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A systematic review and meta-analysis of interventions to preserve insulin-secreting β-cell function in people newly diagnosed with type 1 diabetes: Results from intervention studies aimed at improving glucose control.
Narendran, P, Tomlinson, C, Beese, S, Sharma, P, Harris, I, Adriano, A, Maggs, F, Burrows, M, Nirantharakumar, K, Thomas, N, et al
Diabetic medicine : a journal of the British Diabetic Association. 2022;(1):e14730
Abstract
AIMS: Type 1 diabetes is characterised by the destruction of pancreatic β-cells. Significant levels of β-cells remain at diagnosis. Preserving these cells improves glucose control and protects from long-term complications. We undertook a systematic review and meta-analyses of all randomised controlled trials (RCTs) of interventions to preserve β-cell function in people newly diagnosed with type 1 diabetes. This paper reports the results of interventions for improving glucose control to assess whether they preserve β-cell function. METHODS Searches for RCTs in MEDLINE, Embase, Cochrane CENTRAL, ClinicalTrials.gov and WHO International Clinical Trials Registry. Eligible studies included newly diagnosed patients with type 1 diabetes, any intervention to improve glucose control and at least 1 month of follow-up. Data were extracted using a pre-defined data-extraction sheet with 10% of extractions checked by a second reviewer. RESULTS Twenty-eight studies with 1662 participants were grouped by intervention into six subgroups (alternative insulins, subcutaneous and intravenous insulin delivery, intensive therapy, glucose sensing, adjuncts). Only three studies demonstrated an improvement in glucose control as well as β-cell function. These interventions included intensive insulin therapy and use of an alternative insulin. CONCLUSIONS This is the largest comprehensive review of RCTs in this area. It demonstrates a lack of robust evidence that interventions to improve glucose control preserve β-cell function in new onset type 1 diabetes, although analysis was hampered by low-quality evidence and inconsistent reporting of studies. Development of guidelines to support the design of trials in this field is a priority.
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Temporal Associations Among Body Mass Index, Fasting Insulin, and Systemic Inflammation: A Systematic Review and Meta-analysis.
Wiebe, N, Ye, F, Crumley, ET, Bello, A, Stenvinkel, P, Tonelli, M
JAMA network open. 2021;(3):e211263
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IMPORTANCE Obesity is associated with a number of noncommunicable chronic diseases and is purported to cause premature death. OBJECTIVE To summarize evidence on the temporality of the association between higher body mass index (BMI) and 2 potential mediators: chronic inflammation and hyperinsulinemia. DATA SOURCES MEDLINE (1946 to August 20, 2019) and Embase (from 1974 to August 19, 2019) were searched, although only studies published in 2018 were included because of a high volume of results. The data analysis was conducted between January 2020 and October 2020. STUDY SELECTION AND MEASURES Longitudinal studies and randomized clinical trials that measured fasting insulin level and/or an inflammation marker and BMI with at least 3 commensurate time points were selected. DATA EXTRACTION AND SYNTHESIS Slopes of these markers were calculated between time points and standardized. Standardized slopes were meta-regressed in later periods (period 2) with standardized slopes in earlier periods (period 1). Evidence-based items potentially indicating risk of bias were assessed. RESULTS Of 1865 records, 60 eligible studies with 112 cohorts of 5603 participants were identified. Most standardized slopes were negative, meaning that participants in most studies experienced decreases in BMI, fasting insulin level, and C-reactive protein level. The association between period 1 fasting insulin level and period 2 BMI was positive and significant (β = 0.26; 95% CI, 0.13-0.38; I2 = 79%): for every unit of SD change in period 1 insulin level, there was an ensuing associated change in 0.26 units of SD in period 2 BMI. The association of period 1 fasting insulin level with period 2 BMI remained significant when period 1 C-reactive protein level was added to the model (β = 0.57; 95% CI, 0.27-0.86). In this bivariable model, period 1 C-reactive protein level was not significantly associated with period 2 BMI (β = -0.07; 95% CI, -0.42 to 0.29; I2 = 81%). CONCLUSIONS AND RELEVANCE In this meta-analysis, the finding of temporal sequencing (in which changes in fasting insulin level precede changes in weight) is not consistent with the assertion that obesity causes noncommunicable chronic diseases and premature death by increasing levels of fasting insulin.
