Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 28th World Congress on Diabetes, Obesity & Heart Tokyo, Japan.

Day 1 :

Conference Series Diabetes & Heart Experts Meet 2018 International Conference Keynote Speaker Gerald C. Hsu photo
Biography:

The author received an honorable PhD in mathematics and majored in engineering at MIT.  He attended different universities over 17 years and studied seven academic disciplines.  He has spent 20,000 hours in T2D research.  First, he studied six metabolic diseases and food nutrition during 2010-2013, then conducted research during 2014-2018.  His approach is “math-physics and quantitative medicine” based on mathematics, physics, engineering modeling, signal processing, computer science, big data analytics, statistics, machine learning, and AI.  His main focus is on preventive medicine using prediction tools.  He believes that the better the prediction, the more control you have.

 

Abstract:

Background and Aim:

The author has extended his 8-year T2D research to focus on the relationship between lifestyle for managing metabolic diseases and the probability of having a heart attack or stroke.

Material and Method:

He has developed several big data numerical simulation models using ~1.5M data.  Initially, he chose age, gender, race, family history, smoking, drinking, drug abuse, medical health conditions, and weight/waistline to establish a static baseline. He then developed a mathematical simulation model to combine all key elements of lifestyle management, including food, exercise, stress, sleep, water intake, life routine to conduct his dynamic computations.  He utilized 295,620 data of these six categories within the past 2,274 days to compute the probability of having a heart attack or stroke in the near future.  Finally, he conducted sensitivity analyses to cover the probability variance using different weighting factors (WF).

Results:

Comparing the results from the worst year, 2000, to the health-improving period of 2012-2018, the probability values are:

2000 with BMI 31:  83%

(Three episodes of chest pain during 2001-2006)

2012 with BMI 29:  70%

2018 with BMI 25:  33%

(Normalization Range: 0% - 100%)

In summary, within eight years, he has an average of 34% probability with +/- 18% variance of WF sensitivity.

The mathematical simulation results are validated by past health examination reports.  This big data dynamic simulation approach using math-physical medicine will provide an early warning to patients with chronic disease of having a heart attack or stroke in the future.

 

 

Keynote Forum

Damien Byas

Center for Organizational Research USA

Keynote: Examining the Relationship Between Risk Factors and Obesity Rates in Children and Adults

Time : -

Conference Series Diabetes & Heart Experts Meet 2018 International Conference Keynote Speaker Damien Byas photo
Biography:

Damien Byas Currently serving as a professor in a Master of Public Health (MPH) Program, Senior Research Fellow, and an adjunct professor for an MPH program

Abstract:

Statement of the Problem: The World Health Organization (2017) recently reported that “worldwide, at least 2.8 million people die each year as a result of being overweight or obese, and an estimated 35.8 million (2.3%) of global Disability-adjusted life years (DALYs) are caused by overweight or obesity. The purpose of this study was examine identifiable risk factors and disease outcomes which may be associated with obesity prevalence rates in children and adult populations. Methodology & Theoretical Orientation: This study examined inpatient pediatric patients using the Kids´ Inpatient Database (KID), Healthcare Cost and Utilization Project (HCUP), and the Agency for Healthcare Research and Quality (AHRQ, 2014;2016). A large randomly drawn sample (N = 524,581) of boys (n = 244,553) and girls (n = 280,028) ages 5 to 12, was examined in this research study to test for the association between obesity prevalence and disease related outcomes. Additionally, a small adult sample of adults ages 19 to 55 (N = 143), enrolled in an undergraduate level city college program, were assessed to determine if there was a relationship between obesity prevalence and the outcomes of heart disease risk and type 2 Diabetes risk. The Pearson Chi Square test was applied to measure for significant variable associations in this research study in addition to the application of the Cramer’s V analysis to examine for strength of variable associations. A multiple regression analysis was applied to determine if heart disease risk and type 2 diabetes risk were significant predictors of obesity prevalence in adult groups. Findings: The research found that there were significant associations between obesity and health outcomes in children (p < .001) and that the factors of heart disease risk and type 2 diabetes risk were significant predictors for obesity prevalence in adults (p < .05). Conclusion & Significance: The outcome of this research study provides support for improved efforts to develop more effective strategies to promote positive healthy lifestyles in adults and children’s populations.

