycemic control. Our goal was to learn more about the impact of hypoglycemic agents on HbA1c levels and GV in patients with T2D. A systematic review and network meta-analysis (NMA) of randomized controlled trials were performed to assess the effects of glucagon-like peptide 1 receptor agonists (GLP-1 RAs), sodium-glucose cotransporter (SGLT)-2 inhibitors, dipeptidyl peptidase (DPP)-4 inhibitors, sulfonylurea and thiazolidinediones on Mean Amplitude of Glycemic Excursions (MAGE) and HbA1c. Searches were performed using PubMed and EMBASE. A random-effect model was used in the NMA, and the surface under the cumulative ranking was used to rank comparisons. All studies were checked for quality according to their design and also for heterogeneity before inclusion in this NMA. The highest reduction in MAGE was achieved by GLP-1 RAs (SUCRA 0.83), followed by DPP-4 inhibitors (SUCRA: 0.72), and thiazolidinediones (SUCRA: 0.69). In terms of HbA1c reduction, GLP-1 RAs were the most effective (SUCRA 0.81), followed by DPP-4 inhibitors (SUCRA 0.72) and sulfonylurea (SUCRA 0.65). Our findings indicated that GLP-1 RAs have relatively high efficacy in terms of HbA1c and MAGE reduction when compared with other hypoglycemic agents and can thus have clinical application. Future studies with a larger sample size and appropriate subgroup analyses are warranted to completely understand the glycemic effects of these agents in various patients with T2D. The protocol for this systematic review was registered with the International Prospective Register of Systematic Reviews (CRD42021256363).

Glucose and unstructured physical activity coupling during sleep and wake in young adults with type 1 diabetes

Glucose variations have a bidirectional relationship with the sleep/wake and circadian systems in type 1 diabetes (T1D); however, the mechanisms remain unclear. The aim of this study was to describe the coupling between glucose and unstructured physical activity over 168 h in young adults with T1D. We hypothesized that there would be differences in sleep and wake characteristics and circadian variations. Glucose was measured with a continuous glucose monitoring device every 5 min and activity with a non-dominant wrist-worn actigraph in 30-s epochs over 6–14 days. There was substantial glucose and unstructured physical activity coupling during sleep and wake, along with circadian variation based on the wavelet coherence analysis. The extent to which glucose fluctuations result in disrupted sleep over longer than one week should be examined considering the harmful effects on achieving glycemic targets. Further studies are needed to delineate the respective roles of glucose production and utilization and the potential for improved meal and insulin timing to optimize glucose and sleep in this population reliant on exogenous insulin.

Postoperative Glycemic Variability as a Predictor of Adverse Outcomes Following Lumbar Fusion

STUDY DESIGN

A retrospective cross-sectional study.

OBJECTIVE

This study aims to evaluate the effect size of postoperative glycemic variability on surgical outcomes among patients who have undergone one- to three-level lumbar fusion.

SUMMARY OF BACKGROUND DATA

While numerous patient characteristics have been associated with surgical outcomes after lumbar fusion, recent studies have described the measuring of postoperative glycemic variability as another promising marker.

METHODS

A total of 850 patients were stratified into tertiles (low, moderate, high) based on degree of postoperative glycemic variability defined by coefficient of variation (CV). Surgical site infections were determined via chart review based on the Centers for Disease Control and Prevention definition. Demographic factors, surgical characteristics, inpatient complications, readmissions, and reoperations were determined by chart review and telephone encounters.

RESULTS

Overall, a statistically significant difference in 90-day adverse outcomes was observed when stratified by postoperative glycemic variability. In particular, patients with high CV had a higher odds ratio (OR) of readmission (OR = 2.19 [1.17, 4.09]; P = 0.01), experiencing a surgical site infection (OR = 3.22 [1.39, 7.45]; P = 0.01), and undergoing reoperations (OR = 2.65 [1.34, 5.23]; P = 0.01) compared with patients with low CV. No significant association was seen between low and moderate CV groups. Higher CV patients were more likely to experience longer hospital stays (β: 1.03; P = 0.01). Among the three groups, high CV group experienced the highest proportion of complications.

CONCLUSION

Our study establishes a significant relationship between postoperative glycemic variability and inpatient complications, length of stay, and 90-day adverse outcomes. While HbA1c has classically been used as the principal marker to assess blood glucose control, our results show CV to be a strong predictor of postoperative adverse outcomes. Future high-quality, prospective studies are necessary to explore the true effect of CV, as well as its practicality in clinical practice. Nevertheless, fluctuations in blood glucose levels during the inpatient stay should be limited to improve patient results.Level of Evidence: 4.

