Pathophysiology, Etiology, Epidemiology of Type 1 Diabetes and Computational Approaches for Immune Targets and Therapy

Dariya, Begum; Chalikonda, Gayathri; Srivani, Gowru; Alam, Afroz; Nagaraju, Ganji Purnachandra

doi:10.1615/critrevimmunol.2019033126

Cited by 21 publications

(13 citation statements)

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“…RSES is scored using a 4-point Likert scale ranging from 1 (strongly agree) to 4 (strongly disagree). The negative statements (2,5,6,8,9) are reverse scored. Higher scores indicate higher selfesteem.…”

Section: Methodsmentioning

confidence: 99%

“…Both the unidimensional and three-dimensional structures of DSAS-1-Gr are presented in Table 2. The 18 items were allocated in three factors, similar to those of the original version of DSAS-1: 'identity concerns' (2,5,7,10,13,18); 'treated differently' (3,4,6,8,12,15,19) and 'blame and judgment' (1,9,11,14,17).…”

Section: Structural Validity Exploratory Factor Analysis (Efa)mentioning

confidence: 99%

“…4 Lifelong glycaemic control is one of the main goals in the management of T1D in order to avoid diabetic ketoacidosis and to prevent future macrovascular and microvascular complications of the disease, which can lead to disability or even premature death. 5 The social and psychological burden on people with T1D is significant, regardless of the type of DM (type 1 or 2) and the method of therapy used, whether it is multiple daily injections (MDI) or continuous subcutaneous insulin injection (CSII). [6][7][8][9] Social discrimination is an aspect of the broad and complex construct of stigma experienced by 14% to 28% of the T1D patients.…”

Section: Introductionmentioning

confidence: 99%

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Dimensionality and psychometric properties of the Greek version of the Τype 1 Diabetes Stigma Assessment Scale (DSAS-1-Gr)

Benioudakis¹,

Kalaitzaki²,

Karlafti³

et al. 2022

Psychiatriki

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Section: Methodsmentioning

confidence: 99%

Section: Structural Validity Exploratory Factor Analysis (Efa)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dimensionality and psychometric properties of the Greek version of the Τype 1 Diabetes Stigma Assessment Scale (DSAS-1-Gr)

Benioudakis¹,

Kalaitzaki²,

Karlafti³

et al. 2022

Psychiatriki

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“…Większość rozpoznań tej jednostki chorobowej dotyczy dzieci, ale zdarzają się przypadki zachorowań w późniejszym okresie życia. [1,2] Leczeniem z wyboru w tej grupie pacjentów jest podaż egzogennej insuliny. W celu uniknięcia związanych z chorobą zaburzeń metabolicznych (hiperglikemia z kwasicą ketonową, śpiączka cukrzycowa, hipoglikemia) terapia insuliną powinna być zaplanowana w taki sposób, aby ich ryzyko było jak najmniejsze [1,3].…”

Section: Wprowadzenieunclassified

Omnipod® Insulin Management System - "patch-pump", as a breakthrough in the treatment of type 1 diabetes

Filipczak

Żelazny

Oliwer

et al. 2022

J Educ Health Sport

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Introduction: There are 425 million adults with diabetes worldwide, 10% of whom have type 1 diabetes. The treatment of choice in this group of patients is insulin delivery. In order to avoid disease-related metabolic disorders, insulin therapy should be planned so that their risk is minimized. This often involves multiple subcutaneous deliveries throughout the day. In order to improve patient satisfaction and comfort, , "smart pumps" have been developed. OmniPod® is the first commercially available pump of this type. Aim of the study: The purpose of our work was to present an innovative form of treatment for type 1 diabetes, to demonstrate the advantages, disadvantages and results of treatment using it. Methods and materials: A literature review was conducted in the PubMed database, using the key words: "diabetes type 1"; "diabetes mellitus"; "OmniPod®"; "insulin"; Results: OmniPod® improves glycemic control and glycated hemoglobin (HbA1c) values over traditional therapies. The algorithm used in the pump ensures normal glycemic ranges throughout the day, without the risk of prolonged episodes of hypo- and hyperglycemia. It improves the quality of life (QOL) index thanks to, among other things, water resistance, lack of difficulties during sleep in contrast to conventional insulin pumps. Conclusion: OmniPod® significantly improves users' glycemic and HbA1c control. It allows users to forgo conventional insulin pumps or intensive insulin therapy by raising QOL and increasing patients' sense of proper disease control. Further research should be inclined to evaluate the utility of OmniPod® in other types of diabetes, as well as on the application of the technology in other disease entities.

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“…The etiology factors that lead to T1D can be mainly found in autoantibodies, genetic and environmental factors [6], but some other drivers can be added to the list like gender, ethnicity, and geographical origin. It is interesting to evaluate that unlikely the most widespread autoimmune diseases that disproportionately affect females, on average, girls and boys are equally affected with T1D in young population [7].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Approach for Care Improvement of Children and Youth with Type 1 Diabetes Treated with Hybrid Closed-Loop System

et al. 2022

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Type 1 diabetes is a disease affecting beta cells of the pancreas and it’s responsible for a decreased insulin secretion, leading to an increased blood glucose level. The traditional method for glucose treatment is based on finger-stick measurement of the blood glucose concentration and consequent manual insulin injection. Nowadays insulin pumps and continuous glucose monitoring systems are replacing them, being simpler and automatized. This paper focuses on analyzing and improving the knowledge about which Machine Learning algorithms can work best with glycaemic data and tries to find out the relation between insulin pump settings and glycaemic control. The dataset is composed of 90 days of recordings taken from 16 children and adolescents. Three Machine Learning approaches, two for classification, Logistic Regression (LR) and Random Forest (RL), and one for regression, Multivariate Linear Regression (MLR), have been used for the purpose. Specifically, the pump settings analysis was performed based on the Time In Range (TIR) computation and comparison consequent to pump setting changes. RF and MLR have shown the best results, while, for the settings’ analysis, the data show a discrete correlation between changes and TIRs. This study provides an interesting closer look at the data recorded by the insulin pump and a suitable starting point for a thorough and complete analysis of them.

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Pathophysiology, Etiology, Epidemiology of Type 1 Diabetes and Computational Approaches for Immune Targets and Therapy

Cited by 21 publications

References 0 publications

Dimensionality and psychometric properties of the Greek version of the Τype 1 Diabetes Stigma Assessment Scale (DSAS-1-Gr)

Dimensionality and psychometric properties of the Greek version of the Τype 1 Diabetes Stigma Assessment Scale (DSAS-1-Gr)

Omnipod® Insulin Management System - "patch-pump", as a breakthrough in the treatment of type 1 diabetes

Machine Learning Approach for Care Improvement of Children and Youth with Type 1 Diabetes Treated with Hybrid Closed-Loop System

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