Search results for: incomplete diabetes data

Authors: A. Satty, H. Mwambi

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Much clinical trials data-based research are characterized by the unavoidable problem of dropout as a result of missing or erroneous values. This paper aims to review some of the various techniques to address the dropout problems in longitudinal clinical trials. The fundamental concepts of the patterns and mechanisms of dropout are discussed. This study presents five general techniques for handling dropout: (1) Deletion methods; (2) Imputation-based methods; (3) Data augmentation methods; (4) Likelihood-based methods; and (5) MNAR-based methods. Under each technique, several methods that are commonly used to deal with dropout are presented, including a review of the existing literature in which we examine the effectiveness of these methods in the analysis of incomplete data. Two application examples are presented to study the potential strengths or weaknesses of some of the methods under certain dropout mechanisms as well as to assess the sensitivity of the modelling assumptions.

Keywords: incomplete longitudinal clinical trials, missing at random (MAR), imputation, weighting methods, sensitivity analysis

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Authors: Oktia Woro Kasmini Handayani, Sri Ratna Rahayu, Efa Nugroho, Berta Kalswahermawati

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Diabetes occurs 10 years faster in the Southeast Asian region than the European region, which occurs in the most productive periods. Cultural differences as well as cultural transitions can be determinant factors of health cases in urban and rural areas. The purpose of this research is to analyze the effect of the cultural environment, behavior and the occurrence of diabetes mellitus in urban areas of Semarang, Indonesia. The research was conducted in the area of Semarang Regency, using a quantitative approach and supported by qualitative data, the population is DM type 2 patients, sample size of 200 people, with a purposive sampling technique. The independent variable consists of cultural environment, behavior, and the dependent variable is DM. The data is analyzed with regression test method. Cultural environment affects behavior positively, with t value of 4,690 and p (sig.) 0.000, this means sig <0.05, while the effect of behavior on Diabetes Mellitus obtained t value 2.950 with p-value (sig.) 0.003 this means that sig <0.05, thus it can be interpreted that the behavior has a significant effect on Diabetes Mellitus. The cultural environment directly affects the incidence of DM. It can also shape a person's behavior or lifestyle or habit, whether healthy or unhealthy one, which in turn causes symptoms of DM.

Keywords: Behavior, Cultural Environment, Diebetes Millitus, Urban

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Authors: Wenru Wang

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Over the past decades, Asia has emerged as the ‘diabetes epicentre’ in the world due to rapid economic development, urbanization and nutrition transition. There is an urgent need to develop more effective and cost-effective care management strategies in response to this rising diabetes epidemic. This study aims to develop and compare a nurse-led smartphone-based self-management programme with an existing nurse-led diabetes service on health-related outcomes among type 2 diabetes patients with poor glycemic control in Singapore. We proposed a randomized controlled trial with pre- and repeated post-tests control group design. A total of 128 type 2 diabetes patients with poor glycemic control will be recruited from the diabetes clinic of an acute public hospital in Singapore through convenience sampling. Study participants will be either randomly allocated to the experimental group or control group. Outcome measures used will include the 10-item General Self-Efficacy Scale, 11-item Revised Summary of Diabetes Self-care Activities, and 19-item Diabetes-Dependent Quality of Life. Data will be collected at 3-time points: baseline, three months and six months from the baseline, respectively. It is expected that this programme will be an alternative offered to diabetes patients to master their self-care management skills, in addition to the existing diabetes service provided in diabetes clinics in Singapore hospitals. Also, the self-supporting and less resource-intensive nature of this programme, through the use of smartphone app as a mode of intervention delivery, will greatly reduce nurses’ direct contact time with patients and allow more time to be allocated to those who require more attention. The study has been registered with clinicaltrials.gov. The trial registration number is NCT03088475.

Keywords: type 2 diabetes, poor glycaemic control, nurse-led, smartphone-based, self-management, health-relevant outcomes

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Mustafa Ali Abugila

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A total of 13807 diabetic patients [(males 5893(42.68%), females 7914 (57.32%)] were on the registered in diabetic clinics in the western north of Libya at the end of 2012. Of the total clinic population, 865 patients had Type 1 IDDM (6.26%) and the rest cases had Type 2 NIDDM (93.74%). Diabetes mellitus was higher in females than in males (57.32% , 42.68%), the male to female ratio was (0.74 : 1).

