Background: One of the most common types of diabetes is Type 1 Diabetes Mellitus (T1DM) which causes high or low blood glucose levels (BGL) in a patient’s body. T1DM patients need to maintain their BGL in a safe glycemic range which is between 4.0 mmol/L to 7 mmol/L. Thus, it is high time to find the optimum insulin infusion rate into the patient’s body in achieving prolonged normoglycemic range. Methods: Previous workers had focused on employing the improved Hovorka equations via in-silico study using one T1DM patient’s data; however, in-silico works employing more actual patients’ data are yet to be explored. Hence, this study attempts to apply the improved Hovorka equations on three different T1DM subjects so as to simulate their BGL profiles based on daily stipulated meal disturbances, individual body weights and age group. Results: Results showed that the optimum insulin infusion rates required to regulate the BGL within safe glycemic range were at 0.1 U/min, 0.05 U/min and 0.0167 U/min for the case of patients 1, 2 and 3, respectively; provided that different amounts of meal intake (DG) were observed by each patient during breakfast, lunch and dinner times. Conclusion: In conclusion, this study had proven that the improved Hovorka equations can be used to simulate the meal disturbance effect on BGL for more T1DM patients. Keywords Blood glucose level; Closed-loop control system; Hovorka model; Meal disturbance; Type 1 diabetes mellitus
Diabetes is a widely known disease, which afflicts millions of people annually and is considered one of the leading culprits of mortality and morbidity worldwide.Researchers are making an enormous effort to propose more efficient remedies for the better amelioration of the disease.On the other hand, the public interest in the consumption of herbal medicine for therapeutic purposes is rocketing and the use of these drugs is becoming ubiquitous.Murraya koenigii MK is a tropical tree, originally found in the Indian subcontinent, which is an indispensable piece of the Indian diet and has multipotent medicinal capabilities.The variety of its leaves' hypoglycemic characteristics has been investigated via human, animal, and in vitro studies.This review intends to elaborate on the latest knowledge about the anti-diabetic and hypoglycemic effects of MK in the hope of easing the further application of MK in the alleviation of the diabetes signs and symptoms.
Background: Obesity, insulin resistance and myostatin levels are known to be risk factors for breast cancer.The aim of this study was to evaluate the effect of nonlinear resistance training on serum myostatin levels and insulin resistance in women with breast cancer. Methods:In the present quasi experimental study, 20 women with breast cancer were selected by random sampling from patients referred to Imam Hassan Chemotherapy Center Dezful, Iran and randomly selected in the group of resistance training with non-linear training and control groups.Exercise intervention included 12 weeks of resistance training, 3 sessions per week and each training session including training of different muscle groups with 40%-90% maximum repetition was performed.Fasting blood sampling was performed 48 hours before and after the intervention period.Dependent t-test and analysis of covariance were used for statistical analysis (P ≤ 0.05). Results:After training period, there was a significant decrease was founded in body fat percentage (P=0.038),serum myostatin level (P=0.023),fasting insulin (P<0.001) and insulin resistance (P<0.001) in the training group compared to the control group, but there was no significant difference was observed in the variables of weight (P=0.603),body mass index (P=0.965)and fasting glucose (P=0.410). Conclusion:According to the results of resistance training with improving body composition and insulin resistance has a positive role in reducing the complications associated with breast cancer and these changes are probably related to the metabolic effects of myostatin, a myocene associated with skeletal muscle growth is created.
Introduction: Diabetes Mellitus remains a major public health problem in Africa in the last two decades. A new conceptual framework for studying and understanding trajectories of experiences of people with diabetes mellitus in Africa is presented. Objective: The paper examines all known factors influencing the trajectories of lived experiences of persons with diabetes and how these factors interact with each other at micro and macro levels. Methods: A systematic mapping of peer reviewed literature (n=61) conducted in Africa and published between 01/01/1990 and 31/12/2020 was utilised. Results: Using a conceptual framework, we synthesised the factors influencing trajectories of lived experiences of diabetes in Africa, grouped into six domains: diabetes risk factors, socio-demographic characteristics, individual level experiences, household/family level experiences, community/society level experiences and national level experiences. Conclusion: This framework can be used to test hypotheses about facilitators and barriers to health care-seeking behaviour. As well as understand how trajectories of lived experience of diabetes might be influenced by policy or practice. Research based on understanding of trajectories is expected to improve diabetes patient’s experiences and outcome in diabetes management and care in Africa.
