Association between BMI and risk of severe hypoglycaemia in type 2 diabetes

Cardiac autonomic neuropathy modified the association between obesity and hypoglycemia in type 2 diabetes

BACKGROUND

Previous studies have shown that increasing body mass index (BMI) was associated with decreased hypoglycemia in type 2 diabetes, but it remains uncertain whether this finding could be applied to patients with and without cardiac autonomic neuropathy (CAN).

METHODS

The study included 7789 participants with type 2 diabetes from action to control cardiovascular risk in diabetes (ACCORD) trail. CAN was defined as SDNN < 8.2 ms and RMSSD < 8.0 ms. Obesity was defined as BMI ≥ 30 kg/m2. Outcomes were identified as severe hypoglycemia requiring any assistance (HAA) or requiring medical assistance (HMA). We assessed the association between obesity and severe hypoglycemia in type 2 diabetes with or without CAN using COX regression models adjusted for baseline characteristics.

RESULTS

Over a median follow-up of 4.7 years, a total of 893 participants developed HAA and 584 participants developed HMA. Compared with non-obesity, obesity was associated with lower risk of severe hypoglycemia (HAA: hazard ratio [HR] 0.51, 95% confidence interval [CI] 0.38-0.68, P < 0.001; HMA: HR 0.57, 95% CI 0.40-0.82, P = 0.002) in CAN present group, but not in CAN absent group (HAA: HR 0.98, 95% CI 0.83-1.16, P = 0.830; HMA: HR 0.97, 95% CI 0.79-1.19, P = 0.754). Similarly, increasing BMI was associated with reduced severe hypoglycemic events in participants with CAN, but not in participants without CAN.

CONCLUSIONS

CAN modifies the association between obesity and hypoglycemia in type 2 diabetes. Type 2 diabetic individuals with CAN who are under weight control should pay attention to hypoglycemic events.

TRIAL REGISTRY

http://www.

CLINICALTRIALS

gov . Unique identifier: NCT00000620.

Factors and economic burden of non-severe hypoglycemia among insulin-treated type 2 diabetes patients: a cross-sectional study

OBJECTIVE

This cross-sectional survey was performed to assess the prevalence, factors, and economic burden of non-severe hypoglycemia among insulin-treated type 2 diabetes (T2D) patients in northern Thailand.

METHODS

Between April 2021 and August 2022, 600 participants were evaluated via structured questionnaires containing sociodemographic and clinical characteristics, medications, and economic burden. Patients were divided into two groups (having and not having non-severe hypoglycemia). Variables with a p value <.05 in the univariate model were included in the multivariate model.

RESULTS

The percentage of non-severe hypoglycemia was 50.3% (302/600). Of all participants, the average age was 61.4 ± 26.0 years, 55.7% were female, 53.5% used premix insulin, and the average duration of diabetes was 16.1 ± 10.0 years. Multivariate logistic regression analysis indicated that age (OR = .96; p <.001), duration of diabetes (OR = 1.04; p <.001), BMI (OR = .95; p = .002), thiazolidinedione (OR = 1.56; p = .012) and insulin regimens were associated with having non-severe hypoglycemia. Compared to basal insulin, basal bolus (OR = 6.93; p = .001), basal plus (OR = 3.58; p <.001), and premix insulin (OR = 1.83; p =.003) were associated with hypoglycemia. Greater numbers of sick leave were found in the hypoglycemia group (14 vs 4 patients, p = .029).

CONCLUSIONS

These findings help to individuate those patients who are at higher risk of non-severe hypoglycemia in insulin-treated T2D patients. Compared to the non-hypoglycemia group, patients with hypoglycemia were younger, had longer diabetes duration, lower BMI, received thiazolidinedione and insulin regimens such as premix, basal plus, or basal bolus insulins, and more productivity loss.

