AACE/ACE Comprehensive Diabetes Management Algorithm 2015
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Due to growing environmental and economic constraints, countries are exploring renewable sources such as wind, solar, and fuel cells to save energy, and develop the use of dispersed generations. Thus, the use of electric vehicles (EVs) is on the rise. On a large scale, either of these technologies can have damaging effects on the electricity grid; however, with suitable consumption-side management and programming, technologies and energy storage resources can reduce these effects. Thus, energy management optimization has become an interesting topic of research. Accordingly, the effect of the integrated aggregation of PEVs to the grid for the charge/discharge process and the resulting grid instability, especially at load peak time, is the main challenge to the use of these vehicles. The contribution of this paper includes the presentation of a model for managing the coordinated and uncoordinated charging system of grid-connected EVs with wind power and photovoltaic power units as dispersed generation sources and dividing the EVs into 4 classes by considering the share of each in the grid and considering a random number of vehicles per class using the normal distribution function and implementing the incoordination in wind speed and solar irradiation. The proposed model uses a novel Reinforcement Learning (RL) based onDeep Q Network (DQN) algorithm to solve the multi-objective problem. In this model, the costs of annual energy losses and the operation of dispersed generation units are discussed in an integrated manner as the objective function. The simulation is performed on a 57-bus IEEE grid and the results show the efficiency and improved performance of the model.
American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan—2022 Update
2022, Endocrine PracticeThe objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.
The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.
This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.
This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.
Metformin-induced reductions in tumor growth involves modulation of the gut microbiome
2022, Molecular MetabolismType 2 diabetes and obesity increase the risk of developing colorectal cancer. Metformin may reduce colorectal cancer but the mechanisms mediating this effect remain unclear. In mice and humans, a high-fat diet (HFD), obesity and metformin are known to alter the gut microbiome but whether this is important for influencing tumor growth is not known.
Mice with syngeneic MC38 colon adenocarcinomas were treated with metformin or feces obtained from control or metformin treated mice.
We find that compared to chow-fed controls, tumor growth is increased when mice are fed a HFD and that this acceleration of tumor growth can be partially recapitulated through transfer of the fecal microbiome or in vitro treatment of cells with fecal filtrates from HFD-fed animals. Treatment of HFD-fed mice with orally ingested, but not intraperitoneally injected, metformin suppresses tumor growth and increases the expression of short-chain fatty acid (SCFA)-producing microbes Alistipes, Lachnospiraceae and Ruminococcaceae. The transfer of the gut microbiome from mice treated orally with metformin to drug naïve, conventionalized HFD-fed mice increases circulating propionate and butyrate, reduces tumor proliferation, and suppresses the expression of sterol response element binding protein (SREBP) gene targets in the tumor.
These data indicate that in obese mice fed a HFD, metformin reduces tumor burden through changes in the gut microbiome.
Glycaemic control of Asian patients with type-2 diabetes mellitus on tiered up-titration of metformin monotherapy: A one-year real-world retrospective longitudinal study in primary care
2022, Diabetes Research and Clinical PracticeTo determine the glycaemic control and associated factors among patients with type-2 diabetes mellitus on tiered metformin monotherapy over one-year.
Adult Asian patients on metformin monotherapy with tiered dosage up-titration (low < 500 mg/day; medium 500–<1000 mg/day and high ≥ 1000 mg/day) are divided into four sub-cohorts based on their baseline HbA1c < 7%(C<7); 7%–<8%(C7-<8); 8%–<9%(C8-<9) and ≥ 9%(C≥9). The HbA1c absolute reduction, time to reach glycaemic control (HbA1c < 7%), and time from glycaemic control to failure (HbA1c ≥ 7%) after the dosage up-titration were the outcomes.
Among 5503 eligible patients (mean age = 64.9 years, 45.6% males and 74.6% Chinese), the HbA1c absolute reduction after the up-titration at three months are 0%, 0.4%–0.6%, 0.8%–1.2% and 2.0%–2.1% for C<7, C7-<8, C8-<9 and C≥9 respectively. The median time (months) to attain glycaemic control for low, medium and high dosage up-titration were 4, 3, 3(C7-<8); 12, 7, 4(C8-<9); NA, 7, 7(C≥9). Within twelve months after the goal attainment, 36.2%(C<7), 48.8%(C7-<8), 52.7%(C8-<9) and 45.3%(C≥9) of patients had treatment failure.
The results show that the baseline HbA1c and tiered metformin dosage up-titration are associated with disproportionate HbA1c reduction, time to glycaemic control and time from glycaemic control to failure.
Ultra Rapid-Acting Inhaled Insulin Improves Glucose Control in Patients With Type 2 Diabetes Mellitus
2021, Endocrine PracticeTo determine whether the use of an inhaled insulin would improve HbA1c.
This 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.
Mean 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).
Treatment 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.
Study protocol for assessing the user acceptance, safety and efficacy of a tablet-based workflow and decision support system with incorporated basal insulin algorithm for glycaemic management in participants with type 2 diabetes receiving home health care: A single-centre, open-label, uncontrolled proof-of-concept study
2020, Contemporary Clinical Trials CommunicationsDiabetes management can be especially complex for older adults who receive health care at home. Thus, international guidelines recommend basal-insulin regimens due to simpler handling and low hypoglycaemia risk. A basal-insulin algorithm (including basal-plus) was developed to also include participant's health status and subsequently implemented into a tablet-based workflow and decision support system, GlucoTab@MobileCare. This study protocol describes a proof-of-concept study to investigate user acceptance, safety and efficacy of the GlucoTab@MobileCare system in participants receiving home health care.
The open-label, single-centre, uncontrolled study will recruit a maximum of ten participants with insulin treated type-2-diabetes (age ≥18 years) who receive home health care. During a three month study period participants will receive basal- or basal-plus-insulin therapy once daily as suggested by the GlucoTab@MobileCare system. Statistical analysis will be conducted on an intention-to-treat basis. The primary endpoint is the percentage of tasks (BG measurements, insulin dose calculations, insulin injections) that were performed according to GlucoTab@MobileCare suggestions relative to the total of suggested tasks. Secondary endpoints include user acceptance, safety and efficacy parameters. The study was approved by the ethics committee and regulatory authorities. Before obtaining written informed consent, all participants will receive oral and written information about all aspects of the study. Results will be published in a peer-reviewed journal and at diabetes and geriatric conferences.
Potential implications may be improved quality and safety of basal-insulin therapy in older adults as well as support for health-care-providers in daily routine including evidence-based knowledge.
German Clinical Trials Register (DRKS00015059);