Cost-Effectiveness of Empagliflozin and Metformin Combination Versus Standard Care as First-Line Therapy in Patients With Type 2 Diabetes Mellitus

ObjectiveSodium-glucose cotransporter 2 inhibitors have been shown to reduce cardiovascular events but are currently not used as the first-line therapy. This study was conducted to evaluate the cost-effectiveness of first-line empagliflozin plus metformin versus metformin monotherapy among Australians with type 2 diabetes mellitus (T2DM) and existing cardiovascular disease (CVD).MethodsA Markov model with 1-year cycles and a 5-year time horizon was constructed to simulate the occurrence of recurrent cardiovascular events among Australians aged 50 to 84 years with T2DM and CVD. Efficacy results were derived from the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients-Removing Excess Glucose trial. Costs and utilities were drawn from published sources. The evaluation adopted both health care and societal perspectives, with the latter ascribing the Australian government’s “value of statistical life year” (A$213 000) to each year lived by a person. Future outcomes were discounted at 5% annually. Sensitivity analyses were conducted to enhance the robustness of conclusions.ResultsCompared with metformin monotherapy, first-line empagliflozin plus metformin reduced overall cardiovascular events by 0.82% and overall deaths by 7.72% over 5 years. There were 0.2 years of life saved per person and 0.16 quality-adjusted life years gained, at a net health care cost of A$4408. These equated to incremental cost-effectiveness ratios of A$22 076 per year of life saved and A$28 244 per quality-adjusted life year gained. The gains in the value of statistical life year equated to A$42 530 per person, meaning that from a societal perspective, the intervention was cost-saving.ConclusionFirst-line empagliflozin plus metformin may represent a cost-effective strategy for the management of T2DM and CVD in Australia.     

A Clinical Prediction Model to Distinguish Maturity-Onset Diabetes of the Young From Type 1 and Type 2 Diabetes in the Chinese Population

ObjectiveGenetic detection for the diagnosis of maturity-onset diabetes of the young (MODY) in China has low sensitivity and specificity. Better gene detection is urgently needed to distinguish testing subjects. We proposed to use numerous and weighted clinical traits as key indicators for reasonable genetic testing to predict the probability of MODY in the Chinese population.MethodsWe created a prediction model based on data from 306 patients, including 140 patients with MODY, 84 patients with type 1 diabetes (T1D), and 82 patients with type 2 diabetes (T2D). This model was evaluated using receiver operating characteristic curves.ResultsCompared with patients with T1D, patients with MODY had higher C-peptide levels and negative antibodies, and most patients with MODY had a family history of diabetes. Different from T2D, MODY was characterized by lower body mass index and younger diagnostic age. A clinical prediction model was established to define the comprehensive probability of MODY by a weighted consolidation of the most distinguishing features, and the model showed excellent discrimination (areas under the curve of 0.916 in MODY vs T1D and 0.942 in MODY vs T2D). Further, high-sensitivity C-reactive protein, glycated hemoglobin A1c, 2-h postprandial glucose, and triglyceride were used as indicators for glucokinase-MODY, while triglyceride, high-sensitivity C-reactive protein, and hepatocellular adenoma were used as indicators for hepatocyte nuclear factor 1-α MODY.ConclusionWe developed a practical prediction model that could predict the probability of MODY and provide information to identify glucokinase-MODY and hepatocyte nuclear factor 1-α MODY. These results provide an advanced and more reasonable process to identify the most appropriate patients for genetic testing.     

