A new system that integrates mathematical and statistical models allows the early and personalized prediction of type 2 diabetes (DT2) from the electronic medical history of each patient.
Developed by researchers from the Polytechnic University of Valencia (UPV) and the company Technologies for Health and Welfare (TSB), in collaboration with the Endocrinology and Nutrition Service of the La Fe hospital in Valencia, the new system is in the phase ofTests in this hospital and in the Fondazione Salvatora Maugeri de Pavia (Italy).
UPV sources and faith have explained to Efe that the new system, developed within the framework of the European Mosaic project, would help health professionals detect cases in advance and act in time to prevent the appearance of this disease.
As they point out from the Sabien Research Group of the ITACA Institute of the UPV, more than 90 % of people with diabetes have a diagnosis of type 2 diabetes, known as adult diabetes, and WHO estimates that in 2030 there will be about 550Millions of people with this diagnosis.
"This is a very common pathology whose appearance can be delayed and even prevented if it acts on time," Antonio Martínez Millana explained to Efe, a doctorate at the ITACA Institute of the UPV and project manager at the TSB company.
He explained that there are currently no screening mechanisms to early detect the appearance of DT2 and its diagnosis is relegated to the detection of anomalous results in analytics and is focused on identifying groups that already have a significant prevalence of microvascular complications.
"This suggests that the current methods to diagnose do not have the ability to detect precoccal symptoms of DT2," he said.
This new early detection system allows the continuous and automated stratification of the population at risk of diabetes or other associated complications, combining in the same models factors such as the nutrition or physical activity of each patient with clinical and biological data currently considered in most of the majority in mostof the analysis.
"The system consists of several modules and a series of web interfaces, which can access the different agents involved in the follow -up of patients, from the options themselves, to the managers of the hospital and researchers," he said.
Each patient identified with medium-high risk, Martínez Millana highlighted, "is marked and grouped in a priority review list, thus facilitating the work to doctors."
Within the system developed in Mosaic, researchers have created differentiated tools that allow, among other functions, to know the risk of developing DT2 for each individual and thus analyze what segment of the population is at risk of developing the disease.
In addition, it allows to obtain personalized reports for each patient about the management of the complications that they have developed or could develop throughout the clinical process.
The preliminary results of the system were presented at the Annual IEEE Engineering in Medicine and Biology Society conference, held last August in Milan (Italy).
DT2 is characterized by a resistance to insulin hormone that usually evolves towards a deficiency in the same hormone that occur at the time of clinical manifestations;Its diagnosis usually occurs at 40 years of age and is commonly associated with obesity.
The disease can go unnoticed for several years because the symptoms of hyperglycemia develop gradually and are not of sufficient entity to trigger the classical symptomatology of the diabetic.
Its diagnosis is based on analytical blood glucose determinations orGlycosylated hemoglobin.
However, these patients do run the risk of developing macrovascular complications such as cerebral spills, extremities ischemia or cardiac syndromes, and microvascular (retinopathies, neuropathies, nephropathies or extremities ischemia).