Identification of factors associated with fear of hypoglycemia using the capability, opportunity, motivation and behavior model in people with type 2 diabetes mellitus: a cross-sectional study

AIMS

To examined the relationship between fear of hypoglycemia and certain variables in people with type 2 diabetes mellitus (T2DM) based on the Capability, Opportunity, Motivation, and Behavior model, combined with the context unique to people with diabetes to provide a basis for developing targeted nursing interventions.

METHODS

In this cross-sectional study, 212 people with T2DM were recruited from February 2021 to July 2021. Data were collected using the Hypoglycaemia Fear Survey, Gold score, Patient Assessment of Chronic Illness Care (PACIC) scale and Diabetic Self-Management Attitudes Scale. Multiple linear regression analysis was performed to determine the predictors of fear of hypoglycemia using SPSS 26.0.

RESULTS

The mean fear of hypoglycemia score was 74.88 ± 18.28 (range: 37.00-132.00). In people with T2DM, the frequency of blood glucose monitoring, the frequency of hypoglycemia in the past half-year, degree of understanding of hypoglycemia, impaired awareness of hypoglycemia, PACIC, and self-management attitude of diabetes were the influencing factors of fear of hypoglycemia (adjusted R2 = 0.560, F[21,190] = 13.800, P < 0.001). These variables explained 56.0% of the variance in the fear of hypoglycemia.

CONCLUSIONS

The level of fear of hypoglycemia in people with T2DM was relatively high. In addition to paying attention to the disease characteristics of people with T2DM, medical staff should also pay attention to patients' own perception and handling ability of disease and hypoglycemia, attitude toward self-management behavior and external environment support, all of which have a positive effect on improving the fear of hypoglycemia in people with T2DM, optimizing the self-management level and improving quality of life.

Prediction of Hypoglycemia in Diabetic Patients During Colonoscopy Preparation

OBJECTIVE

To explore the clinical outcomes and establish a predictive model of hypoglycemia during colonoscopy preparation for diabetic patients.

METHODS

Three-hundred ninety-four patients with diabetes who received colonoscopy were retrospectively enrolled in this study and assigned to hypoglycemia or non-hypoglycemia groups. Information about clinical characteristics and outcomes during colonoscopy preparation was collected and compared between the two groups. Logistic regression analysis was applied to identify the risk factors of hypoglycemia. These risk factors were used to construct a hypoglycemia predictive model verified by the receiver operating characteristic (ROC) curve and Hosmer-Lemeshow goodness fit test.

RESULTS

Among 394 participants, 66 (16.8%) underwent a total of 88 hypoglycemia attacks during the bowel preparation. Grade 1 hypoglycemia (≤3.9 mmol/L) comprised 90.9% (80/88) of all hypoglycemia attacks and grade 2 hypoglycemia accounted for 9.1% (8/88), signifying that grade 1 hypoglycemia is the most common type. No severe hypoglycemia was identified. The incidence of nocturnal hypoglycemia was 15.9%. Logistic regression analyses revealed that the main risk factors of hypoglycemia during colonoscopy preparation were postprandial C-peptide, serum triglyceride, gender, type of diabetes mellitus, and insulin injection frequencies. The area under the ROC curve of the hypoglycemia prediction model was 0.777 (95% CI: 0.720-0.833).

CONCLUSION

Diabetic patients are prone to develop mild to moderate hypoglycemia during colonoscopy preparation. This study proposes a predictive model that could provide a reference for identifying patients with a high risk of hypoglycemia during colonoscopy preparation.

Findings for iGlarLixi versus BIAsp 30 confirmed in groups of people with type 2 diabetes with different biomedical characteristics

AIM

To report prespecified and post hoc analyses of the SoliMix dataset exploring the impact of baseline participant characteristics on the original SoliMix study outcomes, to enable informed treatment choices for people with different biomedical characteristics.

