Long-term body weight trajectories and metabolic control in type 1 diabetes patients on insulin pump or multiple daily injections: A 10-year retrospective controlled study

Managing obesity in adults with type 1 diabetes

As the prevalence of obesity has reached epidemic proportions, its prevalence has also increased among adults living with type 1 diabetes mellitus. Unlike the pathophysiologic relationship between obesity and type 2 diabetes mellitus, the relationship between obesity and type 1 diabetes mellitus, and management of obesity in the setting of type 1 diabetes mellitus, have not been well reviewed. In this article, we discuss the comprehensive management of obesity in adults with type 1 diabetes mellitus, focusing on medical nutrition therapy and adjunct therapies such as weight loss-promoting medications and metabolic/bariatric surgery.

Effect of Body Weight on Glycaemic Indices in People with Type 1 Diabetes Using Continuous Glucose Monitoring

Background/Objectives: Obesity and overweight have become increasingly prevalent in different populations of people with type 1 diabetes (PwT1D). This study aimed to assess the effect of body weight on glycaemic indices in PwT1D. Methods: Adult PwT1D using continuous glucose monitoring (CGM) and followed up at a regional academic diabetes centre were included. Body weight, body mass index (BMI), waist circumference, glycated haemoglobin (HbA1c), and standard CGM glycaemic indices were recorded. Glycaemic indices were compared according to BMI, and correlation and linear regression analysis were performed to estimate the association between measures of adiposity and glycaemic indices. Results: A total of 73 PwT1D were included (48% normal weight, 33% overweight, and 19% obese). HbA1c was 7.2% (5.6-10), glucose management indicator (GMI) 6.9% (5.7-8.9), coefficient of variation (CV) for glucose 39.5% ± 6.4, mean glucose 148 (101-235) mg/dL, TIR (time in range, glucose 70-180 mg/dL) 66% (25-94), TBR70 (time below range, 54-69 mg/dL) 4% (0-16), TBR54 (<54 mg/dL) 1% (0-11), TAR180 (time above range, 181-250 mg/dL) 20% ± 7, and TAR250 (>250 mg/dL) 6% (0-40). Glycaemic indices and achievement (%) of optimal glycaemic targets were similar between normal weight, overweight, and obese patients. BMI was associated negatively with GMI, mean glucose, TAR180, and TAR250 and positively with TIR; waist circumference was negatively associated with TAR250. Conclusions: CGM-derived glycaemic indices were similar in overweight/obese and normal weight PwT1D. Body weight and BMI were positively associated with better glycaemic control. PwT1D should receive appropriate ongoing support to achieve optimal glycaemic targets whilst maintaining a healthy body weight.

Blood glucose control and metabolic dysfunction-associated steatotic liver disease in people with type 1 diabetes

PURPOSE

Metabolic dysfunction-associated steatotic liver disease (MASLD) may have distinctive pathophysiological features in type 1 diabetes (T1D). We evaluated the independent role of blood glucose control on MASLD in T1D.

METHODS

In a cross-sectional study on 659 T1D adult patients, MASLD was assessed by the Fatty Liver Index (FLI) and the Hepatic Steatosis Index (HSI). Anthropometric, biochemical, and clinical parameters were retrieved from electronic records. Blood glucose control status was evaluated by dividing participants into subgroups according to the median value of HbA1c [7.6% (60 mmol/mol)], and this analysis was repeated excluding overweight/obese patients.

RESULTS

Patients with HbA1c above 7.6% (60 mmol/mol) showed significantly higher MASLD indices (HSI 38 ± 6 vs. 36 ± 5, p < 0.001; FLI 26 ± 26 vs.19 ± 19, p < 0.001), and higher proportions of MASLD identified by HSI (57 vs. 44%, p < 0.001) and FLI (14 vs. 7%, p < 0.001) than patients with HbA1c below 7.6% (60 mmol/mol). Similar results were obtained for HSI after the exclusion of overweight/obese patients. Stepwise linear regression analysis confirmed that HbA1c was independently associated with HSI (r = 0.496, p = 0.009) and FLI (r = 0.722, p = 0.007); waist circumference with HSI (r = 0.492, p < 0.001); and waist circumference (r = 0.700, p < 0.001), HDL cholesterol (r = 0.719, p < 0.001), and LDL cholesterol (r = 0.712, p < 0.001) with FLI.