Keynote Forum

Shade Akande

Stony Brook University, USA

Keynote: Factors associated with Heart failure Readmissions from Skilled Nursing facilities

Time : -

Conference Series Diabetes & Heart Experts Meet 2018 International Conference Keynote Speaker Shade Akande photo
Biography:

Shade Akande has completed her Doctor of Nursing practice from Stony Brook University. NY, USA in the year 2015. She has given numerous podium presentations related to nursing practice. As a Clinician, she has the expertise, leadership and motivation to successfully contribute to the mission and values of programs and the institution as a whole. She is dedicated to continuously deliver excellent and quality care to the population with increased productivity and positive outcome, fostering education and to embrace the concept of continuous performance improvement

Abstract:

Background: Despite guideline-driven pharmacological therapies and careful transitional care, the rates of preventable hospital re-admission of heart failure patients and associated costs remain unacceptably high in the SNF populations. Transfer to SNF is one strategy to limit hospitalizations. As such, 25% of patients are still symptomatic at time of discharge.

Purpose: The objective of this study is to identify patient factors affecting re-admissions of HF patients residing in SNF within 30-days.  

Methods: A retrospective electronic chart review was completed on patients >65 years with HF who were admitted into large medical center between 2012 and 2014. Descriptive statistics and univariate analyses using the chi-square test or Fisher’s exact test for categorical variables and the Mann-Whitney test for continuous data was used to compare patients readmitted within 30 days vs. those who were not readmitted within 30 days. Significant factors associated with readmission in the univariate analysis (p<0.10) were included for a multivariate logistic regression model. A receiver operating characteristic (ROC) curve was constructed to look at the final model’s ability to predict the outcome.  A numerical measure of the accuracy of the model was obtained from the area under the curve (AUC), where an area of 1.0 signifies near perfect accuracy. The analysis of LOS was accomplished by applying standard methods of survival analysis, i.e., computing the Kaplan-Meier product limit curves, where the data were stratified by readmission within 30 days (Yes vs. No).  No data were considered ‘censored’.  The groups were compared using the log-rank test.  The median rates for each group were obtained from the Kaplan-Meier/Product-Limit Estimates and their corresponding 95% confidence intervals were computed, using Greenwood’s formula to calculate the standard error.  Unless otherwise specified, a result was considered statistically significant at the p<0.05 level of significance. 

Results: Fifteen variables: creatinine, weight difference, CKD, Angina, Arrhythmia, VHD, Tobacco, ADL, independent in bathing, independent in the toilet, S3 Heart sounds present, HJR, AF, Nitrates, and Hydralazine, were identified for the multivariate logistic regression as potential risk factors associated with “readmission within 30 days”. Based on 23 readmissions within 30 days, our final model included only 2 predictor variables.  Creatinine and ADLs were included in the final model as this subset of predictors was found to be the best for prediction of “readmission within 30 days”. Creatinine (p<0.0087) and ADLs (p<0.0077) were both significantly associated with readmission within 30 days in the final logistic regression model.  Every 1-unit increase in creatinine is associated with an 87% increase in the odds of being readmitted within 30 days (OR = 1.87).   Those patients who require assistance with ADLs are over 9 times more likely to be readmitted within 30 days (OR=9.25) as compared to patients who are independent.

 

  • Diabetes and its Complications|Diabetes and Endocrine Complications|CardioMetabolic Syndromes|Diagnosis and Prevention: Diabetes & Heart Diseases|Diabetes & Heart Monitoring Management
Location: Radisson Hotel Narita
Speaker

Chair

Gerald C Hsu

eclaireMD Foundation, USA

Speaker

Co-Chair

Ravi Kant

AIIMS, India

Speaker
Biography:

Sun Shin Yi, D.V.M., Ph.D. has his expertise in evaluation feeding behavior under hyperphagia, sleep and diabetic conditions. He has experienced at lots of preclinical studies about metabolic diseases. He has built this model after years of experience in research, evaluation, teaching and administration both in research and education institutions. He has published more than 60 papers in reputed journals and a board member of Korea Mouse Phenotying Center (KMPC).