Keywords: Diabetes Mellitus (DM), gestational diabetes mellitus, North Western of Libya,

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Authors: Ching-Ling Lin, Li-Chi Huang, Yao-Tsung Chang, Ruey-Yu Chen, Shwu-Huey Yang

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Introduction & Purpose: Diabetes and its related complications always been a major part of medical cost in Taiwan. To patient with diabetes, self-management blood sugar, improving a healthy lifestyle are the most important thing to avoid getting worse. The aim of this study was to explore the trend of the changing in blood glucose within intervention and followed-up periods of patients who participated in the health coaching program between 2017 and 2020. Design & Methods: The data was combined from two diabetes health coaching program. The intervention group had health coaching and usual care for 6 months, whereas the control had usual care only. The main outcome variables were HbA1c level at baseline, 3, 6, 9, and 12 months. Results: In total, the data were available for 99 patients in the coaching intervention group and for 88 patients in the control group, the dropout rate during the follow-up period is about 18%. Of 187 participants, 54% were female, mean age was 61.5 years (SD=10.19), only 32.1% had a bachelor’s degree or higher, and the mean duration of diabetes treatment at Cathay General Hospital was 9.9 years. Within 12 months, the intervention group had a significant decrease of 0.65% (SD=1.05) in HbA1c level, and a non-significant decrease of 0.13%(SD=0.96) was observed in the control group. The figure showed the effect was the most significant in the first three months of the intervention and can be maintained for up to six months after the intervention was over. The HbA1c values of the two groups at each follow-up point are significantly different. In addition, there were non-significant correlation between HbA1c and gender, age, and educational level. Conclusion: Health coaching might be an effective way to enhance self-management for patients with diabetes and improving their blood sugar control in Taiwan.

Keywords: diabetes, health coaching, HbA1c, self-management

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Authors: Samereh Abdoli, Amit Vora, Anusha Vora

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Aim: To qualitatively investigate diabetes burnout in parents of children with Type 1 Diabetes (T1D) who shared their experiences through YouTube videos in order to inform future interventions and improve diabetes practice. Methods: A qualitative descriptive approach was used to explore YouTube videos. Of the 568 videos that were identified, only 9 videos met the inclusion criteria of the study. Results: After the videos were transcribed and analyzed using qualitative content analysis, it was revealed that parents shared common concerns and experiences and they translated into three main themes: I do not ever get a break, I am exhausted, I can’t burn out, and I just need a break Conclusion: All in all, the literature revealed that there are negative psychosocial outcomes associated with caring for a child with T1D, but there is a lack of information on diabetes burnout and how parents’ well-being are affected. Reports of self-neglect and sleep deprivation only confirm the need for intervention for parents of children with T1D. The hope with this study is that burnout can be recognized early on and appropriate interventions put in place to help parents cope with the stressors of caring for a child with a chronic disease.

Keywords: Diabetes burnout, type 1 diabetes, qualitative research, parents

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Authors: Elly Usman, S. Dante, Diah Purnamasari

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Type 2 diabetes mellitus ( T2DM ) is a syndrome characterized by a state of increased blood sugar levels due to chronic disorders of insulin secretion by pancreatic beta cells and insulin action or a combination of both. The organic cation transporter 1, encoded by the SLC22A1 gene, responsible for the uptake of the antihyperglycemic drug, metformin, in the hepatocyte. We assessed whether a genetic variation in the SLC22A1 gene was associated with the glucose - lowering effect of metformin. Method case study research design. Samples are children with type 2 diabetes mellitus who meet the inclusion criteria. The results proportions SLC22A1 gene polymorphisms in children with diabetes mellitus type 2 amounted to 52.04 % at position 400T/C, there is one heterozygous and one at position 595T/C Conclusion The presence of SLC22A1 gene polymorphisms in children with diabetes mellitus type 2.

Keywords: diabetes Mellitus type 2, metformin, organic cation transporter 1, pharmacogenomics

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Mohammad Abdullah-Al-Wadud

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In the current era of automation and artificial intelligence, different systems have been increasingly keeping on depending on decision-making capabilities of machines. Such systems/applications may range from simple classifiers to sophisticated surveillance systems based on traditional sensors and related equipment which are becoming more common in the internet of things (IoT) paradigm. However, the available data for such problems are usually imprecise and incomplete, which leads to uncertainty in decisions made based on traditional probability-based classifiers. This requires a robust fusion framework to combine the available information sources with some degree of certainty. The theory of evidence can provide with such a method for combining evidence from different (may be unreliable) sources/observers. This talk will address the employment of the Dempster-Shafer Theory of evidence in some practical applications.