CONCLUSIONS

Blood glucose control is a main factor associated with MASLD in adults with T1D, also independently of overweight and obesity. Appropriate therapeutic strategies focused on tight blood glucose control may also be needed for the prevention and treatment of MASLD in T1D.

Postprandial Glucose Control With Different Hybrid Closed-Loop Systems According to Type of Meal in Adults With Type 1 Diabetes

BACKGROUND

Hybrid Closed-Loop Systems (HCLs) may not perform optimally on postprandial glucose control. We evaluated how first-generation and advanced HCLs manage meals varying in carbohydrates, fat, and protein.

METHOD

According to a cross-sectional design, seven-day food records and HCLs reports from 120 adults with type 1 diabetes (MiniMed670G: n = 40, MiniMed780G: n = 49, Control-IQ [C-IQ]: n = 31) were analyzed. Breakfasts (n = 570), lunches (n = 658), and dinners (n = 619) were divided according to the median of their carbohydrate (g)/fat (g) plus protein (g) ratio (C/FP). After breakfast (4-hour), lunch (6-hour), and dinner (6-hour), continuous glucose monitoring (CGM) metrics and early and late glucose incremental area under the curves (iAUCs) and delivered insulin doses were evaluated. The association of C/FP and HCLs with postprandial glucose and insulin patterns was analyzed by univariate analysis of variance (ANOVA) with a two-factor design.

RESULTS

Postprandial glucose time-in-range 70 to 180 mg/dL was optimal after breakfast (78.3 ± 26.9%), lunch (72.7 ± 26.1%), and dinner (70.8 ± 27.3%), with no significant differences between HCLs. Independent of C/FP, late glucose-iAUC after lunch was significantly lower in C-IQ users than 670G and 780G (P < .05), with no significant differences at breakfast and dinner. Postprandial insulin pattern (Ins3-6h minus Ins0-3h) differed by type of HCLs at lunch (P = .026) and dinner (P < .001), being the early insulin dose (Ins0-3h) higher than the late dose (Ins3-6h) in 670G and 780G users with an opposite pattern in C-IQ users.

CONCLUSIONS

Independent of different proportions of dietary carbohydrates, fat, and protein, postprandial glucose response was similar in users of different HCLs, although obtained through different automatic insulin delivery patterns.

Treating obesity in type 1 diabetes mellitus - review of efficacy and safety

PURPOSE OF REVIEW

Obesity is an epidemic in the United States with serious concomitant co-morbid conditions; people living with type 1 diabetes mellitus (T1D) are not immune to the risk either. Weight gain in T1D is likely multifactorial, due to genetic, environmental and treatment-related factors. FDA-approved and other adjunctive weight loss therapies may benefit people living with T1D but there are risks to consider when providing recommendations or prescribing medications.

RECENT FINDINGS

We performed a PubMed search of studies assessing clinical outcomes of both approved and off-label medications used in the treatment of type 1 diabetes. Search terms included 'type 1 diabetes, obesity' and the following: (1) metformin, (2) pramlintide, (3) glucagon-like peptide-1 (GLP-1) receptor agonists, (4) dual GLP-1 and gastric inhibitory polypeptide (GIP) agonists, (5) sodium-glucose cotransporter-2 (SGLT-2) inhibitors, (6) surgical treatment of obesity, (7) insulin pump, (8) insulin, (9) medical nutrition therapy, (10) diabetes self-management education, (11) exercise, (12) naltrexone-buproprion, (13) orlistat, and (14) phentermine-topiramate.