 

Abstract:

In particular, sleep is known to be closely related to obesity and diabetes, so we sought to find evidence of sleep efficacy and its use in diabetes. Insomnia is not only a decrease in neurogenesis in the hippocampus, which is the backbone of short-term memory, but also in obesity and diabetes. In this study, we investigated the amount of neuroblast expression in a short DBA/2 mouse strain with a sleep abnormality, and constructed a diabetic model of C.elegans.

Following ingestion of Passion flower (Passiflora incarnate L.; PF) extract, the increase of melatonin level was confirmed in serum, and the increase of DCX was confirmed in Immunohistochemistry (IHC) in PF treated groups than in the untreated group. In addition, the anti-oxidative stress evidence at the C. elegans model was obtained of the PF treatment group, and also confirmed the high survival rate.

Taken togher, we found evidences that sleep efficacy of PF extracts not only improves neurogenesis in the subgranular zone (SGZ) of the hippocampal dentate gyrus, but also has a positive effect through resistance to obesity and diabetes that can occur with insomnia. Through the further study, we will show that PF has various positive effect on diabetes caused by DIO mice model and genetic engineered type 2 diabetic experimental animals.

Speaker
Biography:

Gerald C. Hsu received an honorable PhD in mathematics and majored in engineering at MIT.  He attended different universities over 17 years and studied seven academic disciplines.  He has spent 20,000 hours in T2D research.  First, he studied six metabolic diseases and food nutrition during 2010-2013, then conducted research during 2014-2018.  His approach is “math-physics and quantitative medicine” based on mathematics, physics, engineering modeling, signal processing, computer science, big data analytics, statistics, machine learning, and AI.  His main focus is on preventive medicine using prediction tools.  He believes that the better the prediction, the more control you have.

 

Abstract:

Background and Aim:

The author has extended his 8-year T2D research to focus on the relationship between metabolic diseases and the probability of having a heart attack or stroke.

Material and Method:

He has developed big data numerical simulation models using ~1.5M data.  Initially, he chose age, gender, race, family history, smoking, drinking, drug abuse, medical health conditions, and weight/waistline to establish a static baseline.  He then applied hemodynamics knowledge to develop a macro-simulated mathematical model for the dynamic situations of blood blockage and artery rupture.  He utilized 72,893 data of chronic disease conditions (output data of obesity, diabetes, hypertension, and hyperlipidemia) within the past 2,274 days to compute the probability of having a heart attack or stroke in the near future.  Finally, he conducted sensitivity analyses to cover the probability variance by using different weighting factors (WF).

Results:

Comparing the results from the worst year, 2000, to the health-improving period of 2012-2018, the probability values are:

2000 with BMI 31: 74% 

2001-2006:  Three episodes of chest pain

2012 with BMI 29:  62%

2017: 26.4%

2018 with BMI 25:  31%

(Framingham 2017: 26.7%)

In summary, within eight years, he has an average of 34% probability with +/- 10% variance of WF sensitivity.

Conclusion:

The mathematical simulation results are validated by past health examination reports.  This big data dynamic simulation approach using math-physical medicine will provide an early warning to patients with chronic disease of having a heart attack or stroke in the future.

 

Speaker
Biography:

Dr.Ravi kant is currently working as an associate professor and head, division of diabetes and metabolism in the department of medicine at All India Institute of Medical Sciences, Rishikesh. He has developed the department of medicine at AIIMS Rishikesh. He obtained fellowship in diabetes from CMC Vellore and from Harvard university .He is currently the Harvard course director for the certificate course in diabetes in India. He is also currently the secretary, South East Asian Foundation and the editor of South East Asian Medical Clinics .He is international advisor to the journal of diabetes and endocrine society of Nepal and also journal of public health and holistic medicine.