Keywords: decision making, dempster-shafer theory, evidence fusion, incomplete data, uncertainty

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Authors: Suhaib Radi, Ibrahim Basem Nafadi, Abdullah Ahmed Alsulami, Nawaf Faisal Halabi, Abdulrhman Abdullah Alsubhi, Sami Wesam Maghrabi, Waleed Saad Alshehri

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Background: Kidney stones greatly affect individuals. The range of these effects regarding multiple kidney stone factors (size, presence of obstruction, and modality of treatment) in stone formers with and without diabetes has not been well explored in the literature to the best of the author's knowledge. Our goal is to investigate this unexplored correlation between diabetes and kidney stones by conducting a Cohort retrospective study to precisely evaluate the effects of this condition and the existence of complications in adult individuals with diabetes in Saudi Arabia in comparison to a non-diabetic control group. Methodology: This is a retrospective cohort study aiming to evaluate the range of effects of kidney stones in stone formers in a group of adults diagnosed with type 2 diabetes mellitus and adults without diabetes between 2017 and 2019 in Jeddah, Saudi Arabia. An IRB approval has been granted for this study. The data was analyzed using SPSS. The data was collected from the 1st of December 2022 until the 1st of March 2023. Results: A total of 254 individuals diagnosed with kidney stones were included, 127 of whom were adult individuals with type 2 diabetes, and 127 were non-diabetics. Our study shows that the individuals affected with diabetes were more likely to have larger kidney stones in comparison to individuals without diabetes (13.12 mm vs. 10.53 mm, p-value = 0.03). Moreover, individuals with hypertension and dyslipidemia also had significantly larger stones. On the other hand, no significant difference was found in the presence of obstruction and modality of treatment between the two groups. Conclusion: This study done in Saudi Arabia found that individuals with kidney stones who concurrently had diabetes formed larger kidney stones, and they were also found to have other comorbidities such as HTN, dyslipidemia, obesity, and renal disease. The significance of these findings could assist in the future of primary and secondary prevention of renal stones.

Keywords: kidney stone, type 2 DM, metabolic syndrome, lithotripsy

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Authors: Naveen Kumar Challa, Pavan Verıkıcherla, Madhubalan, Ashısh Sharma

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Aim: Aim of the study was to find whether any difference exists in pupil mydriasis measured with Orbscan in non-diabetic and type 2 diabetic patients at various intervals after installation of Tropicamide 0.8% and Phenylephrine 5%. Methods: the Observational study conducted at a tertiary care eye hospital during September 2014 to March 2015. 240 eyes from 120 patients (40 non-diabetic, 80 diabetic) were dilated with Tropicamide 0.8% and Phenylephrine 5%. One drop of a drug was installed twice. The second drop is installed at 20 minutes after installation of the first drop. In two groups’ pupil diameter was measured before installation of drops and also at 15, 30, 45 and 60 minutes after installation of the first drop using both Orbscan. Result: Mean age of the non-diabetic group is 48.67 ± 7.93 years; Diabetic group is 59.97 ± 8.77 years. Mean duration of Diabetes was 7.01 ± 5.05 years. Mean pupil diameter measured with Orbscan before installation of the drops and also at 15, 30, 45 and 60 minutes after installation of first drop in non-diabetic group was 4.18 ± 0.64mm, 6.15 ± 0.41mm, 7.76 ±0.34, 9.59 ± 0.30, and 9.97 ± 0.10 mm respectively and for the diabetic group it was 4.00 ± 0.56 mm, 5.53 ± 0.52 mm, 7.018 ± 0.58mm, 8.25±0.51mm and 9.18 ± 0.46mm respectively. The mean difference between the mean pupil diameters of the non-diabetic and diabetic group shows a significant difference (P< 0.01) at all intervals except before dilatation. There is a significant negative correlation (r = 0.78 – 0.92) between the duration of diabetes and pupil dilatation at all intervals after installation of the drops. There is also significant difference (P< 0.005) in the mean values of pupil diameter between non retinopathy diabetic subjects and diabetic retinopathy subjects at all intervals after installation of drops. Conclusion: People attending eye clinic, whose pupil mydriasis values falls below the normal may be referred for diabetic evaluation. If normative data is established for the pupil size in Indian population using Orbscan then the values fall under normative data could be a predictor for diabetes. This would in turn help ophthalmologist to detect the diabetes at an early stage and prevent the complications resulting from the diabetes.