Binge-Eating Disorder and Type 2 Diabetes: A Review

ObjectiveTo familiarize health care providers with diagnosis and treatment of binge-eating disorder (BED), a common comorbidity of type 2 diabetes (T2DM).MethodsLiterature review of binge eating and T2DM. Key words used in search include BED, T2DM, obesity, and treatment.ResultsThe prevalence of BED in patients with T2DM appears to be much higher than the 2% to 3.5% prevalence seen in the general population. Studies suggest that up to 20% of patients with T2DM have an underlying eating disorder, the most common of which is binge eating. BED is probably underdiagnosed, even though there are multiple simple tools that providers can use to improve screening for the disorder. Though the relationship between BED and hemoglobin A1c control can vary, it appears that binge-eating behaviors can worsen metabolic markers, including glycemic control. Various medications used by patients with diabetes have been associated with new-onset BED, and treatment may be as simple as removing or replacing such agents. Several medications have been found to significantly reduce binge-eating frequency, and potentially, weight. Patients with BED generally benefit from psychotherapy, including cognitive behavioral therapy.ConclusionBED, only recently added to the International Classification of Disease-10 diagnostic list, is very common in patients with obesity and T2DM. The diagnosis is important to establish, as treatment or referral for treatment, could potentially improve many of the comorbidities and metrics of T2DM.     

Digital Health and Shared Decision-Making in Diabetes Care – A Survey Initiative in Patients and Clinicians

ObjectiveTo assess the landscape of digital health resources in the United States, better understand the impact of the digital health on shared decision-making, and identify potential barriers and opportunities for progress in the care of persons with diabetes.MethodsThe study consisted of two phases: A qualitative phase in which one-on-one interviews were conducted virtually with 34 physicians (endocrinologists {Endos}: n = 15; primary care physicians {PCPs}: n = 19) between February 11, 2021 and February 18, 2021, and a quantitative phase in which two online, email-based surveys in the English language were conducted between April 16, 2021 and May 17, 2021: one with healthcare professionals (HCP) (n = 403: n = 200 Endos and n = 203 PCPs), and one with persons with diabetes (n = 517: patients with type 1 diabetes, n = 257; patients with type 2 diabetes, n = 260).ResultsDiabetes digital health tools were found to be helpful in shared decision-making, but leading barriers include cost, coverage, and lack of time by healthcare professionals. Among diabetes digital health tools, continuous glucose monitoring (CGM) systems were used most commonly and viewed as most effective in improving quality of life and facilitating shared decision-making. Strategies for increasing use of diabetes digital health resources included lower cost, integration into electronic health records, and increased simplicity of tools.ConclusionThis study revealed that both Endos and PCPs feel that diabetes digital health tools have an overall positive impact. Integration with telemedicine and simpler, lower cost tools with increased patient access can further facilitate shared decision-making and improved diabetes care and quality of life.     

The Predictive Ability of C-Peptide in Distinguishing Type 1 Diabetes From Type 2 Diabetes: A Systematic Review and Meta-Analysis

ObjectiveThis systematic review and meta-analysis aimed to investigate the predictive ability of plasma connecting peptide (C-peptide) levels in discriminating type 1 diabetes (T1D) from type 2 diabetes (T2D) and to inform evidence-based guidelines in diabetes classification.MethodsWe conducted a holistic review and meta-analysis using PubMed, MEDLINE, EMBASE, and Scopus. The citations were screened from 1942 to 2021. The quality criteria and the preferred reporting items for systematic reviews and meta-analysis checklist were applied. The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42022355088).ResultsA total of 23,658 abstracts were screened and 46 full texts reviewed. Of the 46 articles screened, 12 articles were included for the meta-analysis. Included studies varied by race, age, time, and proportion of individuals. The main outcome measure in all studies was C-peptide levels. A significant association was reported between C-peptide levels and the classification and diagnosis of diabetes. Furthermore, lower concentrations and the cutoff of <0.20 nmol/L for fasting or random plasma C-peptide was indicative of T1D. In addition, this meta-analysis revealed the predictive ability of C-peptide levels in discriminating T1D from T2D. Results were consistent using both fixed- and random-effect models. The I² value (98.8%) affirmed the variability in effect estimates was due to heterogeneity rather than sampling error among all selected studies.ConclusionPlasma C-peptide levels are highly associated and predictive of the accurate classification and diagnosis of diabetes types. A plasma C-peptide cutoff of ≤0.20 mmol/L is indicative of T1D and of ≥0.30 mmol/L in the fasting or random state is indicative of T2D.     