METHODS

SoliMix (EudraCT 2017-003370-13) compared once-daily iGlarLixi (a fixed-ratio combination of insulin glargine 100 U/mL and the glucagon-like peptide-1 receptor agonist lixisenatide) with twice-daily BIAsp 30 (30% insulin aspart and 70% insulin aspart protamine). In this analysis, the original primary outcomes of noninferiority of iGlarLixi versus BIAsp 30 in terms of glycated haemoglobin (HbA1c) change and superiority in terms of body weight change, together with change in basal insulin dose and hypoglycaemia outcomes, were investigated by baseline age, duration of diabetes, insulin dose, HbA1c level, body mass index (BMI), and renal function.

RESULTS

No evidence of difference in comparative treatment effect was detected across baseline age, duration of diabetes, insulin dose, HbA1c level, BMI and renal function subgroups for any endpoint (all heterogeneity P > 0.05), except American Diabetes Association Level 2 hypoglycaemia event rate when stratified by insulin dose (P = 0.011), which may be a chance difference given multiple testing and the small numbers of Level 2 events.

CONCLUSIONS

Treatment effects of iGlarLixi were consistent irrespective of baseline HbA1c, insulin dose, BMI, age, duration of diabetes and renal function, supporting the use of iGlarLixi as an efficacious and well-tolerated treatment option in people with type 2 diabetes with a wide range of biomedical characteristics.

C-peptide level concomitant with hypoglycemia gives better performances than insulin for the diagnosis of endogenous hyperinsulinism: a single-center study of 159 fasting trials

INTRODUCTION

Diagnosis of endogenous hyperinsulinism relies on the occurrence of a hypoglycemia, concomitant with inadequate high insulin and C-peptide levels. However, diagnostic cutoffs are not consensual among the different learned societies. The objective of this work was to propose optimized cutoffs for these three parameters for the diagnosis of endogenous hyperinsulinism.

METHODS

All the patients having performed a fasting trial in Cochin Hospital Endocrinology Department between February 2012 and August 2022 were included. The results of glycemia, insulin and C-peptide levels during fasting trial were collected and analyzed.

RESULTS

One hundred and fifty-nine patients were included: 26 with endogenous hyperinsulinism and 133 without endogenous hyperinsulinism. ROC analysis of glycemia nadir during fasting trial identified the value of 2.3 mmol/L as the optimal cutoff, ensuring a sensitivity of 100% associated with a specificity of 81%. ROC analysis of insulin and C-peptide levels concomitant with hypoglycemia <2.3 mmol/L showed very good diagnostic performances of both parameters with respective cutoffs of 3.1 mUI/L (=21.5 pmol/L; sensitivity = 96%; specificity = 92%) and 0.30 nmol/L (sensitivity = 96%; specificity = 100%). Insulin to glycemia ratio as well as C-peptide to glycemia ratio (in pmol/mmol) at the time of glycemia nadir did not show better diagnostic performances than C-peptide alone.

CONCLUSION

A C-peptide level 0.3 nmol/L concomitant with a hypoglycemia <2.3 mmol/L appears as the best criterion to make the diagnosis of endogenous hyperinsulinism. Insulin level can be underestimated on hemolyzed blood samples, frequently observed in fasting trial, and thus shows lower diagnostic performances.

Reactive hypoglycaemia during the OGTT after gestational diabetes mellitus: Metabolic implications and evolution

AIMS

Gestational diabetes (GDM) presents an increased cardio-metabolic risk and is diagnosed with an oral glucose tolerance test (OGTT). Reactive hypoglycaemia (RH) during the OGTT in pregnancy is associated with adverse outcomes. Although postpartum OGTT after GDM is recommended, the occurrence and implications of RH are unknown. We investigated the prevalence, metabolic implications and longitudinal evolution of RH at 6-8 weeks postpartum in women with a history of GDM.

METHODS

Between 2011 and 2021, we consecutively followed 1237 women with previous GDM undergoing an OGTT at 6-8 weeks postpartum. RH was defined as 2-h glucose <3.9 mmoL/L after the OGTT. Metabolic outcomes were compared in women with and without RH (RH+/RH-). We also included a subcohort of 191 women with data on insulin sensitivity/secretion indices (MATSUDA, HOMA-IR, insulin-adjusted-secretion ISSI-2).

