scholarly journals Low-cost exercise interventions improve long-term cardiometabolic health independently of a family history of type 2 diabetes: a randomized parallel group trial

2020 ◽  
Vol 8 (2) ◽  
pp. e001377
Author(s):  
Niko S Wasenius ◽  
Bo A Isomaa ◽  
Bjarne Östman ◽  
Johan Söderström ◽  
Björn Forsén ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Exercise Prescription ◽  
Low Cost ◽  
Density Lipoprotein ◽  
Cardiometabolic Health ◽  
Supervised Exercise ◽  
History Of

IntroductionTo investigate the effect of an exercise prescription and a 1-year supervised exercise intervention, and the modifying effect of the family history of type 2 diabetes (FH), on long-term cardiometabolic health.Research design and methodsFor this prospective randomized trial, we recruited non-diabetic participants with poor fitness (n=1072, 30–70 years). Participants were randomly assigned with stratification for FH either in the exercise prescription group (PG, n=144) or the supervised exercise group (EG, n=146) group and compared with a matched control group from the same population study (CON, n=782). The PG and EG received exercise prescriptions. In addition, the EG attended supervised exercise sessions two times a week for 60 min for 12 months. Cardiometabolic risk factors were measured at baseline, 1 year, 5 years, and 6 years. The CON group received no intervention and was measured at baseline and 6 years.ResultsThe EG reduced their body weight, waist circumference, diastolic blood pressure, and low-density lipoprotein-cholesterol (LDL-C) but not physical fitness (p=0.074) or insulin or glucose regulation (p>0.1) compared with the PG at 1 year and 5 years (p≤0.011). The observed differences were attenuated at 6 years; however, participants in the both intervention groups significantly improved their blood pressure, high-density lipoprotein-cholesterol, and insulin sensitivity compared with the population controls (p≤0.003). FH modified LDL-C and waist circumference responses to exercise at 1 year and 5 years.ConclusionsLow-cost physical activity programs have long-term beneficial effects on cardiometabolic health regardless of the FH of diabetes. Given the feasibility and low cost of these programs, they should be advocated to promote cardiometabolic health.Trial registration numberClinicalTrials.gov identifier NCT02131701.

scholarly journals Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-year Non-randomized Clinical Trial

2018 ◽  
Author(s):  
Shaminie J. Athinarayanan ◽  
Rebecca N. Adams ◽  
Sarah J. Hallberg ◽  
Amy L. McKenzie ◽  
Nasir H. Bhanpuri ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Medication Use ◽  
Controlled Study ◽  
Cardiometabolic Health ◽  
Diabetes Medication ◽  
Care Intervention

ABSTRACTOBJECTIVEStudies on long-term sustainability of low-carbohydrate approaches to treat diabetes are limited. We aim to assess the effects of a continuous care intervention (CCI) on retention, glycemic control, weight, body composition, cardiovascular, liver, kidney, thyroid, inflammatory markers, diabetes medication usage and disease outcomes at 2 years in adults with type 2 diabetes (T2D).RESEARCH DESIGN AND METHODSAn open label, non-randomized, controlled study with 262 and 87 participants with T2D were enrolled in the CCI and usual care (UC) groups, respectively.RESULTSSignificant changes from baseline to 2 years in the CCI group included: HbA1c (−12% from 7.7±0.1%); fasting glucose (−18% from 163.67±3.90 mg/dL); fasting insulin (−42% from 27.73±1.26 pmol L-1); weight (−10% from 114.56±0.60 kg); systolic blood pressure (−4% from 131.7±0.9 mmHg); diastolic blood pressure (−4% from 81.8±0.5 mmHg); triglycerides (−22% from 197.2±9.1 mg/dL); HDL-C (+19% from 41.8±0.9 mg/dL), and liver alanine transaminase (−21% from 29.16±0.97 U/L). Spine bone mineral density in the CCI group was unchanged. Glycemic control medication use (excluding metformin) among CCI participants declined (from 56.9% to 26.8%, P=1.3×10-11) including prescribed insulin (−62%) and sulfonylureas (−100%). The UC group had no significant changes in these parameters (except uric acid and anion gap) or diabetes medication use. There was also significant resolution of diabetes (reversal, 53.5%; remission, 17.6%) in the CCI group but not in UC. All the reported improvements had p-values <0.00012.CONCLUSIONSThe CCI sustained long-term beneficial effects on multiple clinical markers of diabetes and cardiometabolic health at 2 years while utilizing less medication. The intervention was also effective in the resolution of diabetes and visceral obesity, with no adverse effect on bone health.TRIAL REGISTRATIONClinicaltrials.govNCT02519309