SARS-CoV-2 Seroprevalence in Individuals With Type 1 and Type 2 Diabetes Compared With Controls

ObjectiveData for the association between diabetes and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) susceptibility are conflicting. We aimed to evaluate this association using an analytical cross-sectional study design.MethodsStudy participants were recruited from endocrine clinics of our hospital and belonged to 3 groups: group 1 (type 1 diabetes mellitus [T1DM]), group 2 (type 2 diabetes mellitus [T2DM]), and group 3 (controls). All participants submitted blood samples for SARS-CoV-2 S1/S2 immunoglobulin G antibody test (LIAISON; DiaSorin) and were interviewed for a history of documented infection.ResultsWe evaluated a total of 643 participants (T1DM, 149; T2DM, 160; control, 334; mean age, 37.9 ± 11.5 years). A total of 324 (50.4%) participants were seropositive for SARS-CoV-2. The seropositivity rate was significantly higher in the T1DM (55.7% vs 44.9%, P = .028) and T2DM (56.9% vs 44.9%, P = .013) groups than in the control group. The antibody levels in seropositive participants with T1DM and T2DM were not significantly different from those in seropositive controls. On multivariable analysis, low education status (odds ratio [OR], 1.41 [95% CI, 1.03-1.94]; P = .035), diabetes (OR, 1.68 [95% CI, 1.20-2.34]; P = .002), and overweight/obesity (OR, 1.52 [95% CI, 1.10-2.10]; P = .012) showed a significant association with SARS-CoV-2 seropositivity. The association between diabetes and SARS-CoV-2 seropositivity was found to further increase in participants with coexisting overweight/obesity (adjusted OR, 2.63 [95% CI, 1.54-4.47]; P < .001).ConclusionSARS-CoV-2 seropositivity, assessed before the onset of the national vaccination program, was significantly higher in participants with T1DM and T2DM than in controls. The antibody response did not differ between seropositive participants with and without diabetes. These findings point toward an increased SARS-CoV-2 susceptibility for patients with diabetes, in general, without any differential effect of the diabetes type.     

Duodenal Mucosa: A New Target for the Treatment of Type 2 Diabetes

ObjectiveAfter a high-fat and high-sugar diet, the duodenal mucosa of rodents proliferate and trigger the signal of insulin resistance, which may be the cause of type 2 diabetes (T2D). In response to this phenomenon, researchers have designed the duodenal mucosal resurfacing (DMR) procedure, mainly through the hydrothermal ablation procedure, to restore the normal mucosal surface, thereby correcting this abnormal metabolic signal. This article aims to understand the changes in duodenum before and after the onset or treatment of T2D, and the potential mechanisms of DMR procedure.MethodsA literature search of PubMed and Web of Science was conducted using appropriate keywords.ResultsBoth animal and clinical studies have shown that the villus thickness, intestinal cells, glucose transporters, enteric nerves, and gut microbiota and their metabolites in the duodenum undergo corresponding changes before and after the onset or treatment of T2D. These changes may be related to the pathogenesis of T2D. DMR procedure may produce beneficial glycemic and hepatic metabolic effects by regulating these changes.ConclusionThe duodenum is an important metabolic signaling center, and limiting nutrient exposure to this critical region will have powerful metabolic benefits. The DMR procedure may regulate glycemic and hepatic parameters through various mechanisms, which needs to be further confirmed by a large number of animal and clinical studies.     