Physical inactivity and poor dietary pattern are considered as health related challenges in ASD (ASD) which seems to be affected by Covid-19 pandemic. The purpose of this clinical trial was to investigate the effect of functional training along with online nutritional education on metabolic related biomarkers in children with ASD. 80 verified children with ASD (age=9.73 ± 1.29, weight=49.94 ± 2.08 kg, stature=146.08 ± 40 cm, BMI percentile= 64.88 ± 2.89, FM percentage+24.71 ± 1.48) were randomly divided into four groups including: (1) functional training, (2) online nutritional education, 3) training+ education and 4) control group. Pre-test was taken for metabolic related biomarkers and each experimental group received their interventions for 8 weeks. Post-test was taken at the end of 8 weeks. The results from this study, did not show significant changes for WHR (sig=0.06). Significant changes was indicated for FM (sig?0.001), TC(sig?0.001), TG (sig=0.006), HDL (sig?0.001), LDL (sig=0.001), HOMA (sig=0.04). In conclusion, functional training and online nutritional education can be considered as beneficial interventions for metabolic related biomarkers improvement in children with ASD during Covid-19 pandemic.
The main therapeutic goal for all type 2 diabetes mellitus (T2DM) patients is to maintain good control so as to prevent the risk of complications associated with poor control. This study determined the prevalence of poor control and its association with socio-demographics and malaria parasitaemia among middle aged and elderly T2DM patients at a tertiary hospital in rural Southwestern Nigeria. We conducted a retrospective observational study on 250 T2DM using semi-structured interviewer administered questionnaire. Venous blood samples were collected and processed for glycated hemoglobin sugar estimation and malaria parasite detection by microscopy. Data were analyzed using SPSS version 20.0. Multivariate logistic regression identi-fied the association of socio-demographics and asymptomatic malaria parasitaemia with poor control. The prevalence of poor glycemic control was 31.6% (95%CI: 34.4%-45.8%). Old age, (AOR=4.868; 95% CI: 1.258-24.574), female genders (AOR=7.100; 95% CI: 1.875-34.655), no formal education (AOR=3.447; 95% CI: 1.098-21.478), presence of malaria parasitaemia (AOR=48.423; 95% CI: 4.987-411.366), and higher parasite density (AOR=7.102; 95% CI: 1.785-15.002), were significantly associated with poor control. Health facilities should integrate screening of malaria parasitaemia into the management of T2DM patients while also exploring other barriers of poor control.
The purpose of the review is to explore the interlinkages between diabetes, insulin therapy, and body composition and discuss the need for body composition assessment as part of the routine nutrition and health assessment of children living with diabetes especially in resource limited contexts with a case study of Uganda. Changes in body composition have an intractable effect of Insulin Dependent Diabetes Mellitus and its management. The association between diabetes and body composition has the potential to lead to adverse health outcomes, especially in later years of life. Health practitioners shall devise strategies to efficiently monitor the body composition of young diabetics at an early stage to revert the life threatening complications among young diabetic patients.
Purpose: Paediatric endocrinology services are relatively new in Africa and Nigeria and the services and resources for the children with diabetes and other endocrine disorders are poorly de-veloped. We aimed to survey pediatric endocrinology services in Nigeria using an online survey tool. Methods: We surveyed the paediatric endocrinologists practicing in public tertiary institutions in Nigeria using an instrument designed to evaluate the availability of manpower, infrastructures, specific medications, and collaborations with other endo crinologists. Results: Fifteen of the 37 practicing paediatric endocrinologists responded, giving a response rate of h a response rate of 40.5%. The mean practice years was 9.3 (range 7-12), and many had skills in managing children with diabetes, thyroid and growth abnormalities. All centres had facilities for ultrasound scan and simple diagnostic techniques but few centres had access to iodine uptake studies, antibody testing and special hormones. While most centres could outsource special tests, patients could rarely afford the services. There were 297 children on manage ment for TIDM and over 90% of these were on pre-mix insulin. Conclusion: The dearth in human and infrastructural capacity in paediatric endocrinology services should be improved on and this will alleviate the burden of diabetes and endocrine disorders in Nigerian children. means the test can be outsourced in a peripheral laboratory not attached to the home center of the paediatric endocrinologist.