 

Abstract:

Background and Aim – The prevalence of diabetes in India has reached alarming levels with 8.7% of population affected as of 2015, which is expected to double in the future. The reasons for the rapid increase in prevalence of diabetes include genetic predilection of Indian population, economic boom, sedentary lifestyle, inadequate follow up and lack of disease awareness. The aim of the study was to overcome the self care deficit which would help patients to be more compliant and better in managing their illness.

Methodology – The study was conducted at weekly diabetes clinic at AIIMS, Rishikesh in which 2oo patients participated. Two sessions, each of 60 minutes were conducted fortnightly. The patients were educated by trained personnel using specially designed module in patients’ own language.  Each group consisted of 10- 15 participants. Participants were tested at the beginning and after the educational programme using a 10 item questionnaire. Data was analysed using MS Excel 2010.  Paired t test was used to find any significant difference between pre and post test score. Average learning gain was computed by Pre – post / 10- pre X100.

Results - A significant improvement in test scores after education session was noted. Average learning gain was 77.98 % ± 23.27 % after the group education. Sixty four percent participants demonstrated more than 75% learning gain.

Conclusion and further scope – A dedicated group session programme implemented in an environment conducive to learning with specially designed module has a significant impact on patients’ knowledge (64% participants demonstrated more than 75% learning gain) about the cause and treatment of their disease. The study can be extended to see if it impacts behaviour by tracing changes in glycaemic control.

 

Biography:

Seema Vinayak is a professor of psychology at Department of Psychology, Panjab University, Chandigarh in India. With research and teaching experience of more than two decades, she has delivered keynote addresses, research presentations, chaired sessions at national and international conferences. Widely travelled and honoured at national and international forums, Prof Vinayak has specialization in clinical psychology, organizational and media psychology.

 

Abstract:

Statement of Problem: Life threatening ailments can be very stressful and may require reconstructing of one's thought process and readjustment of one’s priorities in life. Though studies have highlighted the trauma faced by people diagnosed with cardiovascular diseases, there is lack of research on post-traumatic growth in patients with heart ailments. This research   focusses on cognitive and social predictors of PTG.

Methodology: About 2000 patients (undergoing treatment for heart ailment or cancer) at the hospitals located in three neighboring states viz. Punjab, Haryana and UT of Chandigarh were contacted. Out of these, who met the inclusion criteria and volunteered, 200 patients for each ailment category and 200 as control group were investigated on cognitive rigidity, meaning in life, resilience, perceived intimate partner emotional abuse, marital satisfaction and PTG.

Statistics: Mixed research with qualitative and quantative strands was used. Descriptive analyses, intercorrelation, regression analysis and 2x3 ANOVA ( with 2 levels of gender and 3 levels of conditions) were done. Besides, interviews with the participants were done.

Findings: Cognitive rigidity, perceived intimate partner abuse and marital  satisfaction emerged as significant predictors for PTG. Resilience , marital satisfaction was higher in  heart patients as compared to patients with cancer. Significant gender differences on cognitive rigidity, intimate partner emotional abuse and marital satisfaction emerged.

Conclusion and significance: Psychological intervention programs for the patients can be designed which will add to the life satisfaction and general wellbeing of the patients.

Speaker
Biography:

Ginny Y. Y. Lam, RN(HK), MSN, MDEM earned her MSc in nursing and MSc in Endocrinology, Diabetes and Metabolism from the Hong Kong Polytechnic University and the Chinese University in Hong Kong, respectively. She has 13 years of nursing experience and 2 years of experience as a diabetes nurse. Currently, she is a doctoral student at the Chinese University in Hong Kong and a Nursing Educator in Hong Kong Baptist Hospital. Her research efforts are focused on the area of self-management in patients with diabetes

Abstract:

Diabetes mellitus affects about 10% of total population in Hong Kong, and type 2 diabetes (T2DM) accounts for 90% of all diagnosed diabetes cases. The standard management plan of T2DM includes diabetes self-management education and continuous diabetes support. eHealth offers a 24 h accessible platform that promotes self-management and self-care among patients with diabetes.

A fully automated mobile application called ‘iCare’ was developed, and its effect on the outcome of patients with T2DM in Hong Kong was examined by conducting a randomized controlled trial (RCT). The primary outcome was diabetes self-care behaviour and the secondary outcome was glycated haemoglobin (HbA1C).