RESULTS

The postpartum prevalence of RH was 12%. RH+ women had a more favourable metabolic profile including a 2-5-times lower prevalence of glucose intolerance and metabolic syndrome at 6-8 weeks postpartum compared to RH- (all p ≤ 0.034). In the subcohort, women with RH+ had higher insulin sensitivity, higher ISSI-2 and an earlier glucose peak after OGTT (p ≤ 0.049) compared to RH- women at the same time point. Insulin resistance increased and ISSI-2 decreased over the first year postpartum in both groups. These changes were associated with a 50% reduction in overall RH prevalence at 1-year postpartum. Some of the favourable profiles of RH+ persisted at 1-year postpartum, without group differences in the longitudinal metabolic changes.

CONCLUSIONS

At 6-8 weeks postpartum, RH was frequent in women after GDM and associated with a better metabolic profile including increased insulin sensitivity and higher insulin-adjusted-secretory capacity. RH might be a marker of favourable metabolic prognosis in women with a history of GDM.

Clinical Intervention Effect of a Predictive Model Constructed Based on Risk Factors for Falls in Elderly Patients during Hospitalization

Falls in elderly patients are an important cause of fractures, functional impairment, and mortality. In this paper, a questionnaire was used to collect information on fall history, balance function and sensory function from patients over 65 years of age. In the analysis, the presence or absence of falls was used as a factor, and a corresponding prediction model was constructed using methods such as univariate analysis and regression analysis. This survey found that in the past year, 60% of the patients had fallen, 16.67% had one fall, 33.33% had two falls, and 50% had three or more falls; model specificity is 61.54%, the sensitivity is 71.43%, and the misjudgment is 38.46%. The model has good specificity and sensitivity and a small misjudgment rate; so, the model is more reasonable. This paper selects several sensitivity indices that have a certain impact on the risk of falling and makes a satisfactory forecast, which can provide a theoretical basis for the prevention of the risk of falls in elderly patients during hospitalization.

Analysis of Severe Hypoglycemia Among Adults With Type 2 Diabetes and Nonalcoholic Fatty Liver Disease

IMPORTANCE

Previous studies have indicated that liver cirrhosis is associated with hypoglycemia, but there have been no studies investigating the association between nonalcoholic fatty liver disease (NAFLD) and hypoglycemia in noncirrhotic populations with type 2 diabetes.

OBJECTIVE

To explore the association of NAFLD with severe hypoglycemia among patients with type 2 diabetes.

DESIGN, SETTING, AND PARTICIPANTS

This nationwide population-based retrospective cohort study using the National Health Insurance System of South Korea included individuals aged 20 years or older who had undergone a medical health examination between January 1, 2009, and December 31, 2012, and were diagnosed with type 2 diabetes. Participants were followed up until December 31, 2015. Data analyses were performed between January 1, 2019, and February 2, 2021.

EXPOSURES

The baseline fatty liver index (FLI) was used as a surrogate marker for NAFLD.

MAIN OUTCOMES AND MEASURES

The outcome of interest, severe hypoglycemia, was measured using hospital admission and emergency department visit records with a primary diagnosis of hypoglycemia.