Glycaemia dynamics in gestational diabetes mellitus

Pregnant women may develop gestational diabetes mellitus (GDM), a disease of pregnancy characterised by maternal and fetal hyperglycaemia with hazardous consequences to the mother, the fetus, and the newborn. Maternal hyperglycaemia in GDM results in fetoplacental endothelial dysfunction. GDM-harmful effects result from chronic and short periods of hyperglycaemia. Thus, it is determinant to keep glycaemia within physiological ranges avoiding short but repetitive periods of hyper or hypoglycaemia. The variation of glycaemia over time is defined as 'glycaemia dynamics'. The latter concept regards with a variety of mechanisms and environmental conditions leading to blood glucose handling. In this review we summarized the different metrics for glycaemia dynamics derived from quantitative, plane distribution, amplitude, score values, variability estimation, and time series analysis. The potential application of the derived metrics from self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) in the potential alterations of pregnancy outcome in GDM are discussed.

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

Background

Acute 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.

Objective

To 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.

Methods

This 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.

Results

A 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.

Conclusions

High 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.

The impact of perioperative glucose variability on outcomes after hip fracture

Diabetes is considered an independent risk factor for hip fracture. In the present study, we evaluated whether perioperative glucose variability (GV) was a significant predictor of the outcomes of patients with diabetes after hip fracture.We analyzed the characteristics and outcomes of all patients with hip fractures admitted to our hospital between September 2008 and December 2012. Patients with diabetes were grouped into tertiles for GV, and multivariate survival analysis included age, sex, fracture type, mean fasting plasma glucose, and GV.Among the 1099 patients included in this study, 239 (21.7%) had diabetes. Patients with diabetes were more likely to develop infectious complications (5.4% vs 2.8%, P = .045), and experience mortality postoperatively (1 month: 5.5% vs 2.7%, P = .052; 12 months: 15.1% vs 8.7%, P = .006). The postoperative mortality rate was increased across the GV tertiles, and GV was an independent predictor of 1- and 12-month mortality after surgery.Patients with diabetes had poor prognoses after hip fracture. Perioperative GV is an independent predictor of mortality in patients with diabetes. Therefore, GV might be considered a valid additional parameter to consider in the management of these patients.

Largest Amplitude of Glycemic Excursion Calculating from Self-Monitoring Blood Glucose Predicted the Episodes of Nocturnal Asymptomatic Hypoglycemia Detecting by Continuous Glucose Monitoring in Outpatients with Type 2 Diabetes

AIMS

Nocturnal asymptomatic hypoglycemia (NAH) is a serious complication of diabetes, but it is difficult to be detected clinically. This study was conducted to determine the largest amplitude of glycemic excursion (LAGE) to predict the episodes of NAH in outpatients with type 2 diabetes.

METHODS

Data were obtained from 313 outpatients with type 2 diabetes. All subjects received continuous glucose monitoring (CGM) for consecutive 72 hours. The episodes of NAH and glycemic variability indices (glucose standard deviation [SD], mean amplitude of plasma glucose excursion [MAGE], mean blood glucose [MBG]) were accessed via CGM. LAGE was calculated from self-monitoring blood glucose (SMBG).

RESULTS

A total of 76 people (24.3%) had NAH. Compared to patients without NAH, patients with NAH showed higher levels of glucose SD (2.4 ± 0.9 mmol/L vs 1.7 ± 0.9 mmol/L, p <0.001), MAGE (5.2 ± 2.1 mmol/L vs 3.7 ± 2.0, p<0.001) and LAGE (4.6 ± 2.3 mmol/L vs 3.8 ± 1.9 mmol/L, p=0.007), and lower level of MBG (7.5 ± 1.5 mmol/L vs 8.4 ± 2.2 mmol/L, p=0.002). LAGE was significantly associated with the incidence of NAH and time below rang (TBR) in model 1 [NAH: 1.189 (1.027-1.378), p=0.021; TBR: 0.008 (0.002-0.014), p=0.013] with adjustment for age, BMI, sex, work, hyperlipidemia, complication and medication, and in model 2 [NAH: 1.177 (1.013-1.367), p=0.033; TBR: 0.008 (0.002-0.014), p=0.012] after adjusting for diabetes duration based on model 1, as well as in model 3 [NAH: 1.244 (1.057-1.464), p=0.009; TBR: 0.009 (0.002-0.016), p=0.007] with further adjustment for HbA1c based on model 2. In addition, no significant interactions were found between LAGE and sex, age, HbA1c, duration of diabetes, BMI and insulin therapy on the risk of NAH. The receiver operator characteristic (ROC) curve shows the ideal cutoff value of LAGE for the prediction of NAH was 3.48 mmol/L with 66.7% sensitivity, 50% specificity and 0.587 (95% CI: 0.509-0.665) of area under the ROC curve.