Automated Insulin Delivery Systems as a Treatment for Type 2 Diabetes Mellitus: A Review

ObjectiveApproximately 6.3% of the worldwide population has type 2 diabetes mellitus (T2DM), and the number of people requiring insulin is increasing. Automated insulin delivery (AID) systems integrate continuous subcutaneous insulin infusion and continuous glucose monitoring with a predictive control algorithm to provide more physiologic glycemic control. Personalized glycemic targets are recommended in T2DM owing to the heterogeneity of the disease. Based on the success of hybrid closed-loop systems in improving glycemic control and safety in type 1 diabetes mellitus, there has been further interest in the use of these systems in people with T2DM.MethodsWe performed a review of AID systems with a focus on the T2DM population.ResultsIn 5 randomized controlled trials, AID systems improve time in range and reduce glycemic variability, without increasing insulin requirements or the risk of hypoglycemia.ConclusionAID systems in T2DM are safe and effective in hospitalized and closely monitored settings. Home studies of longer duration are required to assess for long-term benefit and identify target populations of benefit.     

Validation of Diagnostic Coding for Diabetes Mellitus in Hospitalized Patients

ObjectiveSome studies have shown that there is an undercoding of diabetes mellitus among hospitalized patients, which can have adverse clinical and financial implications for health systems. We aimed to validate the discharge diagnostic coding of diabetes mellitus in hospitalized patients using clinical and laboratory-based diagnostic indicators as the reference.MethodsThis was a retrospective cohort study of 83 690 discharges of 48 615 unique adult patients who were hospitalized in an academic medical center over 4.5 years and had at least 4 blood glucose measurements during admission. A missing diabetes code (MDC) was defined using 2 criteria. MDC₁ was defined as the presence of any of the following: blood glucose ≥200 (x2), A1C ≥6.5%, home antihyperglycemic medication, or preadmission code for diabetes, whereas MDC₂ was defined as preadmission diabetes or at least 2 other criteria in MDC₁. Multivariable logistic regression was used to identify factors associated with MDC compared to the present diabetes code.ResultsMDC₁ and MDC₂ were present in 12 186 (14.6%) and 3542 (4.7%) discharges, respectively. Factors associated with both MDC₁ and MDC₂ were medium-dose steroid use [adjusted odds ratio (aOR) 2.11, 2.01], high-dose steroid use (aOR 4.70, 2.50), intermediate medical care service (aOR 1.65, 1.55), infection (aOR 1.21, 1.34), and hepatic disease (aOR 1.93, 1.92).ConclusionIn this retrospective study, MDC ranged from 5% to 15% and was associated with various clinical factors. Further prospective studies are needed to validate these findings, explore the mechanisms behind these associations, and understand the clinical and financial implications.     

New Digital Health Technologies for Insulin Initiation and Optimization for People With Type 2 Diabetes

ObjectiveThe health and economic burden of type 2 diabetes is of global significance. Many people with type 2 diabetes eventually need insulin to help reduce their risk of serious associated complications. However, barriers to the initiation and/or optimization of insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigated how new and future technologies may provide opportunities to help overcome these barriers to the initiation and/or optimization of insulin.MethodsA focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support the initiation and/or optimization of insulin were identified by manually filtering >300 publications and conference abstracts.ResultsMost software tools have been developed for smartphone platforms. At present, published data suggest that the use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care, with additional benefits such as reduced time burden and improved knowledge of diabetes among health care providers. However, there remains paucity of good-quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin.ConclusionNew digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, and titration advice as well as records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve adherence to titration and treatment, resulting in better outcomes for people with diabetes.     

Postoperative Copeptin as a Biomarker for Development of Diabetes Insipidus Following Hypothalamic-Pituitary Surgery