Keywords: diabetes mellitus, pupil diameter, orbscan, tropicamide

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

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Authors: E. H. N. Gashti, J. Razzaghi, K. Kujala

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In general, codes and regulations consider seismic loads only for completed structures of the bridges while, evaluation of incomplete structure of bridges, especially those constructed by free cantilever method, under these loads is also of great importance. Hence, this research tried to study the behavior of incomplete structure of common bridge type (box girder bridge), in construction phase under vertical seismic loads. Subsequently, the paper provided suitable guidelines and solutions to withstand this destructive phenomena. Research results proved that use of preventive methods can significantly reduce the stresses resulted from vertical seismic loads in box cross sections to an acceptable range recommended by design codes.

Keywords: box girder bridges, prestress loads, free cantilever method, seismic loads, construction phase

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Authors: Carolyne Ndungu, Wesley Too, Diana Kassaman

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Diabetes is a global public health problem with an increasing morbidity and mortality rate across the globe. It is reported that 422 million people worldwide have diabetes with type 2 diabetes more common in people of African descent. Whilst prevalence of diabetes is four times more than it was in the last three decades, making it the world's ninth greatest cause of mortality, treatment of complications resulting from poor glycemic control is still high, contributing to poverty level in sub-Saharan. Poor treatment adherence has also been identified as a major contributing factor poor glycemic control among diabetic patients and still remains a significant challenge especially among patients living in rural Kenya. This study therefore seeks to identify gaps, barriers and challenges towards medication non-adherence among diabetic patients on follow-up at Kiambu County Referral Hospital, Kenya. Methods: A cross- sectional descriptive study was carried out at Gatundu Level five Hospital in Kiambu County. The study population consisted of adult patients with type two diabetes mellitus (T2DM) on follow up, at the Diabetes clinic between the month of June to July 2022. Systematic sampling of 200 participants was carried out. Ethical approvals from relevant authorities were done and ethical aspects of the study were also observed. Data analysis is ongoing using logistic regression analysis. Results, recommendations -contribution of this study will be highlighted within the next one month.

Keywords: adherence, diabetes, medication, Kenya

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Authors: Garadi Ahmed, Boubakar S. Bouazza

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The Zero Cross-Correlation (C, w) code is a family of binary sequences of length C and constant Hamming-weight, the cross correlation between any two sequences equal zero. In this paper, we evaluate the performance of ZCC code based on Balanced Incomplete Block Design (BIBD) for Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system using direct detection. The BER obtained is better than 10-9 for five simultaneous users.

Keywords: spectral amplitude coding-optical code-division-multiple-access (SAC-OCDMA), phase induced intensity noise (PIIN), balanced incomplete block design (BIBD), zero cross-correlation (ZCC)

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Authors: Ferreira RC, Simons HZ, Thompson WS, Cutler AJ, Dopico XC, Smyth DJ, Mashar M, Schuilenburg H, Walker NM, Dunger DB, Wallace C, Todd JA, Wicker LS, Pekalski ML

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Type 1 diabetes is caused by autoimmune destruction of insulin-secreting beta cells in the pancreas. T cells are known to play an important role in this immune-mediated destruction; however, there is no general consensus regarding alterations in cytokine production or T cell subsets in peripheral blood of patients with type 1 diabetes. Using polychromatic flow cytometry of peripheral blood mononuclear cells (PBMCs), we assessed production of the proinflammatory cytokines IL-21, IFN-γ and IL-17 by memory CD4 T effector (Teff) cells in 69 patients with type 1 diabetes and 61 healthy donors. We found a 21.9% (95% CI 5.8, 40.2; p = 3.9 × 10(-3)) higher frequency of IL-21(+) CD45RA(-) memory CD4(+) Teffs in patients with type 1 diabetes (geometric mean 5.92% [95% CI 5.44, 6.44]) compared with healthy donors (geometric mean 4.88% [95% CI 4.33, 5.50]). In a separate cohort of 30 patients with type 1 diabetes and 32 healthy donors, we assessed the frequency of circulating T follicular helper (Tfh) cells in whole blood. Consistent with the increased production of IL-21, we also found a 14.9% increase in circulating Tfh cells in the patients with type 1 diabetes (95% CI 2.9, 26.9; p = 0.016). Analysis of IL-21 production by PBMCs from a subset of 46 of the 62 donors immunophenotyped for Tfh showed that frequency of Tfh cells was associated with the frequency of IL-21+ cells (r2 = 0.174, p = 0.004). These results indicate that increased IL-21 production is likely to be an aetiological factor in the pathogenesis of type 1 diabetes that could be considered as a potential therapeutic target.