CONCLUSIONS

High glycemic variability is strongly associated with the risk of NAH. The LAGE based on SMBG could be an independent predictor of NAH for outpatients with type 2 diabetes, and LAGE greater than 3.48 mmol/L could act as a warning alarm for high risk of NAH in daily life.

Insulin Degludec Versus Insulin Glargine on Glycemic Variability in Diabetic Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND/AIMS

Currently, glycemic variability has more deleterious effects than sustained hyperglycemia and is closely associated with acute and chronic complications of diabetes. Reducing glycemic excursion is becoming another vital goal of glycemic control in clinical practice. This study aimed to determine whether insulin degludec (IDeg) or insulin glargine (IGla) was more beneficial for reducing glycemic fluctuations.

MATERIALS AND METHODS

This research was constructed according to the PRISMA guidelines. We searched eight databases and ClinicalTrials.gov from their inception to 30 November 2021. All randomized controlled trials comparing the efficacy of glucose variability between IDeg and IGla in diabetic patients were included.

RESULTS

Fourteen trials with 8,683 participants were included. In patients with T1DM, IDeg was associated with a lower mean (MD: -16.25, 95% CI -29.02 to -3.07, P = 0.01) and standard deviation (P = 0.03) compared to IGla in fasting blood glucose (FBG); in people with T2DM, IDeg was related to a lower mean of FBG versus insulin glargine 100 U/ml (IGla100) (P <0.001) and had a more extended time in the range (TIR) than IGla100 (SMD: 0.15, 95% CI 0.02 to 0.27, P = 0.02) but not longer than insulin glargine 300 U/ml (IGla300). Moreover, IDeg had a lower coefficient of variation of FBG than IGla (P = 0.0254). For other indicators of glycemic variability, namely, standard deviation of blood glucose for 24 h, the mean of 24-h blood glucose, mean amplitude of glycemic excursion, the coefficient of variation for 24 h, the mean of daily differences, area under the glucose curve, and M-value, no significant differences were identified between IDeg and IGla, regardless of T1DM or T2DM.

CONCLUSIONS

Based on the current studies, there was comparable efficacy between IDeg and IGla from multiple aspects of glycemic variability, regardless of T1DM or T2DM. However, IDeg may be superior to IGla in reducing FBG variability in T1DM and T2DM. Nonetheless, due to the limitations of the original studies, it is still unclear whether IDeg is superior to both IGla100 and IGla300. In T2DM, IDeg had more extended TIR than IGla100 but not longer than IGla300. Additionally, more well-designed randomized controlled trials comparing IDeg with IGla300 for different indicators of glycemic variability are still warranted.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, CRD42021283203.

A High Protein Diet Is More Effective in Improving Insulin Resistance and Glycemic Variability Compared to a Mediterranean Diet-A Cross-Over Controlled Inpatient Dietary Study

The optimal dietary pattern to improve metabolic function remains elusive. In a 21-day randomized controlled inpatient crossover feeding trial of 20 insulin-resistant obese women, we assessed the extent to which two isocaloric dietary interventions—Mediterranean (M) and high protein (HP)—improved metabolic parameters. Obese women were assigned to one of the following dietary sequences: M–HP or HP–M. Cardiometabolic parameters, body weight, glucose monitoring and gut microbiome composition were assessed. Sixteen women completed the study. Compared to the M diet, the HP diet was more effective in (i) reducing insulin resistance (insulin: Beta (95% CI) = −6.98 (−12.30, −1.65) µIU/mL, p = 0.01; HOMA-IR: −1.78 (95% CI: −3.03, −0.52), p = 9 × 10⁻³); and (ii) improving glycemic variability (−3.13 (−4.60, −1.67) mg/dL, p = 4 × 10⁻⁴), a risk factor for T2D development. We then identified a panel of 10 microbial genera predictive of the difference in glycemic variability between the two diets. These include the genera Coprococcus and Lachnoclostridium, previously associated with glucose homeostasis and insulin resistance. Our results suggest that morbidly obese women with insulin resistance can achieve better control of insulin resistance and glycemic variability on a high HP diet compared to an M diet.