ObjectiveCopeptin is a surrogate marker of arginine vasopressin release with better stability and simplicity of measurement. Postoperative copeptin levels may guide clinicians in stratifying patients who need close monitoring of fluid balance. The objective is to determine whether copeptin is a predictive marker of postoperative diabetes insipidus (DI).MethodsThis is a prospective diagnostic study. Patients who underwent neurosurgical intervention of the sellar-suprasellar regions were recruited. Serum copeptin levels were measured before and after surgery, within 24 hours. Logistic regression analysis and diagnostic performance measures were calculated to determine the relationship between postoperative copeptin levels and DI.ResultsOf 82 patients, 26 (31.7%) developed postoperative DI, with 7 patients (8.5%) having permanent DI. The samples for copeptin measurement were taken at 13 ± 2.1 hours postoperatively. From the receiver operating characteristic analysis, low postoperative copeptin levels (<2.5 pmol/L) demonstrated an acceptable ability to predict DI (area under the curve, 0.72; 95% CI, 0.60-0.84). Discriminative power was stronger in the permanent DI group (area under the curve, 0.82; 95% CI, 0.64-1.00). Postoperative copeptin levels <2.5 pmol/L were associated with DI (specificity > 91%). However, postoperative copeptin levels >20 pmol/L were rarely associated with DI, with a negative predictive value of 100%.ConclusionsIn patients undergoing sellar-suprasellar interventions, low postoperative copeptin levels within the first postoperative day predict postoperative DI, whereas high levels exclude it. Copeptin measurement should be applied in the clinical practice of postoperative care in patients following hypothalamic-pituitary surgery. This study may expand the potential use of copeptin, including in the Asian population.     

Ultra Rapid-Acting Inhaled Insulin Improves Glucose Control in Patients With Type 2 Diabetes Mellitus

ObjectiveTo determine whether the use of an inhaled insulin would improve HbA1c.MethodsThis study was performed in 20 type 2 diabetes mellitus (T2DM) participants with HbA1c values ≥7.5 (58) to ≤11.5% (102 mmol/mol) on a variety of glucose-lowering regimens. Prandial Technosphere insulin (TI) was rapidly titrated based on a treatment algorithm using postprandial blood glucose to calculate premeal doses. A 2-week baseline period was followed by 12 weeks of active treatment with TI. The primary outcome was change in HbA1c. Secondary outcomes included glucose time in range (time in range: 70-180 mg/dL) obtained by a blinded continuous glucose monitoring during the baseline period and at the end of 12 weeks. Goals were to assess how to rapidly and safely initiate TI intensification, determine dosing requirements, and establish an effective dose range in uncontrolled T2DM.ResultsMean HbA1c decreased by −1.6% (−17 mmol/mol) from 9.0% (75 mmol/mol) at baseline to 7.4% (57 mmol/mol) at 12 weeks (P < .0001). Mean time in range increased from 42.2% to 65.7% (P < .0002). Mean prandial doses of TI were 18 or 19 units for all meals. Time below range was 1.1% baseline and 2.6% post treatment (P = .01).ConclusionTreatment with inhaled TI dosed using a simple algorithm improved glycemic control measured by both HbA1c and time in range, with low rates of hypoglycemia. These data add significantly to understanding TI in the management of T2DM patients for whom prandial insulin is a consideration.     

Results of a 24-Week Trial of Technosphere Insulin Versus Insulin Aspart in Type 2 Diabetes

ObjectiveTo compare glycemic efficacy of Technosphere insulin (TI) versus that of insulin aspart (IA), each added to basal insulin, in type 2 diabetes.MethodsThis randomized, 24-week trial included subjects aged from 18 to 80 years who were treated with subcutaneous insulin for 3 months and had glycated hemoglobin (HbA1C) levels of 7.0% to 11.5%. After receiving stabilized insulin glargine doses during a 4-week lead in, the subjects were randomized to TI or IA. The primary end point was an HbA1C change from baseline, with the differences analyzed by equivalence analyses.ResultsIn the overall cohort (N = 309; males, 23.3%), mean (SD) age was 58.5 (8.4) years, body mass index was 30.8 (4.7) kg/m², weight was 82.2 (13.6) kg, and duration of diabetes was 12.2 (7.1) years. An intention-to-treat cohort had 150 subjects randomized to TI (mean [SD] HbA1C: 8.9% [1.1%]) and 154 randomized to IA (mean [SD] HbA1C: 9.0% [1.3%]). At 24 weeks, mean (SD) HbA1C value declined to 7.9% (1.3%) and 7.7% (1.1%) in the TI and IA cohorts, respectively. A treatment difference of 0.26% was not statistically significant, but the predefined equivalency margin was not met. Subjects receiving TI lost 0.78 kg compared to baseline; subjects receiving IA gained 0.23 kg (P =.0007). The incidence of mild/moderate hypoglycemia was lower for the TI cohort, though not statistically significant.ConclusionBoth TI and IA resulted in significant and clinically meaningful HbA1C reductions. TI also resulted in significant and clinically meaningful weight reductions. These data support the use of inhaled insulin as a treatment option for individuals with type 2 diabetes.     

