What is diabetes mellitus?

Identification of Diabetic Patients through Clinical and Para-Clinical Features in Mexico: An Approach Using Deep Neural Networks

Diabetes is a chronic and noncommunicable but preventable disease that is affecting the Mexican population at worrying levels, being the first place in prevalence worldwide. Early diabetes detection has become important to prevent other health conditions that involve low organ yield until the patient death. Based on this problem, this work proposes the architecture of an Artificial Neural Network (ANN) for the automated classification of healthy patients from diabetics patients. The analysis was performed used a set of 19 para-clinical features to determine the health status of the patients. The developed model was evaluated through a statistical analysis based on the calculation of the loss function, accuracy, area under the curve (AUC) and receiving operating characteristics (ROC) curve. The results obtained present statistically significant values, with accuracy of 0.94 and AUC values of 0.98. Based on these results, it is possible to conclude that the ANN implemented in this work can classify patients with presence of diabetes from controls with significant accuracy, presenting preliminary results for the development of a diagnostic tool that can be supportive for health specialists.

Proposed metabolic dysfunctions in diabetic microthromboses and microangiopathy

This report describes, at least in part, the role of prostaglandin and cyclic nucleotide metabolism in the etiology of the vascular disease associated with diabetes mellitus. Alterations in this metabolism seem associated with induction of platelet aggregation leads to microthromboses leads to microangiopathy sequences that are subtle but inexorable over a long period of time. Prostaglandins are generally elevated in blood from patients having frank signs of diabetic retinopathy when compared with nondiabetic subjects. Prostaglandin concentration remained elevated in diabetic retinopathy patients receiving indomethacin. We formed, therefore, the working hypothesis--yet to be fully tested either in patients or animal models with and without indomethacin treatment--that the increased prostacyclin (synthesized by endothelial microsomes) and cyclic-AMP production, both of which favor prevention of platelet aggregation, accompany the increased concentration of one or more of the prostaglandin E and F compounds. Concurrently, there may be an accompanying reduction of thromboxane A2 (synthesized by platelet microsomes) and cyclic-GMP (both of which favor platelet aggregation) production in the diabetic patients. The elevated prostaglandin in the diabetic patients not receiving indomethacin could possibly be directed toward slowing but not preventing the progression of the complex disease process in diabetes.