RESULTS

Among 1 946 581 individuals with type 2 diabetes, 1 125 187 (57.8%) were male. During a median (IQR) follow-up of 5.2 (4.1-6.1) years, 45 135 (2.3%) experienced 1 or more severe hypoglycemia events. Participants with severe hypoglycemia, vs those without severe hypoglycemia, were older (mean [SD] age, 67.9 [9.9] years vs 57.2 [12.3] years; P < .001) and had lower mean (SD) body mass index (24.2 [3.43] vs 25.1 [3.4]; P < .001). Patients with NAFLD tended to have less severe hypoglycemia without consideration of obesity status. However, after adjustment of multiple clinical covariates, including body mass index, there was a J-shaped association between FLI and severe hypoglycemia (5th decile: adjusted hazard ratio [aHR], 0.86; 95% CI, 0.83-0.90; 9th decile: aHR, 1.02; 95% CI, 0.96-1.08; 10th decile: aHR, 1.29; 95% CI, 1.22-1.37), and the estimated risk of hypoglycemia was higher in participants with NAFLD (aHR, 1.26; 95% CI, 1.22-1.30). The association was more prominent in female participants (aHR, 1.29; 95% CI, 1.23-1.36) and those with underweight (aHR, 1.71; 95% CI, 1.02-2.88).

CONCLUSIONS AND RELEVANCE

In this study, NAFLD was associated with a higher risk of severe hypoglycemia in patients with type 2 diabetes independent of obesity status. Presence of NAFLD should be considered when evaluating vulnerability to hypoglycemia in patients with type 2 diabetes.

The Impact of Hypoglycemia on Patients with Diabetes Mellitus: A Cross-Sectional Analysis

The increasing mortality and morbidity in patients with diabetes mellitus constitute a severe public health problem. The condition is recognized as a cause of impaired quality of life, high costs, and diminished productivity. In this study, we performed a cross-sectional analysis among 300 Polish participants with type 1 and type 2 diabetes to determine and classify risk factors associated with increased incidences of hypoglycemia. Including an open-access knowledge about the correlations between diabetes rates and human’s lifestyle, we confirm that the frequency of smoking and drinking alcohol, low BMI, inappropriate diet, low physical activity, lack of vaccination against influenza and pneumococci, and co-existence of other comorbidities such as cardiovascular diseases, thyroid diseases, hyperlipidemia, retinopathy, and asthma elevate the risk of hypoglycemia. Furthermore, hypoglycemic patients were more often malnourished, depressed, irritated, and exposed to stress. In sum, the analysis of the interaction between diabetes and sociodemographic, environmental, or other disease-related risk factors provides strategies to optimize glycemic control and reduce the incidence of hypoglycemia. Furthermore, we believe our findings may constitute a basis for promoting health by adjusting available and implementing new preventive services reducing hypoglycemic episodes in diabetic patients.

Glucose variability in subjects with normal glucose tolerance: Relations with body composition, insulin secretion and sensitivity

BACKGROUND AND AIMS

To estimate the determinants of glucose variability (GV) in young and middle-aged non-obese subjects with normal glucose tolerance (NGT) we assessed relations between GV parameters, body composition, insulin secretion and sensitivity indices.

METHODS

Thirty individuals with normal body mass index (BMI) and twenty overweight subjects were included. 24-hour mean glucose, time in range, time above range (TAR), time below range (TBR), standard deviation (SD), coefficient of variation (CV), mean amplitude of glucose excursions (MAGE), continuous overlapping net glycemic action (CONGA), J-index, lability index (LI), mean absolute glucose (MAG), M-value, high blood glucose index (HBGI), low blood glucose index (LBGI) were derived from continuous glucose monitoring. Body composition was assessed by DEXA. Insulin secretion and sensitivity was estimated by HOMA-IR and HOMA-B scores.

RESULTS

Overweight subjects demonstrated higher mean glucose, CONGA, J-index and lower TBR, M-value and LBGI values. Mean glucose correlated positively with total, trunk, gynoid and android fat mass, while M-value and LBGI demonstrated negative correlations with these parameters. In multiple stepwise regression analysis, android fat mass was a predictor of mean glucose, CONGA, J-index, SD and MAGE, gynoid fat mass predicted J-index only, and total fat mass was associated inversely with MAG. Fasting insulin was a predictor of TAR, SD, CV, MAGE, MAG, LI and HBGI. HOMA-B was associated with CONGA, M-value and LBGI.