1386-P: Long-Term Weight Change after Pregnancy and Type 2 Diabetes Risk in Women with a History of Gestational Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1386-P
Author(s):  
SYLVIA E. BADON ◽  
FEI XU ◽  
CHARLES QUESENBERRY ◽  
ASSIAMIRA FERRARA ◽  
MONIQUE M. HEDDERSON
Keyword(s):  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Weight Change ◽  
Diabetes Risk ◽  
History Of

scholarly journals Effect of tofogliflozin on arterial stiffness in patients with type 2 diabetes: prespecified sub-analysis of the prospective, randomized, open-label, parallel-group comparative UTOPIA trial

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Naoto Katakami ◽  
◽  
Tomoya Mita ◽  
Hidenori Yoshii ◽  
Toshihiko Shiraiwa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Conventional Treatment ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Open Label ◽  
Parallel Group ◽  
History Of

Abstract Background Tofogliflozin, an SGLT2 inhibitor, is associated with favorable metabolic effects, including improved glycemic control and serum lipid profile and decreased body weight, visceral adipose tissue, and blood pressure (BP). This study evaluated the effects of tofogliflozin on the brachial-ankle pulse wave velocity (baPWV) in patients with type 2 diabetes (T2DM) without a history of apparent cardiovascular disease. Methods The using tofogliflozin for possible better intervention against atherosclerosis for type 2 diabetes patients (UTOPIA) trial is a prospective, randomized, open-label, multicenter, parallel-group, comparative study. As one of the prespecified secondary outcomes, changes in baPWV over 104 weeks were evaluated in 154 individuals (80 in the tofogliflozin group and 74 in the conventional treatment group) who completed baPWV measurement at baseline. Results In a mixed-effects model, the progression in the right, left, and mean baPWV over 104 weeks was significantly attenuated with tofogliflozin compared to that with conventional treatment (– 109.3 [– 184.3, – 34.3] (mean change [95% CI] cm/s, p = 0.005; – 98.3 [– 172.6, – 24.1] cm/s, p = 0.010; – 104.7 [– 177.0, – 32.4] cm/s, p = 0.005, respectively). Similar findings were obtained even after adjusting the mixed-effects models for traditional cardiovascular risk factors, including body mass index (BMI), glycated hemoglobin (HbA1c), total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglyceride, systolic blood pressure (SBP), hypertension, smoking, and/or administration of drugs, including hypoglycemic agents, antihypertensive agents, statins, and anti-platelets, at baseline. The findings of the analysis of covariance (ANCOVA) models, which included the treatment group, baseline baPWV, and traditional cardiovascular risk factors, resembled those generated by the mixed-effects models. Conclusions Tofogliflozin significantly inhibited the increased baPWV in patients with T2DM without a history of apparent cardiovascular disease, suggesting that tofogliflozin suppressed the progression of arterial stiffness. Trial Registration UMIN000017607. Registered 18 May 2015. (https://www.umin.ac.jp/icdr/index.html)

Visit-to-visit blood pressure variability in patients with type 2 diabetes with and without previous history of cardiovascular disease

2020 ◽  
Vol 38 (9) ◽  
pp. 1737-1744
Author(s):  
Maria Grazia Radaelli ◽  
Stefano Ciardullo ◽  
Silvia Perra ◽  
Rosa Cannistraci ◽  
Eleonora Bianconi ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Blood Pressure Variability ◽  
Previous History ◽  
History Of

scholarly journals Lactation Duration and Long-term Risk for Incident Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus

Diabetes Care ◽  
2020 ◽  
Vol 43 (4) ◽  
pp. 793-798 ◽  
Author(s):  
Sylvia H. Ley ◽  
Jorge E. Chavarro ◽  
Mengying Li ◽  
Wei Bao ◽  
Stefanie N. Hinkle ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Incident Type ◽  
Incident Type 2 Diabetes ◽  
History Of ◽  
Lactation Duration

scholarly journals Effective Treatment Recommendations for Type 2 Diabetes Management Using Reinforcement Learning: Treatment Recommendation Model Development and Validation (Preprint)

2021 ◽  
Author(s):  
Xingzhi Sun ◽  
Yong Mong Bee ◽  
Shao Wei Lam ◽  
Zhuo Liu ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Reinforcement Learning ◽  
Blood Lipids ◽  
Diabetes Complications ◽  
Data Driven ◽  
Lipid Lowering ◽  
Treatment Recommendation

BACKGROUND Type 2 diabetes mellitus (T2DM) and its related complications represent a growing economic burden for many countries and health systems. Diabetes complications can be prevented through better disease control, but there is a large gap between the recommended treatment and the treatment that patients actually receive. The treatment of T2DM can be challenging because of different comprehensive therapeutic targets and individual variability of the patients, leading to the need for precise, personalized treatment. OBJECTIVE The aim of this study was to develop treatment recommendation models for T2DM based on deep reinforcement learning. A retrospective analysis was then performed to evaluate the reliability and effectiveness of the models. METHODS The data used in our study were collected from the Singapore Health Services Diabetes Registry, encompassing 189,520 patients with T2DM, including 6,407,958 outpatient visits from 2013 to 2018. The treatment recommendation model was built based on 80% of the dataset and its effectiveness was evaluated with the remaining 20% of data. Three treatment recommendation models were developed for antiglycemic, antihypertensive, and lipid-lowering treatments by combining a knowledge-driven model and a data-driven model. The knowledge-driven model, based on clinical guidelines and expert experiences, was first applied to select the candidate medications. The data-driven model, based on deep reinforcement learning, was used to rank the candidates according to the expected clinical outcomes. To evaluate the models, short-term outcomes were compared between the model-concordant treatments and the model-nonconcordant treatments with confounder adjustment by stratification, propensity score weighting, and multivariate regression. For long-term outcomes, model-concordant rates were included as independent variables to evaluate if the combined antiglycemic, antihypertensive, and lipid-lowering treatments had a positive impact on reduction of long-term complication occurrence or death at the patient level via multivariate logistic regression. RESULTS The test data consisted of 36,993 patients for evaluating the effectiveness of the three treatment recommendation models. In 43.3% of patient visits, the antiglycemic medications recommended by the model were concordant with the actual prescriptions of the physicians. The concordant rates for antihypertensive medications and lipid-lowering medications were 51.3% and 58.9%, respectively. The evaluation results also showed that model-concordant treatments were associated with better glycemic control (odds ratio [OR] 1.73, 95% CI 1.69-1.76), blood pressure control (OR 1.26, 95% CI, 1.23-1.29), and blood lipids control (OR 1.28, 95% CI 1.22-1.35). We also found that patients with more model-concordant treatments were associated with a lower risk of diabetes complications (including 3 macrovascular and 2 microvascular complications) and death, suggesting that the models have the potential of achieving better outcomes in the long term. CONCLUSIONS Comprehensive management by combining knowledge-driven and data-driven models has good potential to help physicians improve the clinical outcomes of patients with T2DM; achieving good control on blood glucose, blood pressure, and blood lipids; and reducing the risk of diabetes complications in the long term.

scholarly journals The Effect of Replacing Carbohydrate-based Breakfast Foods with Eggs on Cardiometabolic Risk Factors in Adults at Risk for Type 2 Diabetes (P08-045-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Kevin Maki ◽  
Orsolya Palacios ◽  
Mary Buggia ◽  
Mary Dicklin ◽  
Marjorie Bell ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
At Risk ◽  
Risk Factor ◽  
Insulin Sensitivity ◽  
Cardiometabolic Risk ◽  
Dietary Intervention ◽  
Density Lipoprotein ◽  
Cardiometabolic Health ◽  
Cardiometabolic Risk Factor