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Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: A Meta-analysis.
Mattioni Maturana, F, Martus, P, Zipfel, S, NIEß, AM
Medicine and science in sports and exercise. 2021;(3):559-573
Abstract
PURPOSE We aimed to investigate differences between high-intensity interval exercise (HIIE, including high-intensity interval training and sprint interval training) and moderate-intensity continuous training (MICT) on physical fitness, body composition, blood pressure, blood lipids, insulin and glucose metabolism, inflammation, and endothelial function. METHODS Differences between HIIE and MICT were summarized using a random-effects meta-analysis on the effect size (Cohen's d). A meta-regression was conducted using the following subgroups: population, age, training duration, men ratio, exercise type, baseline values (clinical relevant ranges), and type of HIIE. Studies were included if at least one of the following outcomes were reported: maximal oxygen uptake (V˙O2max), flow-mediated dilation (FMD), body mass index (BMI), body mass, percent body fat, systolic and diastolic blood pressure, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides, total cholesterol, C-reactive protein (CRP), fasting glucose and insulin, glycated hemoglobin (HbA1c), and insulin resistance (HOMA-IR). A total of 55 studies were included. RESULTS Overall, HIIE was superior to MICT in improving V˙O2max (d = 0.40, P < 0.001) and FMD (d = 0.54, P < 0.05). Oppositely, MICT was superior to HIIE in improving HbA1c (d = -0.27, P < 0.05). No differences were observed in BMI (d = -0.02), body mass (d = -0.05), percent body fat (d = 0.04), systolic blood pressure (d = -0.04), diastolic blood pressure (d = 0.03), HDL (d = -0.05), LDL (d = 0.08), triglycerides (d = 0.03), total cholesterol (d = 0.14), CRP (d = -0.11), fasting insulin (d = 0.02), fasting glucose (d = 0.02), and HOMA-IR (d = -0.04). Moderator analyses indicated that the difference between HIIE and MICT was affected by different subgroups. CONCLUSION Overall, HIIE showed to be more effective in improving cardiovascular health and cardiorespiratory fitness, whereas MICT was superior in improving long-term glucose metabolism. In the process of personalized training counseling, health-enhancing effects of exercise training may be improved by considering the individual risk profiles.
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Effects of Melatonin Supplementation on Insulin Levels and Insulin Resistance: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.
Li, Y, Xu, Z
Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme. 2021;(9):616-624
Abstract
Insulin resistance (IR) is a pivotal process in various metabolic diseases. The well-known treatment is lifestyle modification and medication therapy, which may result in poor compliance and side effects. Melatonin has been suggested to have a role in glucose metabolism, yet the results across studies have been inconsistent. Therefore, we performed a systematic review to evaluate the effects of melatonin supplementation on insulin levels and IR. We searched PubMed, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov, and identified randomized controlled trials (RCTs) published prior to August 2020. Articles were reviewed, selected and extracted by two reviewers independently. In total, 8 RCTs of 376 participants were included. Data were pooled using a random-effects model, with mean differences (MDs) and 95% confidence intervals (CIs). Our results showed that melatonin administration significantly reduced insulin levels and homeostasis model assessment of insulin resistance (HOMA-IR), and increased the quantitative insulin sensitivity check index (QUICKI). We conclude that melatonin ameliorated hyperinsulinemia, insulin resistance, and insulin sensitivity, and the results are an update of a previous meta-analysis. Although more investigations are required, we clearly provide evidence for the use of melatonin as an adjuvant treatment for metabolic disorders involving IR.
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Effects of interrupting prolonged sitting on postprandial glycemia and insulin responses: A network meta-analysis.