SUMMARY

Weight loss treatments provide a wide-range of benefits in reducing both morbidity and mortality in those who are obese. Treatments also have varying adverse effect profiles which may impact T1D treatment. In this review, we aim to summarize study outcomes in people with T1D, including risks and benefits, of on- and off-label weight loss treatments.

Glycemic Control, Basal/Bolus Distribution, BMI and Meal Management in Children and Adolescents with Type 1 Diabetes and Advanced Hybrid Closed Loop

Evidence about the impact of advanced hybrid closed loop (AHCL) on body mass index (BMI) and eating habits in children with type 1 diabetes (T1D) is lacking. This real-world study aimed at evaluating glycemic control, BMI, meals and basal/bolus distribution in young subjects with T1D treated by AHCL. Glycemic metrics, HbA1c, basal/bolus distribution, meals/day, BMI, total daily dose (TDD), and carbohydrates/kg (CHO/kg) have been evaluated in 83 subjects, aged 13 ± 4.5 years, in manual mode, 3 and 6 months after auto-mode. Time in range (TIR) increased after 3 months, exceeding the target of 70% and was maintained at 6 months. While coefficient of variation (CV) did not change, the glucose management indicator (GMI) decreased in auto-mode (6.7 ± 0.3 vs. 7.1 ± 0.5%; p < 0.001), as well as HbA1c. Basal proportion decreased in favor of boluses (38.3 ± 7.3 vs. 43.6 ± 10.9%; p < 0.001). Meals increased at 3 and 6 months (4.4 ± 1.2 vs. 5.0 ± 1.5, p 0.002 and 5.1 ± 1.7, p < 0.001), as well as TDD/kg, without changes in BMI and CHO consumed. No differences in meal composition have arisen from food diaries. In conclusion, AHCL ensured the achievement and maintenance of target TIR in young T1D subjects. The number of meals, TDD, and insulin bolus proportion increased over time, but BMI remained stable.

The Burden of Obesity in Type 1 Diabetic Subjects: A Sex-specific Analysis From the AMD Annals Initiative

OBJECTIVE

Obesity is a growing emergency in type 1 diabetes (T1D). Sex differences in obesity prevalence and its clinical consequences in adult T1D subjects have been poorly investigated. The aim of this study was to investigate the prevalence of obesity and severe obesity, clinical correlates, and potential sex differences in a large cohort of T1D subjects participating to the AMD (Associazione Medici Diabetologi) Annals Initiative in Italy.

RESEARCH DESIGN AND METHODS

The prevalence of obesity [body mass index(BMI) ≥30 kg/m2] and severe obesity (BMI ≥ 35 kg/m2) according to sex and age, as well as obesity-associated clinical variables, long-term diabetes complications, pharmacological treatment, process indicators and outcomes, and overall quality of care (Q-score) were evaluated in 37 436 T1D subjects (45.3% women) attending 282 Italian diabetes clinics during 2019.

RESULTS

Overall, the prevalence of obesity was similar in the 2 sexes (13.0% in men and 13.9% in women; mean age 50 years), and it increased with age, affecting 1 out of 6 subjects ages >65 years. Only severe obesity (BMI >35 kg/m2) was more prevalent among women, who showed a 45% higher risk of severe obesity, compared with men at multivariate analysis. Cardiovascular disease risk factors (lipid profile, glucose, and blood pressure control), and the overall quality of diabetes care were worse in obese subjects, with no major sex-related differences. Also, micro- and macrovascular complications were more frequent among obese than nonobese T1D men and women.

CONCLUSIONS

Obesity is a frequent finding in T1D adult subjects, and it is associated with a higher burden of cardiovascular disease risk factors, micro- and macrovascular complications, and a lower quality of care, with no major sex differences. T1D women are at higher risk of severe obesity.

