Abstract
Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent studies have demonstrated the effectiveness of new strategies to delay and even prevent the onset of type 2 diabetes by a combination of active and healthy lifestyle on cohorts of mid to high risk subjects. Prospective research has been driven on large groups of the population to build risk scores that aim to obtain a rule for the classification of patients according to the odds for developing the disease. Currently, there are more than two hundred models and risk scores for doing this, but a few have been properly evaluated in external groups and integrated into a clinical application for decision support. In this paper, we present a novel system architecture based on service choreography and hybrid modeling, which enables a distributed integration of clinical databases, statistical and mathematical engines and web interfaces to be deployed in a clinical setting. The system was assessed during an eight-week continuous period with eight endocrinologists of a hospital who evaluated up to 8080 patients with seven different type 2 diabetes risk models implemented in two mathematical engines. Throughput was assessed as a matter of technical key performance indicators, confirming the reliability and efficiency of the proposed architecture to integrate hybrid artificial intelligence tools into daily clinical routine to identify high risk subjects.
Highlights
Diabetes is a set of pathological disorders related to an impaired insulin production and/or action [1]
Given as input the available variables in a electronic health record for a given patient or a given population, the models can estimate the probability of being at high risk and for detection models find out the most probable value of the diagnostic values [41]
Estimate the 2h-Oral Glucose Tolerance Test (2h-OGTT) glucose range given all other available variables
Summary
Diabetes is a set of pathological disorders related to an impaired insulin production and/or action [1]. Type 2 Diabetes Mellitus (T2DM) is characterized by both an insulin action resistance and a progressive dysfunction of the endogenous insulin release process. It differs from other types of diabetes by the triggering factor, which is related to unhealthy lifestyle and the long-term defect originated by aging [2]. The diagnostic test to confirm T2DM is based on the comparison of laboratory tests and specific ranges [5]. Even though the fasting glucose and the HbA1C are used to identify subjects at high risk of acquiring T2DM, the gold standard test is the Oral Glucose Tolerance test at 2 h (2h-OGTT)
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