Quan, M, Xun, P, Wu, H, Wang, J, Cheng, W, Cao, M, Zhou, T, Huang, T, Gao, Z, Chen, P
Journal of sport and health science. 2021;(4):419-429
Abstract
PURPOSE This study aimed to evaluate the effectiveness of physical activity (PA) interrupting prolonged sitting (PS) on postprandial glycemia and insulin responses among adults. METHODS PubMed, EMBASE, Cochrane Library, Web of Science, CINAHL, PsycINFO, and the China National Knowledge Infrastructure databases were searched through September 30, 2020. Randomized controlled trials (RCTs) that examined the effect of all forms of PA interrupting PS on postprandial glycemia and/or insulin responses among adults without chronic diseases were included in this study. The risk of bias of included studies was evaluated based on the Cochrane tool. A network meta-analysis was performed to estimate the summary standardized mean differences (SMDs) with 95% confidence intervals (95%CIs) with random effects. RESULTS Thirty crossover RCTs were included in our review. These RCTs included 9 types of interventions that interrupted PS. When compared to PS by itself, light-intensity PA intermittent interrupting (LPA-INT) PS and moderate-intensity PA intermittent interrupting (MPA-INT) PS significantly lowered postprandial glycemia (SMD = -0.46, 95%CI: -0.70 to -0.21; SMD = -0.69, 95%CI: -1.00 to -0.37, respectively) and significantly reduced postprandial insulin response (SMD = -0.46, 95%CI: -0.66 to -0.26; SMD = -0.47, 95%CI: -0.77 to -0.17, respectively). Results of the clustered ranking plot indicated that MPA-INT was the most effective intervention in lowering postprandial glycemia and insulin responses. CONCLUSION Replacing PS with MPA-INT or LPA-INT has a positive effect in reducing postprandial glycemia and insulin responses, with MPA-INT being the optimal intervention strategy.
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Effects of alpha-glucosidase-inhibiting drugs on acute postprandial glucose and insulin responses: a systematic review and meta-analysis.
Alssema, M, Ruijgrok, C, Blaak, EE, Egli, L, Dussort, P, Vinoy, S, Dekker, JM, Denise Robertson, M
Nutrition & diabetes. 2021;(1):11
Abstract
BACKGROUND/OBJECTIVES Despite considerable literature supporting the potential health benefits of reducing postprandial glucose (PPG), and insulin (PPI) exposures, the size of a clinically relevant reduction is currently unknown. We performed a systematic review and meta-analysis to quantify effects of alpha-glucosidase-inhibiting (AGI) drugs on acute PPG and PPI responses. METHODS We searched EMBASE and MEDLINE until March 13, 2018 for controlled studies using AGI drugs together with a standardized carbohydrate load or mixed meal. The mean incremental PPG and PPI levels were calculated as outcomes. Meta-analyses, stratified by diabetes state, were performed by using random effects models. RESULTS The 66 included publications comprised 127 drug-control comparisons for PPG, and 106 for PPI, mostly testing acarbose or miglitol. The absolute effects on PPG were larger among individuals with diabetes (-1.5 mmol/l mean PPG [95% CI -1.9, -1.1] by acarbose, and -1.6 [-1.9, -1.4] by miglitol) as compared to individuals without diabetes (-0.4 [95% CI -0.5, -0.3] by acarbose, and -0.6 [-0.8, -0.4] by miglitol). Relative reductions in PPG by both drugs were similar for diabetic and non-diabetic individuals (43-54%). Acarbose and miglitol also significantly reduced mean PPI, with absolute and relative reductions being largest among individuals without diabetes. CONCLUSIONS The present meta-analyses provide quantitative estimates of reductions of PPG and PPI responses by AGI drugs in diabetes and non-diabetic individuals. These data can serve as benchmarks for clinically relevant reductions in PPG and PPI via drug or diet and lifestyle interventions.
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High prevalence of thyroid carcinoma in patients with insulin resistance: a meta-analysis of case-control studies.