Keywords: T follicular helper cell, IL-21, IL-17, type 1 diabetes

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Authors: Issam M Hajjaji, Adel Tajoury, Salah R Benhamid

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The MENA region has the highest prevalence of diabetes in the world. Various risk scores were developed, not all appropriate locally. The objective of this study is to apply the FINDRISC Score to adult Libyan males to determine its significance, sensitivity, specificity and Positive Predictive Values as an initial screening tool for type 2 diabetes, and suggest a cut-off point. Methods: 600 subjects answered the questionnaire at their place of work, and their waist, weight, height & BP were measured. Thereafter, after excluding those with known diabetes, an Oral Glucose Tolerance Test was done. Results: 414 subjects aged 19-78 completed the questionnaire and tests. 35 (8.4%) had impaired glucose tolerance (IGT) and 13 (3.1%) had diabetes (DM). The AUC-ROC for IGT was 0.614 (95% CI: 0.527-0.701), for DM 0.810 (95% CI: 0.709-0.911) and for both 0.689 (95% CI: 0.609-0.769). The Positive Predictive Value for a cut-off score of 5 were 15.5%, 11.7% & 5.7% for both conditions combined, prediabetes & diabetes respectively. The equivalent values for a cut-off score of 8 were 16.1%, 9.0% & 7.7%. The Negative Predictive Values were uniformly above 90%. Conclusions & Recommendations: The FINDRISC Score had a low predictive value for dysglycaemia in this sample and performed at a level of significance for IGT that is similar to other MENA countries, but did better for DM. A larger sample that included women is suggested, with a view of adjusting the Score to suit the local population.

Keywords: diabetes, FINDRISK, Libya, prediabetes

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Authors: Vijay Kr. Yadav, Nilam Rathi

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Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

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Authors: Ram Sharan Mehta, Dina Khanal, Pushpa Parajuli, Gayanand Mandal, Bijaya Bartuala

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Background: Cardiovascular disease (CVD) is the leading cause of death worldwide. Adequate awareness of risk factors of CVD is the first step towards effective preventive strategies to combat the CVD burden in diabetes patients.This study aims to assess the awareness on risk factors of CVD among patients with diabetes mellitus attending diabetic clinic of BPKIHS and to find the association between awareness with their selected socio demographic variables. Methods and Material: A descriptive cross sectional study was conducted among 112 patients with diabetes in diabetic clinic of BPKIHS. Convenient sampling technique was used for data collection over duration of one month using interview schedule by HDFQ II tool. Data were analyzed by using descriptive and inferential statistics. (Chi square). Results: The mean age of respondents was 55.4±12.13 years. That mean HDFQ score was 14.31± 5.08. Only 33% of the respondents had adequate level of awareness whereas majority of the respondents (67%) had inadequate level of awareness. Majority of the respondent (83.9%) were aware about smoking, (78.6%) physical activity, (75%) increasing age, (75.9%) high blood pressure, (71.4%) overweight respectively. Whereas most of the respondents were not aware of high cholesterol, fatty diet, preventive strategies and association of diabetes with CVD. Awareness was statistically significant with (p=0.043) educational status, (p=0.025) monthly income, (p=0.05) residence, (p=0.006) CVD information received and (p=0.022) co morbid condition as a heart disease. Conclusion: The findings of this study concluded most of the respondents had an inadequate level of awareness on risk factors of CVD. So Effective education and appropriate preventive strategies of CVD are indeed important to reduce CVD burden in diabetes patients.