Time-trends in body mass index, and overweight and obesity as independent risk factors for diabetes angiopathy in young females with type 1 diabetes - A nationwide study in Sweden

AIMS

To examine time-trends in BMI-distributions of young females with and without type 1 diabetes (T1D), with focus on the upper half of the distribution i.e., the median and above, and to explore if overweight and obesity independently increase risk of diabetes angiopathy.

METHODS

Population-based cohort study of 3,473 females with T1D, 16-35 years, identified in the Swedish National Diabetes Registers, January 2005 to October 2015, and 8,487 females from the background population. BMI-distributions were examined using kernel density estimates and quantile regression. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for angiopathy in overweight/obese subjects were estimated with adjusted Cox regression.

RESULTS

The BMI-distribution in females with T1D was right shifted to that of the background population (p < 0.001). The 90th percentile and median BMI increased equally overtime in both groups, but females with T1D started from a higher baseline. In T1D, HRs were significantly increased for any angiopathy in individuals with obesity (adj HR 1.37 (CI 1.14-1.64)), and for retinopathy; adj HRs (CIs): overweight; 1.15 (1.02-1.29), obesity; 1.30 (1.08-1.56).

CONCLUSIONS

Females with T1D have increasing BMI overtime and are heavier than females without T1D. Overweight and obesity are by themselves risk factors for angiopathy.

Dietary treatment of type 1 diabetes: Beyond carbohydrate counting to fight cardiovascular risk

AIMS

Type 1 diabetes (T1D) is tied to an increased risk of cardiovascular morbidity and mortality. Dietary treatment would be an elective therapeutic strategy to fight this risk. However, it is not known what the best dietary approach is. We revisited the currently available literature on the nutritional treatment of T1D in the light of their potential comprehensive effects on the management of cardio-metabolic risk factors (body weight, fasting and postprandial glucose and lipid metabolism).

DATA SYNTHESIS

Nutritional research in T1D is mainly focused on blood glucose control, with most of the trials aiming at evaluating the acute effects of nutrients on postprandial glycemic response. The effects of the quantity and quality of nutrients and some specific foods on other metabolic risk factors have been explored mainly in cross-sectional analysis. Very few well-designed nutritional trials evaluated the best dietary approach to comprehensively manage cardiovascular risk by targeting along with blood glucose control, overweight, fasting and postprandial dyslipidemia. Therefore, the current best practice guidance for the dietary management of cardiovascular risk in T1D is generally based on evidence from patients with type 2 diabetes.

CONCLUSIONS

Well-conducted nutritional trials specifically designed for T1D are needed to identify the best dietary treatment to fight cardiovascular risk in these patients.

Optimal annual body mass index change for preventing spontaneous preterm birth in a subsequent pregnancy

Preterm birth (PTB) is a leading cause of neonatal morbidity and mortality. Although PTB is known to recur, interpregnancy preventive strategies for PTB have not been established to date. Annual BMI change can serve as a specific target value for preventing obstetric complications during interpregnancy care/counseling. This value can also account for age-related weight gain (0.2 kg/m²/year). In a multicenter retrospective study, we investigated the optimal annual BMI change for preventing PTB recurrence using the data of individuals who had two singleton births from 2009 to 2019. The association between annual BMI change and spontaneous PTB (sPTB) was analyzed by separating cases of medically indicated PTB (mPTB) from those of sPTB. Previous history of sPTB was strongly associated with sPTB in the subsequent pregnancy (adjusted odds ratio [aOR], 12.7; 95% confidence interval [CI], 6.5-24.8). Increase in annual BMI was negatively associated with sPTB (aOR, 0.6; 95% CI 0.5-0.9). The sPTB recurrence rate was significantly lower in patients with an annual BMI change of ≥ 0.25 kg/m²/year than in those with an annual BMI change of < 0.25 kg/m²/year (7.7% vs. 35.0%, p = 0.011). Our findings suggest that age-related annual BMI gain between pregnancies may help prevent sPTB recurrence.