CONCLUSION

In non-obese subjects with NGT mean glucose and GV parameters are related to fat mass and fat distribution. These relations can be mediated through insulin secretion and sensitivity.

Hypoglycemia: Elucidating its circadian propensity and recovery time based on clinical parameters

BACKGROUND

Hypoglycemia is frequently associated with insulin therapy in diabetic patients; it leads to many short and long-term complications and even death if not addressed in time. This study was undertaken to observe the circadian propensity of hypoglycemia and its recovery time based on type 2 diabetes mellitus patients' clinical parameters.

METHODS

We included type 2 diabetes mellitus (DM) hospitalized patients with the exclusion of patients suffering from critical illness. Data were collected for a period of three months (September to November 2019).

RESULTS

A total of 120 patients were included, comprising 60% males and 40% females. Approximately 55% of patients had hypoglycemic episodes at around 12 am- 6 am. The most common comorbidity present in these patients was hypertension (43.3%, P=0.931). Anemia (OR-3.765, CI-1.350-5.500, P=0.011), retinopathy (OR 6.066, CI-2.031-8.113, P=0.001), and duration of DM (OR-6.266, CI-2.209-7.774, P=0.001) were significantly associated with the recovery time of hypoglycemia, around 50±14.14min in the elderly population of age 60-70. People with BMI 22.5- 27.5 Kg/m2 took around 45.66 ± 19.37 min to recover after treatment.

CONCLUSION

Time taken to recover from hypoglycemic episodes vary with age and BMI. Associated comorbidities such as anemia, retinopathy, and DM duration had a significant bearing on the time taken to recover from hypoglycemia. Recovery time was directly proportional to BMI, a new finding that needs further molecular level evaluation. Circadian propensity of hypoglycemia in these patients have been identified in the early morning hours of the day.

EXercise to Prevent frailty and Loss Of independence in insulin treated older people with DiabetEs (EXPLODE): protocol for a feasibility randomised controlled trial (RCT)

INTRODUCTION

There are 3.9 million people in the UK with diabetes. Sarcopenia, increased frailty and loss of independence are often unappreciated complications of diabetes. Resistance exercise shows promise in reducing these complications in older adult diabetes patients. The aim of this feasibility randomised controlled trial is to (1) characterise the physical function, cardiovascular health and the health and well-being of older adults with mild frailty with/without diabetes treated with insulin, (2) to understand the feasibility and acceptability of a 4-week resistance exercise training programme in improving these parameters for those with diabetes and (3) to test the feasibility of recruiting and randomising the diabetic participant group to a trial of resistance training.

METHODS AND ANALYSIS

Thirty adults aged ≥60 years with insulin-treated diabetes mellitus (type 1 or 2), and 30 without, all with mild frailty (3-4 on the Rockwood Frailty Scale) will be recruited. All will complete blood, cardiovascular and physical function testing. Only the diabetic group will then proceed into the trial itself. They will be randomised 1:1 to a 4-week semisupervised resistance training programme, designed to increase muscle mass and strength, or to usual care, defined as their regular physical activity, for 4 weeks. This group will then repeat testing. Primary outcomes include recruitment rate, attrition rate, intervention fidelity and acceptability, and adherence to the training programme. A subset of participants will be interviewed before and after the training programme to understand experiences of resistance training, impact on health and living with diabetes (where relevant) as they have aged. Analyses will include descriptive statistics and qualitative thematic analysis.

ETHICS AND DISSEMINATION

The North East-Newcastle and North Tyneside 2 Research Ethics Committee (20/NE/0178) approved the study. Outputs will include feasibility data to support funding applications for a future definitive trial, conference and patient and public involvement presentations, and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

ISRCTN13193281.

The obesity paradox and hypoglycemia in critically ill patients

BACKGROUND

A high body mass index (BMI) has been associated with decreased mortality in critically ill patients. This association may, in part, relate to the impact of BMI on glycemia. We aimed to study the relationship between BMI, glycemia and hospital mortality.

