Study: This is not by controlling carbohydrates alone. Diabetes is treated

A new study conducted by a British University of Bristol research team revealed that factors that go beyond carbohydrates play a major role in regulating blood sugar levels, raising questions about the effectiveness of the current automatic insulin compounding systems. The study published in the Jmirx Med Journal indicates that these systems, despite their technological advances, do not have important information needed to improve the process of regulating blood sugar. The researcher team focused on analyzing the data of patients with type 1 diabetes and the use of modern automatic systems to connect insulin, such as the openaps system to determine the patterns in changing insulin needs into type 1 diabetes, and to analyze the frequency of these patterns. The OpenAP system depends on several main components to determine the amount of insulin needed to control glucose levels in the blood of type 1 diabetes, which is an automatic, advanced and open source system, which aims to create an artificial pancreatic system that automatically controls the insulin levels. The system depends on a set of inputs and ingredients, which include the continuous glucose monitoring device that continuously measures the blood glucose levels, usually sends data to the system every few minutes. These ongoing readings provide immediate updates on glucose levels, allowing the system to make accurate decisions regarding the required insulin doses, and then the insulin pump is used to link the specific doses to the patient’s body. The pump can be programmed to provide accurate doses based on the orders it receives from the system, as the pump is automatically programmed to adjust the basal insulin velocity and pump correctional doses based on glucose readings. Data analyzes are based on the system on smart control -algorithms; It analyzes the data received from the continuous glucose monitoring device and compares it to the targets set for glucose levels, and the patient can provide additional input that affects system decisions, such as the amount of carbohydrates eaten; If the patient takes a meal, he can enter the amount of carbohydrates into the system, which helps the algorithm to adjust the doses accordingly. In some cases, the patient may enter data on its physical activity, which helps the system to adjust insulin in a proactive way, and the system can also be programmed to take into account and control insulin. The lead author of the study, Isabella Dijin of the College of Science and Engineering at the University of Bristol, said the results confirm the current hypothesis that say there are factors that exceed carbohydrates that play an important role in maintaining natural glucose levels in the blood known as the state of yuglisimia, a condition in which glucose levels are. “Without measurable information on these factors, automatic systems deal with insulin with caution, leading to the volatility of glucose in the blood between height and decrease,” Dijin added. And Type 1 diabetes is a chronic condition in which the body produces an insufficient amount of insulin hormone, which is responsible for regulating blood glucose levels. The most important treatment for type 1 diabetes is insulin injection or by pumping advanced pumps, and its amount of insulin and its timing should be accurate with the amount of carbohydrates eaten to avoid high levels of glucose in the blood, in addition to cabbage bhydrates, there are other factors such as physical activity, hormones and tension that the body needs. However, the effects of these factors are not adequately studied, which is the process of identifying insulin doses is complicated and risky as it can lead to unstable results that may jeopardize the patient’s health. The results of the study revealed the complexity of regulating glucose levels in the blood in type 1 diabetes, as insulin needs were found to be greatly different from individuals; The need for a treatment approach is highlighted for each patient, taking into account the individual factors that affect the regulation of glucose. Determining insulin doses and not to include -carbohydrate factors in clinical practices, scientists try to find ways to accurately measure these factors and use this information to identify insulin doses. These steps can contribute to improving the accuracy of predicting glucose levels in the blood, which showed the study that it could not only be reached through insulin and carbohydrate information. The researchers believe that the study shows that the management of type 1 diabetes is more complicated than just calculating carbohydrates. The researchers confirm that the rich data that can be collected from the study of automatic insulin systems deserves the effort done in its analysis, especially in light of the large diversity in the patterns that have been observed even between a small and relatively homogeneous group of participants, and note that there is a need for an individual approach to diabetes management. Patients with Type 1 diabetes are currently working to develop new analysis techniques that deal with the nature of complex and diverse realistic medical data, including challenges of irregular temporal variations and lost data. The team focuses on developing techniques known as ‘Division and Bloc’ for types of multiple time data, with the aim of discovering more detailed patterns and dealing with the challenges offered by automated system data. To achieve progress in this area, the team seeks to obtain long -term accessible data groups, with a wide range of measurements of possible factors, with a variety of type 1 diabetes. The researchers also aim to work with experts on analyzing time data and learning the machine to meet technical challenges, such as dealing with irregular data and discovering the causal factors behind the observed patterns, with the aim of improving care for patients. The results of the study indicate the need to adopt new techniques and methods to help doctors and patients manage Type 1 diabetes; Understanding the factors affecting the individual insulin needs can make tangible progress to provide more specialized care and to avoid harmful fluctuations in glucose levels. This research reflects a tendency to improve the quality of the life of type 1 diabetes through the use of advanced technological instruments and analyzing real data.