scholarly journals Noninvasive Prototype for Type 2 Diabetes Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Javier Ferney Castillo García ◽  
Jesús Hamilton Ortiz ◽  
Osamah Ibrahim Khalaf ◽  
Adrián David Valencia Hernández ◽  
Luis Carlos Rodríguez Timaná
Keyword(s):  
Type 2 Diabetes ◽  
Learning Algorithm ◽  
Low Cost ◽  
Statistical Significance ◽  
Predictive Capacity ◽  
Screening Process ◽  
Electrical Bioimpedance ◽  
Artificial Learning ◽  
Learning Machine

The present work demonstrates the design and implementation of a human-safe, portable, noninvasive device capable of predicting type 2 diabetes, using electrical bioimpedance and biometric features to train an artificial learning machine using an active learning algorithm based on population selection. In addition, there is an API with a graphical interface that allows the prediction and storage of data when the characteristics of the person are sent. The results obtained show an accuracy higher than 90% with statistical significance ( p  < 0.05). The Kappa coefficient values were higher than 0.9, showing that the device has a good predictive capacity which would allow the screening process of type 2 diabetes. This development contributes to preventive medicine and makes it possible to determine at a low cost, comfortably, without medical preparation, and in less than 2 minutes whether a person has type 2 diabetes.

Metformin: Up to Date

2020 ◽  
Vol 20 (2) ◽  
pp. 172-181 ◽  
Author(s):  
Silvia Sciannimanico ◽  
Franco Grimaldi ◽  
Fabio Vescini ◽  
Giovanni De Pergola ◽  
Massimo Iacoviello ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Current Literature ◽  
Weight Control ◽  
Low Cost ◽  
Hepatic Glucose Production ◽  
Metabolic Effects ◽  
Hypoglycemic Agents ◽  
Positive Effects ◽  
Mesh Terms

Background: Metformin is an oral hypoglycemic agent extensively used as first-line therapy for type 2 diabetes. It improves hyperglycemia by suppressing hepatic glucose production and increasing glucose uptake in muscles. Metformin improves insulin sensitivity and shows a beneficial effect on weight control. Besides its metabolic positive effects, Metformin has direct effects on inflammation and can have immunomodulatory and antineoplastic properties. Aim: The aim of this narrative review was to summarize the up-to-date evidence from the current literature about the metabolic and non-metabolic effects of Metformin. Methods: We reviewed the current literature dealing with different effects and properties of Metformin and current recommendations about the use of this drug. We identified keywords and MeSH terms in Pubmed and the terms Metformin and type 2 diabetes, type 1 diabetes, pregnancy, heart failure, PCOS, etc, were searched, selecting only significant original articles and review in English, in particular of the last five years. Conclusion: Even if many new effective hypoglycemic agents have been launched in the market in the last few years, Metformin would always keep a place in the treatment of type 2 diabetes and its comorbidities because of its multiple positive effects and low cost.

scholarly journals Potential Therapeutic Effects of Curcumin on Glycemic and Lipid Profile in Uncomplicated Type 2 Diabetes—A Meta-Analysis of Randomized Controlled Trial

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 404
Author(s):  
Emma Altobelli ◽  
Paolo Matteo Angeletti ◽  
Ciro Marziliano ◽  
Marianna Mastrodomenico ◽  
Anna Rita Giuliani ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Lipid Profile ◽  
Effect Size ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Glycosylated Hemoglobin ◽  
Cochrane Library ◽  
Therapeutic Effects ◽  
Model Assessment

Diabetes mellitus is an important issue for public health, and it is growing in the world. In recent years, there has been a growing research interest on efficacy evidence of the curcumin use in the regulation of glycemia and lipidaemia. The molecular structure of curcumins allows to intercept reactive oxygen species (ROI) that are particularly harmful in chronic inflammation and tumorigenesis models. The aim of our study performed a systematic review and meta-analysis to evaluate the effect of curcumin on glycemic and lipid profile in subjects with uncomplicated type 2 diabetes. The papers included in the meta-analysis were sought in the MEDLINE, EMBASE, Scopus, Clinicaltrials.gov, Web of Science, and Cochrane Library databases as of October 2020. The sizes were pooled across studies in order to obtain an overall effect size. A random effects model was used to account for different sources of variation among studies. Cohen’s d, with 95% confidence interval (CI) was used as a measure of the effect size. Heterogeneity was assessed while using Q statistics. The ANOVA-Q test was used to value the differences among groups. Publication bias was analyzed and represented by a funnel plot. Curcumin treatment does not show a statistically significant reduction between treated and untreated patients. On the other hand, glycosylated hemoglobin, homeostasis model assessment (HOMA), and low-density lipoprotein (LDL) showed a statistically significant reduction in subjects that were treated with curcumin, respectively (p = 0.008, p < 0.001, p = 0.021). When considering HBA1c, the meta-regressions only showed statistical significance for gender (p = 0.034). Our meta-analysis seems to confirm the benefits on glucose metabolism, with results that appear to be more solid than those of lipid metabolism. However, further studies are needed in order to test the efficacy and safety of curcumin in uncomplicated type 2 diabetes.