Annual Body Mass Index Gain and Risk of Gestational Diabetes Mellitus in a Subsequent Pregnancy

Introduction

Weight change during the interpregnancy is related to gestational diabetes mellitus (GDM) in the subsequent pregnancy. In interpregnancy care/counseling, the timeframe for goal setting is important, while the timing of the next conception is unpredictable and preventing age-related body weight gain is difficult. This study aimed to investigate the association between annual weight gain during the interpregnancy, which provide clearer timeframe, and GDM in subsequent pregnancies.

Methods

This multicenter retrospective study was conducted by collecting data on two pregnancies of the same women in 2009-2019. The association between annual BMI gain and GDM during the subsequent pregnancy was examined.

Results

This study included 1,640 pregnant women. A history of GDM [adjusted odds ratio (aOR), 26.22; 95% confidence interval (CI), 14.93-46.07] and annual BMI gain (aOR, 1.48; 95% CI, 1.22-1.81) were related to GDM during the subsequent pregnancy. In the women with a pre-pregnant BMI of <25.0 kg/m2 and without GDM during the index pregnancy, an annual BMI gain of ≥0.6 kg/m2/year during the interpregnancy were associated with GDM in subsequent pregnancies; however, in the other subgroups, it was not associated with GDM in subsequent pregnancies.

Conclusions

For women with a pre-pregnant BMI of <25.0 kg/m2 and without GDM during the index pregnancy, maintaining an annual BMI gain of <0.6 kg/m2/year may prevent GDM during the subsequent pregnancy.

Beneficial effects on body weight of group vs individual care in adults with type 1 diabetes on advanced technologies

RATIONALE AND AIMS

Outpatient group visits in diabetes care have several potential advantages and can be simplified by the new technologies. The aim of this study was to assess feasibility and effectiveness of group visits vs individual visits in adults with type 1 diabetes on insulin pump therapy (continuous subcutaneous insulin infusion, CSII) and continuous glucose monitoring (CGM).

METHODS

Outpatient setting for group visits (2-hour duration, quarterly, 6-8 patients) was the projection on giant screen of each patient's CGM and insulin pump data, with interactive discussion moderated by a diabetologist. Anthropometric measures and glycemic control (HbA1c) were assessed before and after a mean observation period of 4.4 ± 1.2 years (mean ± standard deviation, M ± SD) in CSII patients followed by group visits (GROUP) or individual visits (INDIVIDUAL) between 2013 and 2019.

RESULTS

At the beginning of the observation, GROUP and INDIVIDUAL cohorts were strictly matched for gender (M/F = 37/35 and 37/35), age, diabetes duration, body mass index (BMI), CSII duration, and HbA1c level. HbA1c levels did not change significantly between beginning and end of observation in either cohort (GROUP 7.54 ± 0.80% and 7.60 ± 0.79%, P = .585; INDIVIDUAL 7.73 ± 1.27% and 7.60 ± 1.08%, P = .281) (time*visit effect P = .232, two-way repeated measures analysis of variance [ANOVA]). Body weight remained unchanged in the GROUP cohort (73.2 ± 14.0 vs 73.8 ± 14.8 kg, P = .361), while it increased in the INDIVIDUAL cohort (70.3 ± 13.5 vs 73.0 ± 13.7 kg, P < 0.001) (time*visit effect P = .009).

CONCLUSIONS

Group care is feasible in adult patients with type 1 diabetes using new technologies. Group visits can be beneficial in inducing lifestyle changes, as indicated by the favorable effects observed on body weight trend.