Zhao, J, Zhang, Q, Yang, Y, Yao, J, Liao, L, Dong, J
Aging. 2021;(18):22232-22241
Abstract
The association between insulin resistance and thyroid carcinoma is controversial. We conducted this meta-analysis of association between insulin resistance and thyroid carcinoma. There were 14 studies included in this meta-analysis. Random-effect model was used to merge the weighted mean difference value of fasting serum insulin level and the pooled effect shows that the level of fasting serum insulin is higher in patients with thyroid carcinoma than those of controls (1.88, 95% CI 0.87 to 2.90, P=0.0003). Random-effect model was used to estimate the pooled weighted mean difference and it shows that thyroid carcinoma patients have a higher level of homeostasis model assessment of insulin resistance (HOMA-IR) than patients without thyroid carcinoma (0.54, 95% CI 0.29 to 0.78, P<0.0001). Fixed-effect model with the odds ratio of insulin resistance shows that insulin resistance could increase the risk of thyroid carcinoma 216% compared with participants without insulin resistance (3.16, 95% CI 2.09 to 4.77, P<0.0001). In conclusion, insulin resistance might be a risk factor for thyroid carcinoma.
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Insulin strategies for dietary fat and protein in type 1 diabetes: A systematic review.
Smith, TA, Marlow, AA, King, BR, Smart, CE
Diabetic medicine : a journal of the British Diabetic Association. 2021;(11):e14641
Abstract
AIM: To identify and report the efficacy of insulin strategies used to manage glycaemia following fat and/or fat and protein meals in type 1 diabetes. METHODS A systematic literature search of medical databases from 1995 to 2021 was undertaken. Inclusion criteria were randomised controlled trials that reported at least one of the following glycaemic outcomes: mean glucose, area under the curve, time in range or hypoglycaemic episodes. RESULTS Eighteen studies were included. Thirteen studies gave additional insulin. Five studies gave an additional 30%-43% of the insulin-to-carbohydrate ratio (ICR) for 32-50 g of fat and 31%-51% ICR for 7-35 g of fat with 12-27 g of protein added to control meals. A further eight studies gave -28% to +75% ICR using algorithms based on fat and protein for meals with 19-50 g of carbohydrate, 2-79 g of fat and 10-60 g of protein, only one study reported a glycaemic benefit of giving less than an additional 24% ICR. Eight studies evaluated insulin delivery patterns. Four of six studies in pump therapy, and one of two studies in multiple daily injections showed the combination of bolus and split dose, respectively, were superior. Five studies examined the insulin dose split, four demonstrated 60%-125% ICR upfront was necessary. Two studies investigated the timing of insulin delivery, both reported administration 15 min before the meal lowered postprandial glycaemia. CONCLUSIONS Findings highlight the glycaemic benefit of an additional 24%-75% ICR for fat and fat and protein meals. For these meals, there is supportive evidence for insulin delivery in a combination bolus with a minimum upfront dose of 60% ICR, 15 min before the meal.
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Sodium-glucose co-transporter inhibitors in insulin-treated diabetes: a meta-analysis.