scholarly journals Relationship of the Self-perception of Lifestyle with Level of Physical Activity in People with and without Type 2 Diabetes

2019 ◽  
pp. 1-7
Author(s):  
Briseida Mayel Perez-Avelino ◽  
Nicolás Padilla-Raygoza ◽  
Verónica Benitez-Guerrero ◽  
María Luisa Sánchez Padilla ◽  
Vicente Beltrán-Campos ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Statistical Significance ◽  
Self Perception ◽  
Chi Square ◽  
Cross Sectional ◽  
Lifestyle Questionnaire ◽  
Chi Square Test ◽  
Relationship Of

Objective: To determine the relationship of the perception of lifestyle with the level of physical activity in people with type 2 diabetes and without type 2 diabetes. Study Design: Analytical cross-sectional observational study in Celaya, Guanajuato, Mexico. Methodology: Sample composed of 100 people with type 2 diabetes and 100 people without type 2 diabetes, the lifestyle questionnaire and IPAQ questionnaire were used. Descriptive statistics were calculated for sociodemographic variables; it was calculated Chi-square test and Odds Ratio.  To demonstrate the statistical significance of results, the value of P was set at .05. Statistical analysis was performed in STATA 13.0 ®. Results: In patients with Type 2 Diabetes predominated females, married, who never went school and elementary and BMI ≥ 25 kg/m2; among patients without Type 2 Diabetes, predominant males, singles, went school or university, BMI ≥25 kg/m2; no relationship was found between lifestyle perception and level of physical activity in adults with type 2 diabetes (X² = 0.0022 gl 1 P = .96) neither it was found a significant relationship between lifestyle perception and level of physical activity in adults without type 2 diabetes (X² = 5.23 gl 1 P = .02 RM = 2.85 95% CI = 0.80 to 10.4). Conclusion: The results show that self-perception of lifestyle and physical activity is different in people with less age, more schooling, males.

Low Cost IoT-Based Smart Wheelchair for Type-2 Diabetes and Spine-Disorder Patients

2021 ◽  
pp. 855-862
Author(s):  
Sayanti Dutta ◽  
Anusha Chaudhuri ◽  
Arindam Chakraborty
Keyword(s):  
Type 2 Diabetes ◽  
Low Cost ◽  
Smart Wheelchair

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 Recruitment, retention, and training of people with type 2 diabetes as diabetes prevention mentors (DPM) to support a healthcare professional-delivered diabetes prevention program: the Norfolk Diabetes Prevention Study (NDPS)

2019 ◽  
Vol 7 (1) ◽  
pp. e000619
Author(s):  
Nikki J Garner ◽  
Melanie Pascale ◽  
Kalman France ◽  
Clare Ferns ◽  
Allan Clark ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Healthcare Professionals ◽  
Diabetes Management ◽  
Low Cost ◽  
Diabetes Prevention Program ◽  
Lifestyle Interventions ◽  
Effective Prevention

ObjectiveIntensive lifestyle interventions reduce the risk of type 2 diabetes in populations at highest risk, but staffing levels are usually unable to meet the challenge of delivering effective prevention strategies to a very large at-risk population. Training volunteers with existing type 2 diabetes to support healthcare professionals deliver lifestyle interventions is an attractive option.MethodsWe identified 141 973 people at highest risk of diabetes in the East of England, screened 12 778, and randomized 1764 into a suite of type 2 diabetes prevention and screen detected type 2 diabetes management trials. A key element of the program tested the value of volunteers with type 2 diabetes, trained to act as diabetes prevention mentors (DPM) when added to an intervention arm delivered by healthcare professionals trained to support participant lifestyle change.ResultsWe invited 9951 people with type 2 diabetes to become DPM and 427 responded (4.3%). Of these, 356 (83.3%) were interviewed by phone, and of these 131 (36.8%) were interviewed in person. We then appointed 104 of these 131 interviewed applicants (79%) to the role (mean age 62 years, 55% (n=57) male). All DPMs volunteered for a total of 2895 months, and made 6879 telephone calls to 461 randomized participants. Seventy-six (73%) DPMs volunteered for at least 6 months and 66 (73%) for at least 1 year.DiscussionIndividuals with type 2 diabetes can be recruited, trained and retained as DPM in large numbers to support a group-based diabetes prevention program delivered by healthcare professionals. This volunteer model is low cost, and accesses the large type 2 diabetes population that shares a lifestyle experience with the target population. This is an attractive model for supporting diabetes prevention efforts.