Annual body mass index gain and risk of hypertensive disorders of pregnancy in a subsequent pregnancy

Weight gain during interpregnancy period is related to hypertensive disorders of pregnancy (HDP). However, in interpregnancy care/counseling, the unpredictability of the timing of the next conception and the difficulties in preventing age-related body weight gain must be considered while setting weight management goals. Therefore, we suggest considering the annual change in the body mass index (BMI). This study aimed to clarify the association between annual BMI changes during the interpregnancy period and HDP risk in subsequent pregnancies. A multicenter retrospective study of data from 2009 to 2019 examined the adjusted odds ratio (aOR) of HDP in subsequent pregnancies. The aORs in several annual BMI change categories were also calculated in the subgroups classified by HDP occurrence in the index pregnancy. This study included 1,746 pregnant women. A history of HDP (aOR, 16.76; 95% confidence interval [CI], 9.62 - 29.22), and annual BMI gain (aOR, 2.30; 95% CI, 1.76 - 3.01) were independent risk factors for HDP in subsequent pregnancies. An annual BMI increase of ≥ 1.0 kg/m2/year was related to HDP development in subsequent pregnancies for women without a history of HDP. This study provides data as a basis for interpregnancy care/counseling, but further research is necessary to validate our findings and confirm this relationship.

Obesity in people living with type 1 diabetes

Although type 1 diabetes is traditionally considered a disease of lean people, overweight and obesity are becoming increasingly more common in individuals with type 1 diabetes. Non-physiological insulin replacement that causes peripheral hyperinsulinaemia, insulin profiles that do not match basal and mealtime insulin needs, defensive snacking to avoid hypoglycaemia, or a combination of these, are believed to affect body composition and drive excessive accumulation of body fat in people with type 1 diabetes. The consequences of overweight or obesity in people with type 1 diabetes are of particular concern, as they increase the risk of both diabetes-related and obesity-related complications, including cardiovascular disease, stroke, and various types of cancer. In this Review, we summarise the current understanding of the aetiology and consequences of excessive bodyweight in people with type 1 diabetes and highlight the need to optimise future prevention and treatment strategies in this population.

COVID-19 and Type 1 Diabetes: Addressing Concerns and Maintaining Control

The worldwide outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been an unprecedented pandemic. Early on, even as the signs and symptoms of coronavirus disease 2019 (COVID-19) were first characterized, significant concerns were articulated regarding its potential impact on people with chronic disease, including type 1 diabetes. Information about the basic and clinical interrelationships between COVID-19 and diabetes has rapidly emerged. Initial rapid reports were useful to provide alerts and guide health care responses and initial policies. Some of these have proven subsequently to have durable findings, whereas others lacked scientific rigor/reproducibility. Many publications that report on COVID-19 and "diabetes" also have not distinguished between type 1 and type 2 (1). Available evidence now demonstrates that people with type 1 diabetes have been acutely affected by COVID-19 in multiple ways. This includes effects from limited access to health care, particularly during lockdown periods, and increased morbidity/mortality in infected adults with type 1 diabetes compared with peers without diabetes.

Diabetes technologies in people with type 1 diabetes mellitus and disordered eating: A systematic review on continuous subcutaneous insulin infusion, continuous glucose monitoring and automated insulin delivery

AIMS

In this systematic review, we aimed (1) to identify and describe research investigating the use of advanced diabetes technologies (continuous subcutaneous insulin infusion, CSII; continuous glucose monitoring, CGM; automated insulin delivery, AID) in people with type 1 diabetes (T1DM) and disordered eating and (2) to discuss potential (dis)advantages of diabetes technology use in this population, derived from previous research.

METHODS

We conducted a systematic literature search in two electronic databases for English articles published between 2000 and 2020 addressing eating disorders and/or dysfunctional eating behaviours and diabetes technology use in children, adolescents and adults with T1DM (PROSPERO ID CRD42020160244).

RESULTS

Of 70 publications initially identified, 17 were included. Overall, evidence on the use of diabetes technologies in people with T1DM and disordered eating is scarce. The majority of the studies reports findings on CSII in people with T1DM and dysfunctional eating behaviours or eating disorders. Findings predominantly stem from observational data and are, in most cases, secondary findings of the respective studies. Providing the greatest flexibility in diabetes management, CSII may have benefits in disordered eating. CGM data may complement the diagnostic process of disordered eating with a physiological indicator of insulin restriction (i.e. time spent in hyperglycaemia).