Ferreira, JP, Oliveira, AC, Saraiva, FA, Vasques-Nóvoa, F, Leite-Moreira, A
European journal of endocrinology. 2021;(6):783-790
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BACKGROUND Patients with insulin-treated type 2 diabetes (T2D) have a high risk of major adverse cardiovascular events. Sodium-glucose cotransporter inhibitors (SGLTi) improve outcomes without hypoglycaemic risk. AIMS To study the effect of SGLTi in patients with T2D with and without background insulin treatment in outcome-driven RCTs. METHODS Random effects models. RESULTS A total of 54 374 patients with T2D were included in the analysis, of which 26 551 (48.8%) were treated with insulin. For 3P-MACE in patients without insulin treatment, the HR (95% CI) for the effect of SGLTi vs placebo was 0.93 (0.81-1.05), with moderate heterogeneity (I2 = 49.2%, Q statistic P = 0.11). In insulin-treated patients, the HR (95% CI) was 0.88 (0.82-0.95), without evidence of heterogeneity (I2 =0.0%, Q statistic P =0.91). The pooled effect evidenced a 10% reduction of 3P-MACE with SGLTi (HR: 0.90, 95% CI: 0.85-0.96), without SGLTi-by-insulin interaction P = 0.53. For the composite outcome of HF hospitalisation or cardiovascular death in patients without insulin treatment, the HR (95% CI) for the effect of SGLTi vs placebo was 0.77 (0.61-0.92), with marked heterogeneity (I2 = 66.8%, Q statistic P = 0.02). In insulin-treated patients, the HR (95% CI) was 0.77 (0.68-0.86), without significant heterogeneity (I2 = 31.7%, Q statistic P = 0.25). The pooled effect evidenced a 23% reduction of HF hospitalisations or cardiovascular death with SGLTi (HR: 0.77, 95% CI: 0.68-0.85), without SGLTi-by-insulin interaction P = 0.98. CONCLUSION SGLTi reduces cardiovascular events regardless of insulin use. However, the treatment effect is more homogeneous among insulin-treated patients, supporting the use of SGLTi for the treatment of patients with T2D requiring insulin for glycaemic control.
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Predictors of the Acute Postprandial Response to Breaking Up Prolonged Sitting.
Henson, J, Edwardson, CL, Celis-Morales, CA, Davies, MJ, Dunstan, DW, Esliger, DW, Gill, JMR, Kazi, A, Khunti, K, King, J, et al
Medicine and science in sports and exercise. 2020;(6):1385-1393
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PURPOSE To identify predictors of favorable changes to postprandial insulin and glucose levels in response to interrupting prolonged sitting time with standing or light-intensity physical activity. METHODS Data were combined from four similarly designed randomized acute cross-over trials (n = 129; body mass index [BMI] range, 19.6-44.6 kg·m; South Asian = 31.0%; dysglycemia = 27.1%). Treatments included: prolonged sitting (6.5 h) or prolonged sitting broken-up with either standing or light-intensity physical activity (5 min every 30 min). Time-averaged postprandial responses for insulin and glucose were calculated for each treatment (mean ± 95% confidence interval). Mutually adjusted interaction terms were used to examine whether anthropometric (BMI), demographic (age, sex, ethnicity [white European vs South Asian]) and a cardiometabolic variable (Homeostatic Model Assessment of Insulin Resistance)-modified responses. RESULTS Postprandial insulin and glucose were reduced when individuals interrupted prolonged sitting with bouts of light physical activity, but not with standing. Reductions in time-averaged postprandial insulin were more pronounced if individuals were South Asian compared with white European (-18.9 mU·L [-23.5%] vs -8.2 mU·L [-9.3%]), female compared with male (-15.0 mU·L [-21.2%] vs -12.1 mU·L [-17.6%]) or had a BMI ≥27.2 kg·m (-20.9 mU·L [-22.9%] vs -8.7 mU·L [-18.2%]). Similarly, being female (-0.4 mmol·L [-0.6 mmol·L, -0.2 mmol·L], -6.8% vs -0.1 mmol·L [-0.3 mmol·L, 1 mmol·L], -1.7%) or having a BMI ≥27.2 kg·m (-0.4 mmol·L [-0.6 mmol·L, -0.2 mmol·L], -6.7% vs -0.2 mmol·L [-0.4 mmol·L, 0.0 mmol·L], -3.4%) modified the postprandial glucose response. No significant interactions were found for Homeostatic Model Assessment of Insulin Resistance or age. CONCLUSIONS Being female, South Asian, or having a higher BMI, all predicted greater reductions in postprandial insulin, whereas being female and having a higher BMI predicted greater reductions in postprandial glucose when sitting was interrupted with light physical activity. These results could help to guide personalized interventions in high-risk participants for whom breaking prolonged sitting time with light activity may yield the greatest therapeutic potential.