Keywords: cardiovascular disease, awareness, diabetes patients, risk

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Authors: Chun-Chin Huang

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Individuals with prediabetes increase the risk of developing type 2 diabetes. Exercise is a potent stimulator of skeletal muscle glucose uptake and thus good for maintaining glucose homeostasis. That could be a conducive method to improve blood glucose regulation and prevent type 2 diabetes without medication intake. The aim of this study was to summarize mechanisms of insulin resistance and investigate the beneficial effects of acute and chronic aerobic exercise on glycemic control in prediabetes and type 2 diabetes. Aerobic exercise regulates glucose homeostasis and reduces blood glucose, insulin concentrations. Therefore, the type of aerobic exercise brings positive effects to prediabetes and type 2 diabetes.

Keywords: insulin resistance, glucose sensitivity, impaired fasting glucose, impaired glucose tolerance

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Authors: Jisun Jun, Eun Ko, Sooim Shin, Kitae Kim, Moonsung Choi

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Diabetes is a metabolic disease characterized by hyperglycemia, insulin resistant, mitochondrial dysfunction. Diabetes is associated with the development of diabetic retinopathy resulting in worsening vision and eventual blindness. In this study, eyes were enucleated from glucose-immersed zebrafish which is a good animal model to generate diabetes, and then mitochondria were isolated to evaluate activities of mitochondrial electron transfer complexes. Surprisingly, the amount of isolated mitochondria was increased in eyes from glucose-immersed zebrafish compared to those from non-glucose-immerged zebrafish. Spectrophotometric analysis for measuring activities of mitochondrial complex I, II, III, and IV revealed that mitochondria functions was even enhanced in eyes from glucose-immersed zebrafish. These results indicated that 3 days or 7 days glucose-immersion on zebrafish to induce diabetes might contribute metabolic compensatory mechanism to restore their mitochondrial homeostasis on the early stage of diabetes in eyes.

Keywords: diabetes, glucose immersion, mitochondrial complexes, zebrafish

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Authors: Balasaheb Bansode

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Diabetes is a very important component in non-communicable diseases. Diabetes ailment is a route of the multi-morbidities ailments. The South Indian states are almost completing the demographic transition in India. The study objectives present the prevalence of diabetes and its association with co-morbidities among the south Indian women. The study based on National Family Health Survey fourth round (NFHS) 4 conducted in 2015-16. The univariate, bivariate and multivariate analyses techniques have been used to find the association of risk factors and comorbidities with diabetics. The result reveals that the prevalence of diabetes is high among South Indian women. The study shows the women with diabetics have more chances to diagnose with hypertension and anemia comorbidities. The factors responsible for co-morbidities are changing the demographic situation, socioeconomic status, overweight and addict with substance use in South India. The awareness about diabetes prevention and management should be increased through health education, disease management programmes, trained peers and community health workers and community-based programmes.

Keywords: diabetes, risk factors, comorbidities, women

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Authors: Sara Alzahrani, Samia Bokari, Patan Khan, Muneera Alshareef, Rania Safwat, Mohammed Galal, Hamdi Alqadi, Ameerah Alzahrani, Rehab Alboraie

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Introduction & Background: Diabetes in COVID-19 patients is individual risk factor and documented in worldwide studies to contribute to disease severity, increased length of stay and higher mortality. Aggressive management of blood sugars and acute diabetic complications reduce the length of stay and mortality. Methods: Randomly selected 200 patients admitted with diabetes and COVID-19 studied. The unified treatment protocol applied for all patients and blood sugars monitored closely and optimized .Data collected on bimonthly basis and analyzed. Patients’ characteristics taken from data extraction tool (Oasis) of hospital. Median values for length of stay and post discharge FBS and RBS were calculated via Microsoft Excel tool. Mortality rates were calculated by percentages. The results monitored in the post discharge clinic was 130 mg/dl and 170 mg/dl respectively. The results compared with the standard international studies. Discussion: Diabetes in COVID-19 patients posed great challenge as increased severity and mortalities reported compared to non-diabetic. Taking a pre-emptive strategy to combat this problem by aggressively manage diabetes help in reducing length of stay and morbidity. The length of stay in studded population was 3 days as compared to 13 days in a major international study. Financial saving come from rapid turnover of beds. The mortality was 2.5 % compared to reported 7.3% in a major study, reflecting the implications of aggressive management of diabetes. Regular follow-up and support by running post-discharge clinic definitely help reducing readmissions and acute complications of uncontrolled diabetes. Conclusion: Aggressive management of diabetes in COVID-19 patients by tailored treatment protocols and dedicated teams will help to decrease the morbidity and mortality.