CONCLUSIONS

Results on possible (dis)advantages of diabetes technology use in people with T1DM and disordered eating are based on observational data, small pilot trials and anecdotical evidence from case reports. Prospective data from larger samples are needed to reliably determine potential effects of diabetes technology on disordered eating in T1DM.

Obesity in Patients with Type 1 Diabetes: Links, Risks and Management Challenges

Obesity affects large numbers of patients with type 1 diabetes (T1D) across their lifetime, with rates ranging between 2.8% and 37.1%. Patients with T1D and obesity are characterized by the presence of insulin resistance, of high insulin requirements, have a greater cardiometabolic risk and an enhanced risk of developing chronic complications when compared to normal-weight persons with T1D. Dual treatment of obesity and T1D is challenging and no specific guidelines for improving outcomes of both glycemic control and weight management have been established for this population. Nevertheless, although evidence is scarce, a comprehensive approach based on a balanced hypocaloric diet, physical activity and cognitive behavioral therapy by a multidisciplinary team, expert in both obesity and diabetes, remains as the best clinical practice. However, weight loss responses with lifestyle changes alone are limited, so in the "roadmap" of the treatment of obesity in T1D, it will be helpful to include anti-obesity pharmacotherapy despite at present there is a lack of evidence since T1D patients have been excluded from anti-obesity drug clinical trials. In case of severe obesity, bariatric surgery has proven to be of benefit in obtaining a substantial and long-term weight loss and reduction in cardiovascular risk. The near future looks promising with the development of new and more effective anti-obesity treatments and strategies to improve insulin resistance and oxidative stress. Advances in precision medicine may help individualize and optimize the medical management and care of these patients. This review, by gathering current evidence, highlights the need of solid knowledge in all facets of the treatment of patients with obesity and T1D that can only be obtained through high quality well-designed studies.

Effect of adjunctive glucose-lowering drugs on body weight in people with type 1 diabetes: a systematic review and network meta-analysis protocol

INTRODUCTION

Obesity increases the risk of comorbidities and diabetes-related complications and, consequently, efforts to prevent and reduce excess weight in people with type 1 diabetes are essential. The aim of this systematic review and network meta-analysis is to assess the effect of adjunctive glucose-lowering drugs on body weight and other important health outcomes in people with type 1 diabetes.

METHODS AND ANALYSIS

This systematic review and network meta-analysis will include randomised controlled trials (RCTs) evaluating the use of adjunctive glucose-lowering drugs for treatment of people with type 1 diabetes. MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, ClinicalTrials.gov and WHO International Clinical Trials Registry Platform will be searched from inception to present. Key eligibility criteria include: RCT study design; adult participants with type 1 diabetes; treatment with a glucose-lowering drug for ≥24 weeks; and comparison of the intervention to placebo, usual care or another glucose-lowering drug. The primary outcome is change in body weight. Other major outcomes include change in HbA1c and total daily insulin dose and risk of hypoglycaemia and other adverse events. Dual study selection, data extraction and risk of bias assessment will be performed. Results from the meta-analysis will be presented as weighted mean differences for continuous outcomes and risk ratios for dichotomous outcomes. Sources of heterogeneity will be explored by subgroup and sensitivity analysis. A network meta-analysis for the primary outcome will be performed using an arm-based random-effects model based on the Bayesian framework while assessing for transitivity across studies and consistency between direct and indirect estimates. The overall quality of the evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluation approach for each outcome.

ETHICS AND DISSEMINATION

No ethical assessment is required. The results of this review will be disseminated through peer-reviewed publication and conference presentation.

PROSPERO REGISTRATION NUMBER

CRD42020158676.