Until recently, obesity was one of the greatest public health issues. At the moment, the world is counting deaths from COVID-19, and raging obesity pandemic is not in the focus. While the quarantine is the mainstay of COVID-19 prevention, it also opposes obesity prevention. Obesity is a risk factor for severe COVID-19 infection. Treatment of obesity during quarantine is challenging;trying to lose weight without the opportunity for outdoor activity or access to fresh and healthy foods may lead to frustration, depression and overeating. Therefore, we propose that patients should focus on preventing new weight gain instead of losing weight. It can be achieved by practicing indoor physical exercise together with adequate diet. The diet should be opposite from, "Western diet pattern'' and include foods easily obtainable during quarantine;with longer shelf life, but also rich in anti-inflammatory and immune-modulatory bioactive compounds. These characteristics of the diet make it simple to implement during quarantine, it helps in the process maintaing weight and supports immune system-all what is required to possibly reduce the risk of severe COVID-19 infection. The anti-inflammatory properties from given diet have beneficial role, especially in obese patients, as they have low grade chronic inflammation which additionally may worsen clinical course of COVID-19 infection.
Background: Type 1 diabetes mellitus (T1DM) occurs due to inability of the body to produce sufficient amount of insulin to regulate blood glucose level (BGL) at normoglycemic range between 4.0 to 7.0 mmol/L. Thus, T1DM patients require doing self-monitoring blood glucose (SMBG) via finger pricks and depending on exogenous insulin injection to maintain their BGL which is very painful and exasperating. Ongoing works on artificial pancreas device nowadays focus primarily on a computer algorithm which is programmed into the controller device. This study aims to simulate so-called improved equations from the Hovorka model using actual patients' data through in-silico works and compare its findings with the clinical works. Methods: The study mainly focuses on computer simulation in MATLAB using improved Hovorka equations in order to control the BGL in T1DM. The improved equations can be found in three subsystems namely; glucose, insulin and insulin action subsystems. CHO intakes were varied during breakfast, lunch and dinner times for three consecutive days. Simulated data are compared with the actual patients' data from the clinical works. Results: Result revealed that when the patient took 36.0 g CHO during breakfast and lunch, the insulin administered was 0.1 U/min in order to maintain the blood glucose level (BGL) in the safe range after meal; while during dinner time, 0.083 U/min to 0.1 U/min of insulins were administered in order to regulate 45.0 g CHO taken during meal. The basal insulin was also injected at 0.066 U/min upon waking up time in the early morning. The BGL was able to remain at normal range after each meal during in-silico works compared to clinical works. Conclusions: This study proved that the improved Hovorka equations via in-silico works can be employed to model the effect of meal disruptions on T1DM patients, as it demonstrated better control as compared to the clinical works.
Introduction: The global prevalence and mortality of diabetes mellitus worldwide is steadily increasing, and its increases are faster in low and middle income countries. In Senegal, diabetes mellitus affects 2.1% of the population and is responsible for 3% of deaths from all causes. However, the epidemiological profile of the patients received in the emergency unit is not clearly established. This is how this study was conducted to find out the frequency of diabetes mellitus and the factors associated within the emergency unit of Dakar hospitals. Methodology: The study setting was for the emergency unit of Pikines Hospital and The Principal Hospital of Dakar. This was an observational, descriptive cross sectional study for analytical purposes looking for factors associated with the onset of diabetes. A representative sample was drawn and a consecutive recruitment of eligible patients was carried out. The data collection tools were based on the WHO stepwise survey questionnaire and the data collection was conducted in an ethical manner. Results: It was 615 patients who were included, of which 53.7% at The Principal Hospital of Dakar and 46.3% at the Pikine’s Hospital. This was 72.4% of those surveyed who did not engage in sufficient physical activity and only 3.6% reported consuming more than five fruits and vegetables per day. They were 22.7% to be overweight and 17.4% were obese. The patients who reported never having controlled their glycemia in their life were 40.4%. Among the patients who had measured their glycemia at least once in their life, 69.7% did so in a health facility, before resorting to the pharmacy and self-measurement. The frequency of diabetes mellitus was 16.9% of which 77% were previously diagnosed diabetes mellitus cases and 23% were newly diagnosed. The mean random capillary glycemia was 1.34 g/L with a standard deviation of 0.7 g/L. In decreasing order of frequency of metabolic complication diagnosed there was hyperglycaemic hyperosmolarity (48.8%) followed by diabetic ketoacidosis (39.5%). The risk factors identified for the onset of diabetes mellitus in the emergency’s unit population were age, existence of employment and body mass index. Conclusion: The risk factors for diabetes mellitus are well represented in our emergency units. The fight for primary prevention of diabetes mellitus remains a multi-ministerial challenge, as suggested by the associated factors identified in this study. All strategic plans for the fight against diabetes mellitus and non-communicable diseases in general must be built according to the One Health vision.