The study was conducted at a diabetes clinic in a regional hospital in Hong Kong from June, 2015 to October, 2016. Those eligible patients were approached for the study and screened for their interest and final eligibility. After explanation and obtaining the written consent, they were randomised into a control group or intervention group. The participants in the control group received usual care and intervention group received eHealth intervention - iCare on top of the usual care. All outcome measures were assessed at baseline (T0) and 3 months post intervention (T1) in both groups. Intention-to-treat (ITT) and per- protocol analyses were performed to address the effect of attrition.

A total of 170 eligible participants were randomised into the control group (n= 85) or the intervention group (n= 85). No significant differences were observed in the group-by-time interaction for all constructs of diabetes self-care behaviour in the adjusted model (diet p=0.804; exercise p=0.912; medication p=0.892; self-monitoring blood glucose [SMBG] p=0.109; and foot care p=0.187). Similar to the primary outcome, the secondary outcome did not differ between the two groups after the 3-month intervention. Results of per-protocol analysis were comparable with the findings of the ITT analysis.

Results showed that the eHealth intervention iCare did not significantly improve any outcome measurements when compared with usual care after the 3-month study period. Modest improvements were observed in all constructs of diabetes self-care behaviour in the intervention group. Future research and development of eHealth applications may be needed to strengthen the interactivity of the eHealth design and to identify the aspects and extents that can facilitate self-management among patients with T2DM.

  • Workshop

Session Introduction

Vivek Kamath

Founder & Managing Director, Heal the World

Title: Heart Diseases – Cure without any surgery/medicines
Speaker
Biography:

Vivek Kamath founder of heal the world organization is a Reiki Master, Mexican Healer, Melchizedek Healer, Crystal Healer and Past Life Regression Therapy Expert. He has healed many diabetic patients (Type1, Type2, Type 3/1.5/LADA) without any medicines. He has also healed blood pressure (both high and low blood pressure), heart disease (removed the heart blockages), removed kidney stones, ovarian cysts, fibrosis of the breast, fatty liver, lungs disease, cured sinusitis, sever joint pain, lumbar L5 spinal disk pain, Sciatica pain, neck pain, constipation, rheumatoid arthritis, glaucoma,migraines,headaches,insomnia,stomach related problem, IBS, diabetic gum problems, skin problems( dry skin, eczema) and chronic nasal allergies, nasal blockages without any medicines. Some of the above treatments have been completed within a week to maximum 1 month duration.  

 

Abstract:

Statement of the Problem:  Heart Diseases such as High Blood Pressure, Low Blood Pressure, High Cholesterol, High Triglycerides and Heart Blockages.

Heal The World – A revolutionarily health care organization has been formed in Bangalore, India to heal any diseases without any medicines. We use powerful ancient healing techniques such as 1. REIKI 2. MEXICAN Healing 3. Crystal Healing 4. Melchizedek Healing 5. Past Life Regression therapy to heal any diseases.

We have healed many blood pressure, cholesterol and high triglycerides patients within a month’s time without any medicines.

In fact, with the help of Reiki Distant healing, we have healed low blood pressure diseases within 15 days.

Recently, we have tested few patients of high blood pressure (180/130) and we provided them 1 Mexican healing and immediately after the 1 Mexican healing, we checked their blood pressure it came down by 20 units. (160/100). Furthermore, we gave few Reiki Distant healings to high cholesterol (400) and high triglycerides (900) and within few days their cholesterol came down to (240) and triglycerides came down to 650.

We have also removed CAD (triple vessel disease) 3 blockages within 18 days of Reiki Distant and 5 Mexican healing sessions. Till now, we have removed the blockages of 2 patients.

The first thing what we do in healing is to remove the chest pain within few days. Once we remove the pain, then we start working on reducing their blood pressure, bringing cholesterol to normal level and cleansing all the nerves, valves and organs etc. The energy which we pass in the heart and valves helps to remove the blocks and negative energy from the organ.  

More importantly, in some case Reiki Distant healing has been proved very effective to remove the pain.