Effectiveness of Wearable Activity Monitors on Metabolic Outcomes in Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis

ObjectiveWearable activity monitors are promising tools for improving metabolic outcomes in patients with type 2 diabetes mellitus (T2DM); however, no uniform conclusive evidence is available. This study aimed to evaluate the effects of the intervention using wearable activity monitors on blood glucose, blood pressure, blood lipid, weight, waist circumference, and body mass index (BMI) in individuals with T2DM.MethodsTwo independent reviewers searched 4 online databases (PubMed, Cochrane Library, Web of Science, and Embase) to identify relevant studies published from January 2000 to October 2022. The primary outcome indicator was hemoglobin A1c (HbA1c), and the secondary outcome indicators included physical activity (steps per day), fasting blood glucose, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, systolic blood pressure, diastolic blood pressure, BMI, waist circumference, and weight.ResultsA total of 25 studies were included. The HbA1c level (standardized mean difference [SMD], −0.14; 95% confidence interval [CI], −0.27 to −0.02; P = .02; I² = 48%), BMI (SMD, −0.16; 95% CI, −0.26 to −0.05; P = .002; I² = 0), waist circumference (SMD, −0.21; 95% CI, −0.34 to −0.09; P < .001; I² = 0), and steps/day (SMD, 0.55; 95% CI, 0.36-0.94; P < .001; I² = 77%) significantly improved.ConclusionWearable activity monitor–based interventions could facilitate the improvement of the HbA1c level, BMI, and waist circumference and increase in physical activity in individuals with T2DM. Wearable technology appeared to be an effective tool for the self-management of T2DM; however, there is insufficient evidence about its long-term effect.     

A Pilot Study of Youth With Type 1 Diabetes Initiating Use of a Hybrid Closed-Loop System While Receiving a Behavioral Economics Intervention

ObjectiveMany youth do not use the hybrid closed-loop system for type 1 diabetes effectively. This study evaluated the impact of financial incentives for diabetes-related tasks on use of the 670G hybrid closed-loop system and on glycemia.MethodsAt auto mode initiation and for 16 weeks thereafter, participants received a flat rate for wearing and calibrating the sensor ($1/day), administering at least 3 mealtime insulin boluses per day ($1/day), and uploading ($5/week). Weekly bonuses were given for maintaining at least 70% of the time in auto mode, which were increased for persistent auto mode use from $3/week to a maximum of $13/week. If a participant failed to maintain auto mode for a week, the rewards were reset to baseline. Data from 17 participants aged 15.9 years ± 2.5 years (baseline hemoglobin A1c [HbA1c] 8.6% ± 1.1%) were collected at 6, 12, and 16 weeks. The reinforcers were withdrawn at 16 weeks, with a follow-up assessment at 24 weeks.ResultsWith reinforcers, the participants administered an average of at least 3 mealtime insulin boluses per day and wore the sensor over 70% of the time. However, auto mode use waned. HbA1c levels decreased by 0.5% after 6 weeks, and this improvement was maintained at 12 and 16 weeks (P < .05). Upon withdrawal of reinforcers, HbA1c levels increased back to baseline at 24 weeks.ConclusionCompensation for diabetes-related tasks was associated with lower HbA1c levels, consistent administration of mealtime insulin boluses, and sustained sensor use. These results support the potential of financial rewards for improving outcomes in youth with type 1 diabetes.     