Background: Diabetes is a major public health problem with an estimated global prevalence of 9.3% (463 million people) by 2019 and a projection of 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045 (WHO 2013). Majority of diabetes mortality occurs in low and middle income countries where approximately 80% of people with diabetes live. Diabetes care is expensive and exerts a big economic burden on patients, their families, health systems and the society as a whole. Hence great need to evaluate indicators for a successful service delivery system. The objective of this study was to assess the diabetic care indicators and the associated factors among diabetic patients as a guide towards optimum care requirements. Methods: A cross sectional survey was conducted among diabetic patients receiving care from five health centres in Makandara sub-county between August and November 2019. Pre-tested questionnaires were used to collect the socio-demographic and quality of care data. The recruitment of the participants was done using the consecutive systematic sampling plan among the patients seeking care in the diabetic clinics and statistical analysis of data performed using excel and STATA. Results: A total of 201 diabetic patients (Male-57, Female-144) aged 18 years-93 years were interviewed. Study findings indicated that all (100%) of the facilities had clinical officers and nurses to offer quality care services but 40% of them lacked trained pharmaceutical technicians and 20% of them lacked trained laboratory technologists. Four out of five facilities had the clinical officers trained on diabetes care standards. On process of care indicators study results indicated that blood pressure and urinalysis were performed in 100% and 96.5% respectively of the patients while serum creatinine, serum lipid profiles and dilated eye examination were reported at a prevalence of 7.5%, 4.5% and 0.5% respectively. Health education was also a common practice in all the facilities which involved nutritional advice, diabetes education and exercise counselling. On diabetes management pharmacologic approach using oral hypoglycaemias was the most used method at 87%, followed by insulin at 13% and oral Insulin at 1% prevalence. On outcome of care indicators 58% of the patients had their systolic pressure below 140 mm/Hg with the overall mean of systolic blood pressure in the five facilities being 135.8 while 89% of the patients had their diastolic blood pressure below 90 mm/Hg with the overall mean in the five facilities being 78.2 mm/Hg. Conclusion: Majority of the health facilities had trained clinical officers and nurses with considerable training on diabetes management.However, lack of trained pharmaceutical technicians and laboratory technologists was hampering the quality of care given. Conclusion: Majority of the health facilities had trained clinical officers and nurses with considerable training on diabetes management. However, lack of trained pharmaceutical technicians and laboratory technologists was hampering the quality of care given.
Background: Wheat is the chief table food with wide spectrum products. Wheat sensitization (WS) is a worldwide suspected immunological problem.
Diabetic foot ulcers are associated with significant morbidity and mortality in individuals living with diabetes mellitus. It is also a leading cause of non-traumatic amputation worldwide. The most important predisposing factor for diabetic foot ulcer is peripheral neuropathy. Precedent events leading to diabetic foot ulcers include trauma, wearing of tight, fitting shoes and burns. Rat bites are an uncommon but important cause of ulcer in patients living with diabetes, especially in low socio-economic strata like Nigeria. The patient living with diabetes described here was from a rural setting and presented to us with foot ulcers secondary to rat bites. Rat bites are a very preventable cause/predisposing factor for foot ulcers and patients need to be more enlightened on measures to reduce the occurrence of foot ulcers as a result of rat bites and in addition, a good knowledge of daily foot examination by the patient.
Retinal blood vessel and retinal vessel tree segmentation are significant components in disease identification systems. Diabetic retinopathy is found using identifying hemorrhages in blood vessels. The debauched vessel segmentation helps in an image segmentation process to improve the accuracy of the system. This paper uses Edge Enhancement and Edge Detection method for blood vessel extraction. It covers drusen, exudates, vessel contrasts and artifacts. After extracting the blood vessel, the dataset is fed into CNN network called EyeNet for identifying DR infected images. It is observed that EyeNet leads to Sensitivity of about 90.02%, Specificity of about 98.77% and Accuracy of about 96.08%.