METHODS

We included all patients with a recorded BMI from four large international clinical databases (n = 259,177). We investigated the unadjusted association of BMI with average glucose levels, mortality and hypoglycemia rate. We applied multivariate analysis to investigate the impact of BMI on hypoglycemia rate, after adjusting for glycemia-relevant treatments (insulin, dextrose, corticosteroids, enteral and parenteral nutrition) and key physiological parameters (previous blood glucose level, blood lactate, shock state, SOFA score).

RESULTS

We analyzed 5,544,366 glucose measurements. On unadjusted analysis, increasing BMI was associated with increasing glucose levels (average increase of 5 and 10 mg/dL for the 25-30, 30-35 kg/m2 BMI groups compared to normal BMI (18.5-25 kg/m2) patients). Despite greater hyperglycemia, increasing BMI was associated with lower hospital mortality (average decrease of 2% and 3.25% for the 25-30, 30-35 kg/m2 groups compared to normal BMI patients) and lower hypoglycemia rate (average decrease of 2.5% and 3.5% for the 25-30, 30-35 kg/m2 groups compared to normal BMI patients). Increasing BMI was significantly independently associated with reduced hypoglycemia rate, with odds ratio (OR) 0.72 and 0.65, respectively (95% CIs 0.67-0.77 and 0.60-0.71, both p < 0.001) when compared with normal BMI. Low BMI patients showed greater hypoglycemia rate, with OR 1.6 (CI 1.43-1.79, p < 0.001). The association of high BMI and decreased mortality did not apply to diabetic patients. Although diabetic patients had higher rates of hypoglycemia overall and higher glucose variability (p < 0.001), they also had a reduced risk of hypoglycemia with higher BMI levels (p < 0.001).

CONCLUSIONS

Increasing BMI is independently associated with decreased risk of hypoglycemia. It is also associated with increasing hyperglycemia and yet with lower mortality. Lower risk of hypoglycemia might contribute to decreased mortality and might partly explain the obesity paradox. These associations, however, were markedly modified by the presence of diabetes.

Increased nutrition-related risk as an independent predictor of the incidence of hypoglycemia in the hospitalized older individuals with type 2 diabetes: a single-center cohort study

Background and aims

There are few reports on the association between malnutrition and hypoglycemia. The geriatric nutritional risk index (GNRI) allows risk classification by morbidity and mortality resulting from conditions often associated with malnutrition in older individuals. However, the association between GNRI and hypoglycemia is unclear. This study examined the associations between nutrition-related risk and hypoglycemia among older individuals with type 2 diabetes (T2D) using diabetes medication.

Methods

This single-center historical cohort study included hospitalized patients aged ≥ 65 years with T2D on medication. Nutrition-related risk was assessed using the GNRI and classified into four risk groups. Hypoglycemia and serious hypoglycemia were determined by oral or intravenous glucose intake and blood glucose < 3.9 mmol/L (70 mg/dL) as hypoglycemia, among them blood glucose < 3.0 mmol/L (54 mg/dL) as serious hypoglycemia. Data were recorded at least once during hospitalization.

Results

Patients who met the criteria (n = 1.754) were included in the study. The participants median age was 75.0 years. During the study, 81 patients (4.6%) experienced hypoglycemia and 7 patients (0.4%) experienced serious hypoglycemia. Hypoglycemia was observed in patients in the major risk (16.0%), moderate risk (9.7%), low risk (5.2%), and no risk (1.5%) groups (p for trend < 0.001). After adjusting for other risk factors, the hazard ratios of hypoglycemic among people with major, moderate, and low risk were 5.50, 3.86, and 2.55, respectively.

Conclusions

Hypoglycemia increased with increasing nutrition-related risk among older individuals with T2D using diabetes medication. The GNRI is a simple and useful assessment tool in the clinical setting.

