Day 2 :
eclaireMD Foundation, USA
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.
Based on his research, the author developed two prediction tools and was able to reduce his PPG from 380 mg/dL to 116 mg/dL, daily glucose from 279 mg/dL to 117 mg/dL, and A1C from 10% to 6.1%
He examined correlations between PPG and three known major factors, medication, carbs and sugar intake, exercise, and other secondary factors, including stress/tension, measurement time delay, traveling, illness, sleep disturbance, seasonal weather, etc. In summary, more than 20 elements were considered and over 1 million data collected.
During 934 days (from 6/1/2015 to 12/21/2017), he had 2,802 meals and collected about 60,000 PPG-related data. The conclusions were: +60% correlation between PPG and carbs and sugar intake (average 14.7 gram and 38% contribution rate); - 64% correlation between PPG and post-meal walking (average 4,300 steps and 43% contribution rate). Collectively, these secondary factors account for approximately 19% (weather has contributed 10%) of the predicted PPG values.
Those collected 2,800 meal photos were analyzed against 6 million food data collected and re-processed from US government and stored in cloud server. All food data were sorted according to country, franchise restaurants, individual cafes,
home-cooked meals, airline food, etc. Here are some examples:
Airline food - 136 mg/dL; Restaurant food - 127 mg/dL; Home
Cooking - 111 mg/dL.
The predicted PPG (115.5 mg/dL) vs measured PPG (120.5
mg/dL) has a linear accuracy rate of 96% and 87% correlation.
Abdul Malek Ukil Medical College, Bangladesh
Dr. Mohammad Saifuddin, young eminent endocrinologist of Bangladesh who dedicated himself in service of humanity towards rural people of Bangladesh. He passed MBBS from Dhaka Medical College at 2004 and obtained fellowship in Medicine (FCPS) from Bangladesh College of Physicians and Surgeons at 2012 and passed MD (Endocrinology) from BIRDEM Academy at 2013. He is working in Bangladesh Civil Service for last 10 years and now working as Assistant Professor (Endocrinology) in Abdul Malek Ukil Medical College, Noakhali, Bangladesh. He has 14 publications in national and international level. His work of interest in Diabetes and complications, Adrenal disorders, Osteoporosis, Thyroid disorders, Menstrual abnormalities.
Patients with diabetes mellitus (DM) are prone to develop infection, especially urinary tract infection (UTI) in comparison with non-diabetics. Due to the emergence of multidrug resistant (MDR) uropathogenic strains, the choice of antimicrobial agent is sometimes difficult. This study is designed to reveal the distribution of uropathogens in Diabetic patients and corresponding sensitivity patterns and to correlate the microbiological results with various clinical parameters. A nine month retrospective review of 100 urine culture reports of Diabetic patients from January 2015 to September 2015 from semiurban multispeciality hospital of Feni, Bangladesh were analyzed. Only Diabetic patients were included in this study who were clinically diagnosed as UTI patients with a corresponding urine culture showing a bacterial count of ˃105cfu/ml. Out of 100 patients with UTI, 39 (39%) were male and 61 (61%) were female. Organisms grown in urine culture were Escherichia coli (64) followed by Klebsiella (11), Proteus (7), Staph Aureus (4), Pseudomonas (4), Acinetobacter (3), Sreptococcus (3), Enterococcus (2) and one each of Enterobacter and Fungi. Overall sensitivity pattern in decreasing order of various commonly used antibiotics were Meropenem (89%), Nitrofurantoin (86%), Amikacin (81%), Ceftriaxone (68%), Cefuroxime (61%), Cefixime (39%), Quinolones (28%), Amoxicillin (16%). The significance of the study lies in the determination of common pathogens in diabetic patients with UTI and the resistance pattern of antibiotics so that physicians and pharmacists get the proper information rationalizing the rational use of antibiotics.
Urgo International, Singapore
Emilio Galea started his career in healthcare in 1985 in Malta where he held different positions, from direct care, clinical instructor and examiner with the Institute of Healthcare and managerial positions. He went to the Middle East in 2007 as a Clinical Resource Nurse and then Assistant Director of Nursing. His role included the function of wound management advisor. Emilio is active in conferences and was awarded with the Speaker of the Year Award by the Health Authority of Abu Dhabi. He contributes regularly to magazines and wound care journals and also published the ‘Wound Care Product Catalogue’ that provided guidelines regarding advanced wound care products in SEHA facilities. Emilio is currently the International Medical Director for Urgo International. He holds an MSc Skin Integrity Skills & Treatment from the University of Hertfordshire (UK) and his personal and professional objective is to facilitate, through education, evidence based wound management practice.
A growing proportion of diabetic foot ulcers are being diagnosed as neuro-ischemic. Diabetic foot ulcers (DFUs) score high in the incidence of chronic wounds; the annual population-based incidence of DFUs ranges from 1.0% to 4.1%, with a lifetime incidence that may be as high as 25% globally. Neuro-ischemia predominately leads to the development of ulcers on the margins of the foot, toes and dorsum of the foot rather than at pressure sites from poorly fitting shoes. Management of this type of wound is complex, requiring prompt referral, debridement where indicated, appropriate footwear, offloading, dressings and the treatment of infection. Although neuro-ischemic ulcers are the most common DFUs, until recently, no studies have assessed the superiority of any device in a cohort of patients with only neuro-ischemic ulcers and no device or drug has demonstrated efficacy in neuro-ischemic DFU treatment.
The discovery that matrix metalloproteinases and neovascularization are involved has led to the identification and study of nano-oligosaccharide factor (KSOS molecule), which shows promise in treating this challenging condition. Conducted on 240 patients across five European countries, the Explorer study represents a clinical research first in the field of diabetic foot ulcers. The randomized, double-blind study compares the efficacy and tolerance of the TLC-NOSF matrix to those of a neutral dressing on neuro-ischemic diabetic foot ulcers. Reactions to the Explorer RCT have been very promising, where it was suggested that: “the results are certainly more encouraging than findings for most interventions that have been reported to date”
An overview will be provided regarding the global burden of diabetic neuro-ischemic ulcers and the results of the ground breaking double blind study published in The Lancet, that has identified effective local treatment of these devastating ulcers.
Government College University, Pakistan
Dr. Andleeb Batool has expertise in Molecular Biology and human genetics. Currently working on Epidemiology familial genetics of Type 1 and Type 2 Diabetes.
Type 2 diabetes (T2D) has been the subject of numerous genetic studies in recent years which revealed associations of the disease with many susceptibility loci. We evaluated the 10 genes (TCF7L2, HHEX, ITGA2, CDKL1, ADRB3, PRKCB1, CETP, GNB3, LTA, LPL, PPARG) for susceptibility of T2D in Pakistani population by performing a case-control study. A total of 450 subjects (Patients= 280, Controls = 70) participated in the study. Genotyping was performed by PCR-RFLP and overall, 6 SNPs from the study were found to be significantly associated with T2D. ITGA2 (rs1062535- rs1139484- KT359366) was first time studied in south Asians which showed a significant association with T2D and a novel SNP was identified and got its accession number (KT359366). The loci from HHEX, ITGA2, LTA, PPARG and ADD1 remain associated with T2D after SNP and genotype analysis (P < 0.05) while GNB3 and PRKCB1 were only associated in genotype analysis. Two haplotypes (GAT, GGC) from ITGA2 were associated with T2D development while GGT (p-0.0001) was protective against diabetes. No association was detected with TCF7L2, CDKL1, ADRB3, CETP, GNB3, and LPL. This data can be used for prevention and screening of population at risk, moreover can be helpful in large scale studies.