Keywords: diabetes, covid-19, management, mortality

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Authors: Riyas Peringattuthodiyil, Mark Taylor, Ian Wallace, Ailish Nugent, Mike Mitchell, Judith Thompson, Allison McKee, Philip C. Johnston

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Aim of Study: The purpose of the study was to screen for diabetes through HbA1c in patients with chronic pancreatitis (CP) within the Belfast Trust. Background: Patients with chronic pancreatitis are at risk of developing diabetes, earlier diagnosis with subsequent multi-disciplinary input has the potential to improve clinical outcomes. Methods: Clinical and laboratory data of patients with chronic pancreatitis were obtained through the Northern Ireland Electronic Healthcare Record (NIECR), specialist hepatobiliary, and gastrointestinal clinics. Patients were invited to have a blood test for HbA1c. Newly diagnosed patients with diabetes were then invited to attend a dedicated Belfast City Hospital (BCH) specialist chronic pancreatitis and diabetes clinic for follow up. Results: A total of 89 chronic pancreatitis patients were identified; Male54; Female:35, mean age 52 years, range 12-90 years. Aetiology of CP included alcohol 52/89 (58%), gallstones 18/89 (20%), idiopathic 10/89 11%, 2 were genetic, 1: post ECRP, 1: IgG autoimmune, 1: medication induced, 1: lipoprotein lipase deficiency 1: mumps, 1: IVDU and 1: pancreatic divisum. No patients had pancreatic carcinoma. Mean duration of CP was nine years, range 3-30 years. 15/89 (16%) of patients underwent previous pancreatic surgery/resections. Recent mean BMI was 25.1 range 14-40 kg/m². 62/89 (70%) patients had HbA1c performed. Mean HbA1c was 42 mmol/mol, range 27-97mmol/mol, 42/62 (68%) had normal HbA1c (< 42 mmol/mol) 13/62 (21%) had pre-diabetes (42-47mmol/mol) and 7/62 (11%) had diabetes (≥ 48 mmol/mol). Conclusions: Of those that participated in the screening program around one-third of patients with CP had glycaemic control in the pre and diabetic range. Potential opportunities for improving screening rates for diabetes in this cohort could include regular yearly testing at gastrointestinal and hepatobiliary clinics.

Keywords: pancreatogenic diabetes, screening, chronic pancreatitis, trust experience

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Authors: Ismail Okur, Betul Taspinar, Turkan Pasali Kilit, Eda O. Okur, Ferruh Taspinar

Abstract:

Type 2 Diabetes Mellitus (T2DM) is one of the most important global health emergencies and every year more and more people are affected by T2DM. T2DM causes life-changing complications by affecting organ and systems. Although diet and exercise are the best way to treat patients with T2DM, those patients generally have a sedentary life style. This study was planned to determine whether patients with T2DM have kinesiophobia (fear of movement). A controlled trial was conducted on 87 adults. Forty-one individuals with T2DM (study group, 34 female and 7 male) and 46 nondiabetic individuals (control group, 39 female and 7 male) were included in the study. Patients were screened for fear of movement using the Tampa Scale for Kinesiophobia (TSK). The data including age, sex, weight, height, and TSK scores were obtained. Mann Whitney U test were used to analyse the data. The mean ages and BMI of study and control groups were 51.98 ± 6.03 year and 49.52 ± 5.61 year and 31.82 ± 2.88 kg/m2 and 30.22 ± 2.91 kg/m2, respectively. The groups have similar demographic properties. The kinesiophobia scores of study and control groups were 42.78 ± 5.50 and 39.48 ± 5.05, respectively and the difference was statistically significant (p=0.05). This study showed that patients with T2DM had high kinesiophobia scores rather than nondiabetics. Those patients might avoid to do exercise. In other words, patients with T2DM might have lower physical activity level. Therefore the authors suggest that to evaluate and interfere with kinesiophobia before conducting exercise therapy will be useful for diabetes care.