Perspectives of glycemic variability in diabetic neuropathy: a comprehensive review

Diabetic neuropathy is one of the most prevalent chronic complications of diabetes, and up to half of diabetic patients will develop diabetic neuropathy during their disease course. Notably, emerging evidence suggests that glycemic variability is associated with the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for diabetic neuropathy. In this review, we describe the commonly used metrics for evaluating glycemic variability in clinical practice and summarize the role and related mechanisms of glycemic variability in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. In addition, we also address the potential pharmacological and non-pharmacological treatment methods for diabetic neuropathy, aiming to provide ideas for the treatment of diabetic neuropathy.

Zhang et al. describe metrics for evaluating glycaemic variability (GV) in clinical practice and summarize the role and related mechanisms of GV in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. They aim to stimulate ideas for the treatment of diabetic neuropathy.

In-Hospital Mortality and Glycemic Control in Patients with Hospital Hyperglycemia

BACKGROUND

Stress-induced hyperglycemia is a phenomenon that occurs typically in patients hospitalized for acute disease and resolves spontaneously after regression of the acute illness. However, it can also occur in diabetes patients, a fact that is sometimes overlooked. It is thus important to make a proper diabetes diagnosis if hospitalized patients with episodes of hyperglycemia with and without diabetes are studied.

AIMS

To estimate the extent of the association between stress-induced hyperglycemia and in-hospital mortality in patients with hospital hyperglycemia (HH), and to explore potential differences between patients diagnosed with diabetes (HH-DBT) and those with stress-induced hyperglycemia (SH), but not diagnosed with diabetes.

METHODS

A cohort of adults with hospital hyperglycemia admitted to a tertiary, university hospital in Buenos Aires, Argentina, was analyzed retrospectively.

RESULTS

In the study, 2,955 patients were included and classified for analysis as 1,579 SH and 1,376 HH-DBT. Significant differences were observed in glycemic goal (35.53% SH versus 25.80% HH-DBT, p < 0.01), insulin use rate (26.66% SH versus 46.58% HH-DBT, p < 0.01), and severe hypoglycemia rate (1.32% SH versus 1.74% HH-DBT, p < 0.01). There were no differences in hypoglycemia rate (8.23% SH versus 10.53% HH-DBT) and hospital mortality. There was no increase in risk of mortality in the SH group adjusted for age, non-scheduled hospitalization, major surgical intervention, critical care, hypoglycemia, oncological disease, cardiovascular comorbidity, and prolonged hospitalization.

CONCLUSIONS

In this study, we observed better glycemic control in patients with SH than in those with HH-DBT, and there was no difference in hospital mortality.

Relationship between short and long-term glycemic variability and oxidative stress in type 1 diabetes mellitus under daily life insulin treatment

OBJECTIVE

The purpose of this study was to investigate the heterogeneity of the association between glycemic variability and oxidative stress markers in T1DM patients under daily life insulin treatment.

METHODS

We studied, in a cross-sectional analysis, 76 T1DM patients without clinical chronic diabetes complications and 22 healthy individuals. Were evaluated the short-term glycemic variability (STGV), long-term glycemic variability (LTGV), oxidative stress markers [8-isoprostaglandin-F2α (Ur-8-iso-PGF2α), nitric oxide (NO), thiobarbituric acid reactive substances (TBARS) and erythrocytes reduced/oxidized glutathione (GSH/GSSG)] and biochemical dosages (glycaemia, HbA1c, lipidogram, albuminuria).

RESULTS

Plasmatic NO was positively associated with LTGV (last year average of HbA1c) (8.7 ± 1.6% or 71 ± 18 mmol) (rS: 0.278; p: 0.042). Plasmatic TBARS, erythrocytes GSH/GSSH and Ur-8-iso-PGF-2α didn't show correlation with glycemic variability. GSH/GSSG was inversely correlated with LDL-cholesterol (rS: - 0.417; p: 0.047) and triglycerides (rS: -0.521; p: 0.013). Albuminuria was positive correlated with age (rS: 0.340; p: 0.002), plasmatic NO (rS: 0.267; p 0.049) and TBARS (rS: 0.327; p: 0.015).

CONCLUSION

In daily life insulin treatment, young T1DM patients have higher plasmatic NO than healthy subjects. However, the correlation between glycemic variability and oxidative stress markers is heterogeneous. Lipid profile and albuminuria are associated with different oxidative stress markers. These data collaborate to explain the controversial results in this issue.