Machine learning (ML) was a rapidly advancing technology in the modern world. It had a wide variety of applications such as medical diagnosis, stock market trading, email spam, and malware filtering, etc., ML algorithms train the computer to learn from the past data and make predictions on the unknown samples. This research mainly focuses on the prediction of the PIMA Indian diabetes disease. The diabetes dataset was taken from the UCI machine learning repository. The research work was broken down into three stages. The AdaBoost technique was applied to all the features of the PIMA Indian Diabetes dataset. The correlation technique was applied for feature selection and the selected features were trained and tested with AdaBoost. A novel Hybrid Genetic Algorithm (HGA) was designed and developed for feature selection and the selected features were trained and tested with AdaBoost. Even though the correlation identifies the feature subsets based on statistical relevance but it fails in providing optimal feature subset. This drawback was overcome by the proposed novel HGA by selecting an optimal feature subset that can improve the performance of the AdaBoost model. A comparison of correlation and HGA was performed. The HGA with AdaBoost outperformed when compared with correlation with AdaBoost and AdaBoost models in terms of accuracy. The proposed methods were also applied to other datasets like the Wisconsin breast cancer diagnostic and Cleveland heart disease datasets to show its broader applications. The HGA with AdaBoost outperformed other reported techniques for the PIMA Indian diabetes
The award should motivate individuals to strive to realize their fullest potential which could, in turn, be beneficial to the field as a whole. Epic works are not only a testament to the individual’s efforts, but they also have the potential to change the whole world as they can lead to the formulation of better policies and or a new mindset.
Diabetes patients are likely increasing day by day in the recent years due to many factors. Patients mainly prefer artificial systems to provide insulin with a glucometer in an open loop insulin system. Among the commercially updated systems the most preferably used system is the hybrid closed loop system in high power computing power. In this paper a novel insulin delivery system with reduced energy and computation requirements are considered. The information regarding patient is done in the conventional manner using a continuous glucose sensor and insulin based pump. An embedded system connected to the pump and sensor will collect glucose data and process the data. The channel is connected radiofrequency signals. So the system cannot be connected to the processor which increases overall stability of the system. Based on the patient parameter configuration, automatic control should be made by the basal infusion rate of insulin bringing glycaemic level of patients to the target level. Simulated results are implemented in Uva/ Paduva simulator for the proposed algorithm.
Background The use of digital health technologies to tackle diabetes has been particularly flourishing in recent years. Previous studies have shown to varying degrees that these technologies can have an impact on diabetes prevention and management. Objective The aim of this review is to summarize the best evidence regarding the effectiveness of digital health interventions to improve one or more diabetes indicators. Methods We included all types of interventions aimed at evaluating the effect of digital health on diabetes. We considered at all types of digital interventions (mobile health, teleconsultations, tele-expertise, electronic health records, decision support systems, e-learning, etc.). We included systematic reviews published in English or French over the last 29 years, from January 1991 to December 2019, that met the inclusion criteria. Two reviewers independently reviewed the titles and abstracts of the studies to assess their eligibility, and extracted relevant information according to a predetermined grid. Any disagreement was resolved by discussion and consensus between the two reviewers, or involved a third author as referee. Results In total in our review of journals, we included 10 reviews. The outcomes of interest were clinical indicators of diabetes that could be influenced by digital interventions. These outcomes had to be objectively measurable indicators related to diabetes surveillance and management that are generally accepted by diabetes experts. Six of the ten reviews showed moderate to large significant reductions in glycated hemoglobin (HBA1c) levels compared to controls. Most reviews reported overall positive results and found that digital health interventions improved health care utilization, behaviours, attitudes, knowledge and skills. Conclusion Based on a large corpus of scientific evidence on digital health interventions, this overview could help identify the most effective interventions to improve diabetes indicators.
Marketing strategies often use some aspects of human nature balancing among ethics and profit. Sensory marketing is based on "embodied cognition" the concept that bodily sensations help to determine human decisions without conscious awareness. Consumers don't perceive such messages as marketing and don't react with the usual resistance. Taste is unique among other sensory systems in its instinctive association with mechanisms of reward and aversion, related to close contact with consumer. The background of obesity is in interaction of genetic, metabolic, behavioural and environmental factors: the rapidity with which obesity increases suggests that behavioural and environmental influences are accelerating the epidemic. Traditionally, "addiction" is applied to the abuse of drugs that activate the brain's reward pathways. There is wider understanding of the term including so-called "behavioural addictions" including compulsive overeating phenomenon. Food addiction is described as loss of control, overconsumption and withdrawal symptoms experienced in relation to highly palatable foods. It is proposed that some foods have the potential for abuse in a manner similar to conventional drug. This article argues a concept of ethic in marketing when classifying obesity as an addiction. If so, sensory marketing targeting food is doing much more harm way than we thought.