scholarly journals The Effect ofTinospora crispaon Serum Glucose and Insulin Levels in Patients with Type 2 Diabetes Mellitus

2012 ◽  
Vol 2012 ◽  
pp. 1-4 ◽  
Author(s):  
Theerawut Klangjareonchai ◽  
Chulaporn Roongpisuthipong
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Healthy Subjects ◽  
Statistical Significance ◽  
Area Under The Curve ◽  
Serum Glucose ◽  
Dry Powder ◽  
Insulin Levels

Objective. To determine the effects ofTinospora crispaon serum glucose and insulin levels in healthy subjects and patients with type 2 diabetes mellitus.Method. Serum from 10 healthy subjects and 10 diabetic participants, who had fasted overnight, were obtained every 30–60 minutes during the 3 hours of continued fasting and during the 3 hours after ingestion of 75 g of glucose with or without ingestion of 125 or 250 g ofTinospora crispadry powder capsule. Glucose and Insulin levels were analyzed and the areas under the curve for mean serum glucose and insulin levels were calculated.Result. The areas under the curve of mean serum glucose and insulin levels in both healthy and diabetic participants were not significantly different between with or withoutTinospora crispadry powder capsule. In diabetic participants the area under the curve of glucose was slightly lesser when 250 mg ofTinospora crispawas ingested, but not reaching statistical significance (478 and 444 mg min/ml, resp.,P=0.57).Conclusion. The results suggest thatTinospora crispaingestion cannot affect serum glucose and insulin levels in healthy subjects or patients with type 2 diabetes mellitus.

scholarly journals Interpretable Machine Learning Algorithm Reveals Novel Gut Microbiome Features in Predicting Type 2 Diabetes

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1559-1559
Author(s):  
Wanglong Gou ◽  
Chu-Wen Ling ◽  
Yan He ◽  
Zengliang Jiang ◽  
Yuanqing Fu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Gut Microbiome ◽  
Large Scale ◽  
Validation Cohort ◽  
Learning Algorithm ◽  
External Validation ◽  
Positive Association ◽  
Interpretable Machine Learning

Abstract Objectives The gut microbiome-type 2 diabetes (T2D) relationship among human cohorts have been controversial. We hypothesized that this limitation could be addressed by integrating the cutting-edge interpretable machine learning framework and large-scale human cohort studies. Methods 3 independent cohorts with &gt;9000 participants were included in this study. We proposed a new machine learning-based analytic framework — using LightGBM to infer the relationship between incorporated features and T2D, and SHapley Additive explanation(SHAP) to identified microbiome features associated with the risk of T2D. We then generated a microbiome risk score (MRS) integrating the threshold and direction of the identified microbiome features to predict T2D risk. Results We finally identified 15 microbiome features (two of them are indicators of microbial diversity, others are taxa-related features) associated with the risk of T2D. The identified T2D-related gut microbiome features showed superior T2D prediction accuracy compared to host genetics or traditional risk factors. Furthermore, we found that the MRS (per unit change in MRS) consistently showed positive association with T2D risk in the discovery cohort (RR 1.28, 95%CI 1.23-1.33), external validation cohort 1 (RR 1.23, 95%CI 1.13-1.34) and external validation cohort 2 (GGMP, RR 1.12, 95%CI 1.06-1.18). The MRS could also predict future glucose increment. We subsequently identified dietary and lifestyle factors which could prospectively modulate the microbiome features, and found that body fat distribution may be the key factor modulating the gut microbiome-T2D relationship. Conclusions Taken together, we proposed a new analytical framework for the investigation of microbiome-disease relationship. The identified microbiome features may serve as potential drug targets for T2D in future. Funding Sources This study was funded by National Natural Science Foundation of China (81903316, 81773416), Westlake University (101396021801) and the 5010 Program for Clinical Researches (2007032) of the Sun Yat-sen University (Guangzhou, China).

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