Abstract Objectives To assess the effect of breakfast egg intake, vs. energy-matched carbohydrate (CHO)-based foods, on insulin sensitivity and markers of cardiometabolic health in adults at-risk for type 2 diabetes. Methods Overweight or obese adults with prediabetes and/or metabolic syndrome were included in this randomized crossover study consisting of two 4-wk dietary intervention periods, separated by a ≥4 wk washout. During each intervention, subjects consumed study products containing either 2 eggs/d for 6 d/wk (12 eggs/wk) or energy-matched CHO-based foods for breakfast. Percent changes from baseline were assessed for insulin sensitivity; CHO metabolism; lipid metabolism, including lipoprotein lipids, subfactions and particle sizes; high-sensitivity C-reactive protein (hs-CRP); and blood pressures (BP). Results Overall, 30 subjects (11 male; 19 female) with mean age of 53.5 ± 1.9 y and body mass index (BMI) of 31.9 ± 0.7 kg/m2 provided evaluable data. Median low-density lipoprotein cholesterol (LDL-C) decreased by 6.0% from a baseline of 119 mg/dL after 4-wk intake of the CHO breakfast foods, which was larger than the 2.9% reduction during the egg condition (P = 0.023 between diets). Mean systolic blood pressure was reduced significantly more during the egg condition vs. the CHO condition (2.7% vs. 0.0%, respectively, P = 0.018) from a baseline value of 127 mmHg. None of the other cardiometabolic risk factor parameters showed significant differences in response between diet conditions. Conclusions Intake of 12 eggs/wk for breakfast, vs. energy matched CHO-based foods, did not adversely affect the cardiometabolic risk factor profile in men and women at risk for diabetes. Funding Sources American Egg Board/Egg Nutrition Center, Park Ridge, IL Supporting Tables, Images and/or Graphs

Long-term blood pressure variability, incidence of hypertension and changes in renal function in type 2 diabetes

2020 ◽  
Vol 38 (11) ◽  
pp. 2279-2286
Author(s):  
Francesca Viazzi ◽  
Elisa Russo ◽  
Antonio Mirijello ◽  
Paola Fioretto ◽  
Carlo Giorda ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Renal Function ◽  
Blood Pressure Variability

scholarly journals Individualised risk prediction model for new-onset, progression and regression of chronic kidney disease in a retrospective cohort of patients with type 2 diabetes under primary care in Hong Kong

BMJ Open ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. e035308
Author(s):  
Lin Yang ◽  
Tsun Kit Chu ◽  
Jinxiao Lian ◽  
Cheuk Wai Lo ◽  
Shi Zhao ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Primary Care ◽  
Retrospective Cohort ◽  
Density Lipoprotein ◽  
Test Results ◽  
Health Records ◽  
Laboratory Test Results ◽  
New Onset

ObjectivesThis study is aimed to develop and validate a prediction model for multistate transitions across different stages of chronic kidney disease (CKD) in patients with type 2 diabetes mellitus under primary care.SettingWe retrieved the anonymised electronic health records of a population-based retrospective cohort in Hong Kong.ParticipantsA total of 26 197 patients were included in the analysis.Primary and secondary outcome measuresThe new-onset, progression and regression of CKD were defined by the transitions of four stages that were classified by combining glomerular filtration rate and urine albumin-to-creatinine ratio. We applied a multiscale multistate Poisson regression model to estimate the rates of the stage transitions by integrating the baseline demographic characteristics, routine laboratory test results and clinical data from electronic health records.ResultsDuring the mean follow-up time of 1.8 years, there were 2632 patients newly diagnosed with CKD, 1746 progressed to the next stage and 1971 regressed into an earlier stage. The models achieved the best performance in predicting the new-onset and progression with the predictors of sex, age, body mass index, systolic blood pressure, diastolic blood pressure, serum creatinine, haemoglobin A1c, total cholesterol, low-density lipoprotein, high-density lipoprotein, triglycerides and drug prescriptions.ConclusionsThis study demonstrated that individual risks of new-onset and progression of CKD can be predicted from the routine physical and laboratory test results. The individualised prediction curves developed from this study could potentially be applied to routine clinical practices, to facilitate clinical decision making, risk communications with patients and early interventions.

Sign in / Sign up

Export Citation Format

Share Document