Nordic Walking Improves Cardiometabolic Parameters,Fitness Performance,and Quality of Life in Older Adults With Type 2 Diabetes

ObjectiveTo assess the effect of Nordic walking (NW) on cardiometabolic health, physical performance, and well-being in sedentary older adults with type 2 diabetes (T2D).MethodsFifteen subjects with T2D (female, 5; male, 10; age, 65 ± 6.2 years [mean ± standard deviation]; body mass index, 27.3 ± 4.9 kg/m² [mean ± standard deviation]) were enrolled in a 6-month NW training program. The fasting glucose and glycosylated hemoglobin levels, lipid profile (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides), systolic blood pressure (SBP), and diastolic blood pressures were measured before and after the intervention. Participants’ quality of life (Short-Form Health Survey) and physical fitness (6-minute walking test) were also evaluated.ResultsCompared with baseline, NW significantly improved the fasting glucose level (103.5 ± 18.5 vs 168.7 ± 37.7 mg/dL, P = .01), SBP (121.8 ± 12.2 vs 133 ± 14.4 mm Hg, P = .02), physical fitness (759.88 ± 69 vs 615.5 ± 62.6 m, P < .001), and both mental health (54.5 ± 4.4 vs 45.7 ± 5.6, P < .01) and physical health (49.8 ± 4.7 vs 40.3 ± 5.9, P < .01). The levels of glycosylated hemoglobin (6.15% ± 0.8% vs 6.4% ± 1%, P = .46), total cholesterol (162.2 ± 31.2 vs 175.5 ± 28.8 mg/dL, P = .13), low-density lipoprotein cholesterol (95.2 ± 24.2 vs 106.3 ± 32.3 mg/dL, P = .43), and triglycerides (135.5 ± 60.8 vs 127.6 ± 57.4 mg/dL, P = 0.26) improved without reaching significance.ConclusionNW training improved the glycemic levels, SBP, physical fitness, and perception of quality of life in older adults with T2D. NW represents a suitable complementary strategy to improve the global health status in this population.     

Comparison of New Glucose-Lowering Drugs on the Risk of Pancreatitis in Type 2 Diabetes: A Network Meta-Analysis

ObjectiveTo explore whether new glucose-lowering drugs increase the risk of pancreatitis in individuals with type 2 diabetes. This present network meta-analysis aimed to investigate the risk of pancreatitis associated with the use of glucagon-like peptide-1 (GLP-1) agonists and dipeptidyl peptidase-4 (DPP-4) inhibitors in the treatment of type 2 diabetes mellitus.MethodsPubMed, Web of Science, Embase, and the Cochrane Library were searched. The literature was published from the date of their inception to July 21, 2021, including placebo-controlled or head-to-head trials of 2 new glucose-lowering drugs. The relative ratio (RR) and 95% confidence interval (CI) were used to assess the risk of GLP-1 agonists and DPP-4 inhibitors for pancreatitis or pancreatic cancer among patients with type 2 diabetes.ResultsSeventeen studies were identified, covered 102 257 participants. The pooled results showed a neutral relationship between GLP-1 agonists and pancreatitis (overall RR, 0.96; 95% CI, 0.31-3.00) or pancreatic cancer (overall RR, 1.10; 95% CI, 0.31-4.10) compared with placebo. Meanwhile, DPP-4 inhibitors were not associated with the increased risk of pancreatitis (overall RR, 1.60; 95% CI, 0.25-11.00) or pancreatic cancer (overall RR, 0.79; 95% CI, 0.26-2.40). Among them, lixisenatide and saxagliptin may be the safest drugs compared with other drugs according to the ranking of probability. Sensitivity and subgroup analysis confirmed the stability of the core results.ConclusionThe most obvious finding of this study is that GLP-1 agonists and DPP-4 inhibitors are safe with respect to the risk of pancreatitis and pancreatic cancer compared with placebo. This conclusion may provide useful evidence for correlated clinical researches.