Smoking is Associated With Increased Risk of Not Achieving Glycemic Target, Increased Glycemic Variability, and Increased Risk of Hypoglycemia for People With Type 1 Diabetes

BACKGROUND

The prevalence of smoking and diabetes is increasing in many developing countries. The aim of this study was to investigate the association of smoking with inadequate glycemic control and glycemic variability with continuous glucose monitoring (CGM) data in people with type 1 diabetes.

METHODS

Forty-nine smokers and 320 nonsmokers were obtained from the Novo Nordisk Onset 5 trial. After 16 weeks of treatment with continuous subcutaneous insulin infusion, risk of not achieving glycemic target and glycemic variability from six CGM measures was investigated. Analyzes were carried out with logistic regression models (glycemic target) and general linear models (glycemic variability). Finally, CGM median profiles were examined for the identification of daily glucose excursions.

RESULTS

A 4.7-fold (95% confidence interval: 1.5-15.4) increased risk of not achieving glycemic target was observed for smokers compared with nonsmokers. Increased time in hyperglycemia, decreased time in range, increased time in hypoglycemia (very low interstitial glucose), and increased fluctuation were observed for smokers compared with nonsmokers from CGM measures. CGM measures of coefficient of variation and time in hypoglycemia were not statistically significantly different. Examination of CGM median profiles revealed that risk of morning hypoglycemia is increased for smokers.

CONCLUSIONS

In conclusion, smoking is associated with inadequate glycemic control and increased glycemic variability for people with type 1 diabetes with especially risk of morning hypoglycemia. It is important for clinicians to know that if the patient has type 1 diabetes and is smoking, a preemptive action to treat high glycated hemoglobin levels should not necessarily be treatment intensification due to the risk of hypoglycemia.

Real-world risk of hypoglycemia-related hospitalization in Japanese patients with type 2 diabetes using SGLT2 inhibitors: a nationwide cohort study

INTRODUCTION

Sodium-glucose cotransporter 2 (SGLT2) inhibitors are believed to lower glucose levels and inhibit cardiovascular events related to type 2 diabetes (T2D). To maximize their benefits, the risk of resultant hypoglycemia has to be minimized; however, the magnitude of this risk remains unclear. Here, we aimed to identify clinical factors linked to an increased risk of hypoglycemia among Japanese patients with T2D and treated with SGLT2 inhibitors.

RESEARCH DESIGN AND METHODS

This was a real-world retrospective cohort study conducted using the Japanese Medical Data Vision database. We identified patients with T2D and treated with SGLT2 inhibitors who were enrolled in the database from April 2014 to October 2019. Cox multivariate regression analyses were performed to determine demographical and clinical factors linked to SGLT2 inhibitor-associated hypoglycemia-related hospitalization.

RESULTS

Of 171 622 patients prescribed SGLT2 inhibitors, hypoglycemia-related hospitalization occurred in 216 (0.13%), with 0.60 incidences per 100 person-years. The risk of SGLT2 inhibitor-associated hypoglycemia was higher with each 10-year increase in age (HR 1.49; 95% CI 1.32 to 1.68) and high in patients with body mass index <25 kg/m² (HR 1.98; 95% CI 1.50 to 2.61), insulin use (HR 3.26; 95% CI 2.43 to 4.38), and sulfonylurea use (HR 1.44; 95% CI 1.02 to 2.03). The risk was lower in women than in men (HR 0.73; 95% CI 0.54 to 0.98) and low in concomitant metformin users (HR 0.52; 95% CI 0.37 to 0.74).

CONCLUSIONS

These findings may help minimize the risk of hypoglycemia-related hospitalization due to T2D treatment with SGLT2 inhibitors. We revealed that the risk of hypoglycemia may be higher when combining SGLT2 inhibitors with sulfonylureas and/or insulin. Furthermore, we discovered a high risk of hypoglycemia in older and non-obese patients. These findings may assist in maximizing the benefits of SGLT2 inhibitors for the treatment of T2D.