Publicação
Assessing the Therapeutic Efficacy of GLP-1 Receptor Analogues in Overweight or Obese Individuals with Type 1 Diabetes
| Resumo: | Diabetes mellitus is a chronic disease that occurs when one cannot produce or use insulin effectively. Almost 500 million people live with this issue, which means they are more prone to comorbidities such as obesity or overweight. The current worldwide scenario is already being termed an epidemic. In order to overcome the risks associated with these clinical factors, glucagon-like peptide 1 receptors have emerged as a promising intervention as they have demonstrated multifaceted metabolic benefits. Due to the recent introduction of this pharmaceutical in people with type 1 diabetes, many studies are still unfolding to understand its limitations and long-term consequences better. Through a predictive model, this study identifies individual and clinical characteristics that may influence response to treatment. Moreover, given the high price of the drug, the model can serve as a validation tool for medical teams to assess whether the patient will achieve the expected outcome, contributing to the effective management of the substance. The results and validation metrics indicate that the predictive model successfully predicted the response to treatment and identified the factors that contributed to the success of the treatment, highlighting that the early stages of overweight are the optimal time to start the therapy. Additionally, it was found that patients with an optimised glycaemic control (low glycosylated haemoglobin levels) have less treatment efficacy. This study is especially valuable for healthcare professionals, leading to personalised treatment strategies and supporting treatment decision-making. Furthermore, it is an innovative study in terms of content since no literature combines these agonists for type 1 diabetes with a predictive perspective. |
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| Autores principais: | Cordeiro, Alexandra do Céu Gonçalves |
| Assunto: | Diabetes Obesity Glucagon-Like Peptide 1 Receptor Agonists Predictive Model SDG 3 - Good health and well-being |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Diabetes mellitus is a chronic disease that occurs when one cannot produce or use insulin effectively. Almost 500 million people live with this issue, which means they are more prone to comorbidities such as obesity or overweight. The current worldwide scenario is already being termed an epidemic. In order to overcome the risks associated with these clinical factors, glucagon-like peptide 1 receptors have emerged as a promising intervention as they have demonstrated multifaceted metabolic benefits. Due to the recent introduction of this pharmaceutical in people with type 1 diabetes, many studies are still unfolding to understand its limitations and long-term consequences better. Through a predictive model, this study identifies individual and clinical characteristics that may influence response to treatment. Moreover, given the high price of the drug, the model can serve as a validation tool for medical teams to assess whether the patient will achieve the expected outcome, contributing to the effective management of the substance. The results and validation metrics indicate that the predictive model successfully predicted the response to treatment and identified the factors that contributed to the success of the treatment, highlighting that the early stages of overweight are the optimal time to start the therapy. Additionally, it was found that patients with an optimised glycaemic control (low glycosylated haemoglobin levels) have less treatment efficacy. This study is especially valuable for healthcare professionals, leading to personalised treatment strategies and supporting treatment decision-making. Furthermore, it is an innovative study in terms of content since no literature combines these agonists for type 1 diabetes with a predictive perspective. |
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