Heart Failure in Type 1 Diabetes: A Complication of Concern? A Narrative Review

Heart failure (HF) has been a hot topic in diabetology in the last few years, mainly due to the central role of sodium-glucose cotransporter 2 inhibitors (iSGLT2) in the prevention and treatment of cardiovascular disease and heart failure. It is well known that HF is a common complication in diabetes. However, most of the knowledge about it and the evidence of cardiovascular safety trials with antidiabetic drugs refer to type 2 diabetes (T2D). The epidemiology, etiology, and pathophysiology of HF in type 1 diabetes (T1D) is still not well studied, though there are emerging data about it since life expectancy for T1D has increased in the last decades and there are more elderly patients with T1D. The association of T1D and HF confers a worse prognosis than in T2D, thus it is important to investigate the characteristics, risk factors, and pathophysiology of this disease in order to effectively design prevention strategies and therapeutic tools.

Comparisons of efficacy and safety in insulin glargine and lixisenatide plus glulisine combination therapy with multiple daily injection therapy in Japanese patients with type 2 diabetes

Aims/Introduction

Multiple daily injection therapy for early glycemic control in patients with type 2 diabetes mellitus is associated with hypoglycemia and weight gain. This study aimed to compare the efficacy (time in range of glucose level 70–180 mg/dL), safety (time below range level 1 of glucose <70 mg/dL), glycemic variability changes, therapeutic indices, body mass index and titration periods between multiple daily injection and insulin glargine U100 and lixisenatide (iGlarLixi) combination (iGlarLixi + insulin glulisine; injected once daily [evenings]) therapies using intermittent continuous glucose monitoring.

Materials and Methods

A total of 40 hospitalized patients with type 2 diabetes were randomly assigned to the iGlarLixi + insulin glulisine group or the multiple daily injection group. An intermittent continuous glucose monitoring system was attached, and each injection was adjusted to achieve the target glucose level according to the respective titration algorithm. Times in and below the range were analyzed using data collected on days 11–13 of the intermittent continuous glucose monitoring.

Results

The time in range did not significantly differ between the groups. However, the time below range level 1 was lower in the iGlarLixi + insulin glulisine group (P = 0.047). The changes in glycemic variability, therapeutic indices and body mass index were not significantly different between the groups, although the titration period was significantly shorter in the iGlarLixi + insulin glulisine group (P = 0.033).

Conclusions

iGlarLixi + insulin glulisine combination therapy is safe and equally efficacious as multiple daily injection therapy for glycemic control, while avoiding hypoglycemia risk and reducing the number of injections are required.

Glycemic Trajectories and Treatment Outcomes of Patients with Newly Diagnosed Tuberculosis: A Prospective Study in Eastern China

Rationale: Patients with newly diagnosed tuberculosis often have inconsistent glycemic measurements during and after treatment. Distinct glycemic trajectories after the diagnosis of tuberculosis are not well characterized, and whether patients with stress hyperglycemia have poor treatment outcomes is not known.Objectives: To identify distinct glycemic trajectories from the point of tuberculosis diagnosis to the posttreatment period and to assess the relationship between glycemic trajectories and tuberculosis treatment outcomes.Methods: Patients with newly diagnosed, drug-susceptible tuberculosis and with at least three fasting plasma glucose tests at tuberculosis diagnosis and during the third and sixth month of treatment were identified and included from Jiangsu Province, China. Patients were also given an additional fasting plasma glucose test at 2 and 4 months after treatment.Measurements and Main Results: Several distinct glycemic trajectories from the point of tuberculosis diagnosis to the posttreatment period were found, including consistently normal glycemic testing results (43%), transient hyperglycemia (24%), erratic glycemic instability (12%), diabetes (16%), and consistent hyperglycemia without diabetes (6%). Compared with participants with a consistently normal glycemic trajectory, patients with transient hyperglycemia were more likely to experience treatment failure (adjusted odds ratio [AOR], 4.20; 95% confidence interval [CI], 1.57-11.25; P = 0.004) or erratic glycemic instability (AOR, 5.98; 95% CI, 2.00-17.87; P = 0.001). Patients living with diabetes also had a higher risk of experiencing treatment failure (AOR, 6.56; 95% CI, 2.22-19.35; P = 0.001), and this was modified by glycemic control and metformin use.Conclusions: Among patients with tuberculosis without diabetes, glycemic changes were common and may represent an important marker for patient response to tuberculosis treatment.