Keywords: diabetes, fear of movement, kinesiophobia, type 2 diabetes mellitus

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Authors: Noor A. Hakim

Abstract:

Several studies in the developed countries investigated the prevalence of diabetes and obesity among individuals from different socioeconomic levels and suggested lower rates among the higher socioeconomic groups. However, studies evaluating diabetes risk and prevalence of obesity among the population of middle- to high-income status in developing countries are limited. The aim of this study is to evaluate the risk of developing type-2 diabetes mellitus (T2DM) and the weight status of female students in private universities in Jeddah City, Saudi Arabia. This is a cross-sectional study of 121 female students aged ≤ 25 years old was conducted; participants were recruited from two private universities. Diabetes risk was evaluated using the Finnish Diabetes Risk Score. Anthropometric measurements were assessed, and body-mass-index (BMI) was calculated. Diabetes risk scores indicated that 35.5% of the female students had a slightly elevated risk, and 10.8% had a moderate to high risk to develop T2DM. One-third of the females (29.7%) were overweight or obese. The majority of the normal weight and underweight groups were classified to have a low risk of diabetes, 22.2% of the overweight participants were classified to have moderate to high risk, and over half of the obese participants (55.5%) were classified to be at the moderate to high-risk category. Conclusions: Given that diabetes risk is alarming among the population in Saudi Arabia, healthcare providers should utilize a simple screening tool to identify high-risk individuals and initiate diabetes preventive strategies to prevent, or delay, the onset of T2DM and improve the quality of life.

Keywords: risk of type 2 diabetes, weight status, college students, socioeconomic status

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Authors: M. Nasiri

Abstract:

Aim: Considering the hypoglisimic ad hipolipidimic effect of the fenugreek seed and aerobic exercise training, this study was conducted to evaluate the effect of fenugreek and aerobic exercise training on insulin resistance in women with type 2 diabetes. Methodology: 32 patients with type II diabetes were selected and randomly divided into four groups: control, fenugreek, training and fenugreek - training. Fenugreek groups used 10 grams of fenugreek seeds daily for eight weeks on two occasions before noon and evening meal. Training of groups is also performed a regular program of aerobic exercise 65-55% of maximum heart rate (4 days per week).Two days before and after the training period, blood samples were taken from their brachial veins in a fasting state (12 hours prior to the test) in a sitting position. The data was analyzed used of t-independent and ANOVA at a significance level of α < 0.05. Results: Intra-group changes in all experimental groups showed that significant decrease insulin resistance, and the difference between groups showed significant difference between the groups of fenugreek - training than other groups there. Conclusions: According to the research findings to fenugreek combined with aerobic exercise more beneficial effect on the inhibition of insulin resistance in women with diabetes are recommended to them.

Keywords: fenugreek, training, insulin resistance, diabetes

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Authors: Mehak Nagpal, T. S. Sathyanarayan Rao

Abstract:

Background: Sexual functioning is a neglected aspect of health in women with diabetes, though it contributes greatly towards quality of life and feeling of wellbeing. Also women with DM are at higher risk than men of developing sexual dysfunction and depression. Materials and Methods: Cross-sectional comparison study. Sample size: 100 previously diagnosed type 2DM patients attending Outpatient Diabetic Clinic at Medicine department JSS Hospital Mysore; aged 20-65 years and 60 normal healthy female subjects for Control group. Data was collected with ethical approval over a period of 2 years. Tools Used: 1) Hamilton Depression Rating Scale (HAMD – 17 item) 2) Female Sexual Functioning Index (FSFI) 3) Arizona Sexual Experience Scale (ASEX-F) for female-for screening. 4) The Appraisal of Diabetes Scale (ADS). Results: Statistically significant differences were observed in prevalence rate and severity of depression between diabetic group (45% vs 11% syndromal depression) and controls. Depression scores correlated significantly with glycaemic control, adherence to treatment, BMI and the cognitive appraisal of diabetes. There was significantly greater impairment in the sexual functioning of women with type 2 diabetes mellitus as compared to controls; both prevalence (62% vs 38.3%) and severity (p value < 0.01). Arousal (74.2% vs 53.3%), Desire (76.3% vs 50%) and Satisfaction (76.7% vs 63.7%) were most affected and 64.5% were affected in 2 or more domains. A negative illness appraisal on ADS correlated significantly with poor glycaemic control, higher rates of depression and also more severe female sexual dysfunction (p value < 0.05). Conclusion: Diabetes specific factors that correlated significantly with FSD in this study included the psychological appraisal of diabetes, duration of diabetes, presence of complications and BMI.

Keywords: depression, female sexual dysfunction, India, type 2 diabetes mellitus

Procedia PDF Downloads 317

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

Abstract:

In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

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